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My internship experience as a Finance Intern at Gerresheimer

December 21, 2025 by Tibor HAUER

In this article, Tibor HAUER (ESSEC Business School, Global Bachelor in Business Administration (GBBA), Exchange semester 2025) shares his professional experience as a Finance Intern at Gerresheimer.

About the company

Gerresheimer is a globally operating partner for the pharmaceutical, biotech and cosmetics industries and plays an important role in the international healthcare value chain. As a specialist in primary packaging and drug delivery solutions, the company develops and manufactures products such as vials, syringes, ampoules, inhalers and innovative digital health applications that support safe and reliable treatment for patients worldwide. These products must meet strict regulatory requirements, and Gerresheimer combines decades of manufacturing expertise with continuous technological development to meet these standards. In the 2024 financial year, the company generated a consolidated revenue of around € 2.04 billion, underscoring its strong position in the global healthcare market.

With more than 40 production sites and development centers across Europe, the Americas and Asia, the company serves a broad and diverse customer base ranging from global pharmaceutical corporations to emerging biotech firms. This international footprint allows Gerresheimer to operate close to its customers, ensure stable supply chains and respond efficiently to market needs. In addition to its manufacturing capabilities, the company places strong emphasis on quality management, process reliability and long-term partnerships, which form the foundation of its reputation as a trusted industry partner.

Logo of Gerresheimer.

Source: the company.

Within the group, I worked in the Treasury, Tax & Insurance function at Gerresheimer’s Regensburg site. The department is responsible for managing liquidity, financial risks and insurance topics across the company. It also supports tax related processes. Its core activities include cash and liquidity management, monitoring foreign exchange risks, handling payment processes and supporting selected tax and insurance matters. In addition, I worked in the Plant Controlling team at the production site in Pfreimd. This team supports the financial management of manufacturing operations. Its work focuses on cost controlling, performance monitoring and reporting at plant level.

My internship

I joined Gerresheimer from March to July 2025 as a Finance Intern. During my internship, I worked in different finance-related teams and gained practical experience in both central finance functions and a production oriented controlling environment. From the beginning, I was integrated into the daily work of the teams and supported ongoing processes as well as ad hoc tasks. I worked independently on defined responsibilities while closely collaborating with experienced colleagues. This allowed me to quickly understand internal processes and apply theoretical knowledge in a practical setting. The internship combined recurring operational tasks with analytical work. I was involved in daily and weekly finance activities, but also supported analyses and reports that were used for internal decision making.

My missions

My responsibilities covered a broad range of tasks across Treasury, Controlling and Tax. In Treasury, I supported liquidity related activities by preparing cash overviews and maintaining rolling liquidity forecasts. I also analyzed foreign exchange exposures using SAP data. SAP is an enterprise resource planning system that is widely used by large organizations to manage and integrate financial and operational data. In addition, I supported the preparation and follow up of hedging activities. Through my involvement in payment processes and selected credit related topics such as guarantees and fees, I gained insight into how financial risks are managed in an international environment.

In addition, I worked closely with the Controlling function, where I contributed to weekly revenue planning and prepared blocked stock reports to improve transparency regarding inventory risks. I supported forecasting and planning activities. Moreover I assisted in analyzing the management profit and loss statement by cost categories. This work helped me understand how financial planning and performance monitoring support managerial decision making.

Beyond recurring tasks, I prepared financial models and scenario analyses for internal investment related questions and supported ad hoc analyses requested by management. I also assisted in the preparation of monthly and quarterly reports and supported management meetings by drafting clear and structured summaries. In the area of Tax, i supported VAT related topics, electricity and energy tax refunds, as well as transfer pricing documentation and tax audits.

Required skills and knowledge

This position required a combination of technical and analytical skills. A strong command of Excel was essential for working with financial data, preparing forecasts, building models and performing analyses. Regular use of SAP and planning systems supported the handling of large datasets and reporting processes. A solid understanding of finance and controlling concepts was necessary to interpret financial figures, analyze performance and support planning and decision-making processes.

On the soft skills side, accuracy and a structured way of working were particularly important, especially when dealing with liquidity data, forecasts and reports. Strong communication skills were required, as I regularly coordinated with colleagues from different finance related functions and prepared summaries for management. In addition, a proactive and reliable working style helped me adapt quickly to new tasks, manage parallel responsibilities and contribute effectively in a dynamic finance environment.

What I learned

Through this internship, I gained a comprehensive understanding of how finance functions support the operations and decision-making processes of an international industrial company. I learned how liquidity is managed in practice and how financial data is used to monitor risks and ensure financial stability across different entities. In addition, I developed a solid understanding of planning, forecasting and controlling processes and their role in operational and strategic steering.

On a personal level, I became more confident in working independently with complex financial data and presenting results in a clear and structured way. I learned how to prioritize tasks, manage parallel responsibilities and communicate effectively with colleagues from different finance related functions. Overall, this internship confirmed my strong interest in finance and motivated me to pursue further roles in this field.

Financial concepts related to my internship

I present below three key financial concepts related to my internship: liquidity management and forecasting, rolling planning and forecasting, and foreign exchange risk management.

Liquidity management and forecasting

Liquidity management is a core responsibility of the Treasury function and is essential to ensure that a company can always meet its financial obligations. It involves monitoring cash positions, forecasting future cash flows and managing short- and medium-term liquidity needs. During my internship, I supported liquidity management by preparing cash overviews and maintaining rolling liquidity forecasts. This helped me understand how liquidity planning supports financial stability and enables companies to react to changing cash flow situations in a timely manner.

Rolling planning and forecasting

Rolling planning and forecasting is an important concept in controlling and financial steering. Unlike a static annual budget, rolling forecasts are updated regularly to reflect the latest business developments. During my internship, I supported the rolling revenue planning process, including forecasts, budgeting and strategic planning in the GRIPS planning system (an internal corporate planning tool used to consolidate, analyze and manage financial plans across different business units). This approach allows management to respond more flexibly to changes in market conditions and provides a more reliable basis for operational and strategic decision making.

Foreign exchange risk management

Companies operating internationally are exposed to foreign exchange risks, as revenues, costs and cash flows often occur in different currencies. Foreign exchange risk management aims to identify these exposures and reduce their impact on financial results. During my internship, I analyzed foreign exchange exposures using SAP data and supported the preparation and follow up of hedging activities. This experience gave me practical insight into how currency risks are monitored and managed in order to stabilize cash flows and protect margins.

Why should I be interested in this post?

If you are a business or finance student interested in roles in finance, treasury or controlling, this experience provides valuable insight into how financial processes support an international industrial company. The internship offers exposure to both central finance functions and a production focused controlling environment, combining analytical work with operational relevance.

You gain practical experience in areas such as liquidity management, forecasting, risk management and reporting, while working closely with different finance related teams. This combination helps develop strong analytical skills, a structured way of working and a solid understanding of how finance contributes to informed decision making in practice.

Useful resources

Business

Gerresheimer AG

Gerresheimer Job postings

Gerresheimer Annual Reports and Investor Presentations

European Association of Corporate Treasurers

Academic articles and books

Bragg, S. M. (2017) Treasury Management: The Practitioner’s Guide 1st ed., Hoboken (NJ), Wiley.

Brealey, R. A., Myers, S. C., & Allen, F. (2025) Principles of Corporate Finance, 15th ed., New York (NY), McGraw-Hill Education.

Ernst, D., & Häcker, J., 2015. Corporate Risk Management: A Case Study on Risk Evaluation Cham (Switzerland), Springer.

Aretz, K., Bartram, S. M., & Dufey, G., 2007. Why hedge? Rationales for corporate hedging and value implications, The Journal of Risk Finance, 8(5), 434–449.

About the author

The article was written in December 2025 by Tibor HAUER (ESSEC Business School, Global Bachelor in Business Administration (GBBA), Exchange semester 2025).

▶ Read all articles by Tibor HAUER.

My professional experience as an intern at Bowery Properties, private real estate investment firm

December 21, 2025 by Noa AZRIA

In this article, Noa AZRIA (ESSEC Business School, Master in Finance (MiF), 2025–2026) shares her professional experience as an intern at Bowery Properties.

About the company

Bowery Properties is a Miami-based multifamily investment and real estate firm active across Florida. The firm invests in and manages residential and commercial properties and has completed several notable acquisitions in South Florida, especially in the multifamily segment. Its focus on value-add assets – properties that can be improved through renovations and better management – created an ideal environment for me to understand how value is created in real estate private equity, both on paper and on the ground. In recent years, for example, Bowery has bought Buena Vista Gardens, an 89-unit portfolio in Miami’s Little Haiti, and Windward Vista Apartments, a 352-unit complex in Lauderhill acquired for 44.1 million dollars.

Logo of Bowery Properties.

Source: the company.

My internship

I joined the Acquisitions team in Miami and reported directly to the Vice President. From day one, I was involved in real transactions rather than just observing. My missions included analysing new investment opportunities, working on Excel models, preparing market studies and supporting my manager during calls.

During the internship, I realized how demanding and stimulating this role is. It requires analytical skills to underwrite deals and assess risk–return, but also communication and negotiation abilities to present new projects in an environment where all stakeholders are closely interconnected, from brokers and investors to banks.

My missions

One of the key missions of my internship was my involvement in the acquisition of Sunset Apartments, a 130-unit multifamily property valued at approximately $28.5 million. I had the opportunity to follow the transaction from the underwriting phase and contribute directly to the investment analysis, which gave me a comprehensive view of the acquisition process. The investment thesis was based on a value-add strategy, meaning that the asset had improvement potential that could be unlocked through renovations and more active asset management. The objective was to increase rents, attract better-quality tenants, reduce vacancy, and ultimately enhance the exit value of the property. My role focused mainly on financial modelling. I worked on the Excel model by integrating Capex per unit, building a phased renovation plan over one to two years, and modelling rent increases as units were renovated and tenants turned over. This allowed me to understand how Capex assumptions and rental growth directly impact key return metrics such as the internal rate of return (IRR), which measures the annualized return generated by the investment based on its future cash flows and exit value.

To support these assumptions, I also prepared a comprehensive market study. This involved identifying comparable multifamily properties in the same area, collecting data on rents, amenities, and occupancy rates, and benchmarking them against Sunset Apartments. This analysis was included in the investment package sent to banks and investors and therefore required a high level of rigor, accuracy, and clarity, as the work was subject to external scrutiny.

Beyond analytical work, my missions also included on-site asset analysis. I regularly accompanied the Vice President on property tours for both multifamily and retail assets. One particularly significant visit was to Parc Place, a large shopping center valued at approximately $71 million. During these visits, I contributed to the qualitative and operational assessment of assets, focusing on accessibility, visibility, parking, tenant mix, vacancy levels, and operational signals observed on site.

Finally, I was exposed to the structuring of transactions with banks and investors. I attended numerous calls with brokers, banks, and investors. Discussions with banks mainly revolved around debt terms such as loan-to-value ratios, interest rate structures (fixed or variable), amortization profiles, and covenants including debt service coverage ratio (DSCR) and minimum occupancy requirements. With investors, I worked on models presenting different capital structure options, ranging from simple profit-sharing arrangements to more complex waterfalls with preferred returns and thresholds. These missions gave me a concrete understanding of how real estate transactions are structured and how risk and return are allocated in private equity.

Required skills and knowledge

This internship required a strong ability to adapt and learn quickly. At the beginning, I mainly worked on clearly defined tasks such as updating financial models, collecting market data, and formatting analytical documents. These missions required rigor, attention to detail, and a solid understanding of basic financial concepts.

As my responsibilities increased, the role demanded greater autonomy, analytical thinking, and organizational skills. I was required to conduct full market studies, build acquisition analyses from scratch, and manage tasks with a higher level of responsibility. Being able to structure analyses, prioritize information, and deliver accurate work under time constraints was essential in this environment.

What I learned

From this experience at Bowery Properties, I developed and strengthened several skills.

On the technical side, I improved my financial analysis of real estate assets (net operating income (NOI), capital expenditures (Capex), rent roll, internal rate of return (IRR), equity multiple), my ability to conduct market studies based on comparable assets and local fundamentals, and my understanding of debt financing (loan to value (LTV), debt service coverage ratio (DSCR), interest structures) and equity structuring (straight splits, waterfalls with hurdles).

On the personal and professional side, I gained autonomy and a sense of responsibility. I also strengthened my rigour and attention to detail, knowing that a simple mistake in an assumption can change the conclusion of a deal. Finally, I progressed in stress management, communication (knowing when and how to speak up with an idea or a concern) and confidence in my own judgement when I had analyzed a file in depth.

Financial and business concepts related to my internship

I present below three financial and business concepts related to my internship: investment horizon, qualitative analysis through on-site due diligence, and the importance of qualitative relationships with stakeholders.

Investment horizon

A fundamental concept in real estate private equity is the investment horizon. Unlike liquid financial assets, real estate investments are illiquid and require a medium- to long-term holding period to fully realize value. During my internship, acquisition decisions were systematically assessed with a clear investment horizon in mind, particularly for value-add strategies where renovations, tenant turnover, and operational improvements take time to materialize. Understanding this concept was essential to align Capex plans, cash-flow projections, and exit assumptions with a realistic holding period.

Qualitative analysis through on-site due diligence

Another key concept I learned was the role of on-site due diligence in real estate investment decisions. Through property tours and site visits, I understood that visiting an asset is not only a formality, but a critical step to assess risks and opportunities that cannot be fully captured in financial models.

On-site analysis allowed us to evaluate concrete elements such as the physical condition of the property, tenant behavior, maintenance issues, accessibility, visibility, and the overall environment. These observations were essential to validate renovation budgets, leasing assumptions, and the feasibility of the value-add strategy. This experience showed me that on-site due diligence plays a central role in confirming the realism of the business plan and reducing execution risk before acquisition.

Importance of qualitative relationships with stakeholders

Finally, my internship emphasized the importance of qualitative relationships with key stakeholders in real estate private equity. Beyond technical analysis, deal execution relies heavily on trust-based relationships with brokers, banks, investors, and operating partners. I observed that effective communication, credibility, and long-term relationships facilitate access to deals, improve negotiation dynamics, and enhance the efficiency of the investment process. This concept showed me that, even in a highly analytical field, human relationships remain a central component of successful investment strategies.

Why should I be interested in this post?

This post may be particularly useful if you are considering a career in real estate private equity or real estate investment and you want to know what an acquisition role really looks like beyond the job description. It can also help you understand how multifamily and commercial deals are analyzed and structured in practice, and how an internship can clarify your career project by exposing you to real decisions and real transactions.

By sharing this experience, my goal is to offer a concrete and honest picture of what it means to work in real estate private equity at an early stage in your career: the analytical dimension, the fieldwork, the pressure, but also the learning curve and the satisfaction you feel when your work contributes directly to a deal.

About the author

The article was written in December 2025 by Noa AZRIA (ESSEC Business School, Master in Finance, 2025-2026).

▶ Read all articles by Noa AZRIA.

DCF vs. Multiples: Why Different Valuation Methods Lead to Different Results

December 20, 2025 by Cornelius HEINTZE

In this article, Cornelius HEINTZE (ESSEC Business School, Global Bachelor in Business Administration (GBBA) – Exchange Student, 2025) explains how the usage of different valuation methods can lead to different outcomes and how to use them.

Why this is important

In finance valuation is always present and it is not only a mechanical exercise. Analysts are working with discounted cash flow models, multiples or other procedures to value a company. Using these different methods will lead to different outcomes and it is crucial to understand why these differences occur and if this is in line with your expectations or differing from them. This helps to avoid misleading conclusions and relying only on a single method or having difficulties interpreting multiple methods.

The DCF model: measuring intrinsic value

The discounted cash flow (DCF) model aims to measure the intrinsic value of a company. It does this by forecasting the expected future cash flows generated by the company and discounting them back to the present using an appropriate discount rate that reflects the risk specific for the company. The goal is to estimate the equity value of the company. The discount rate is often the WACC (weighted-average cost of capital), or the cost of equity based on the method you are using. The method can either be to estimate the enterprise value which would represent the value of the whole company including its assets and its liabilities. For this method you would use the WACC. To get to the equity value directly you have to subtract the part of the liabilites that contribute to the cash flows and create cash flows that are only generated by equity. You will also have to find out the cost of equity, which can be done using the CAPM. After doing this you will have the equity value of the company.

DCF logic (simplified):

Explicit forecast period: Forecast cash flows CF_t for years t = 1 … T and discount them at rate r.
Terminal value: Estimate the value beyond year T using a stable long-term assumption. This is referred to as an annual perpetuity and can include a growth factor if it aligns with the assumptions about the company.

Formula (illustrative):

Value = Σ_t=1…T CF_t / (1 + r)^t + Terminal Value / (1 + r)^T

This formula can differ based on which type of DCF model you are using. If you are using the WACC to discount your cashflows you will be left with the enterprise value of the company’s total assets and liabilities and not the equity value. To get to the equity value, you will have to subtract the liabilities.

Equity value using WACC = (Σ_t=1…T CF_t / (1 + WACC)^t + Terminal Value / (1 + r)^T) – Liabilities

If you are using the cash flows that can be assigned to the equity of the company and the cost of equity to discount these cash flows you will automatically end up with the equity value.

Equity value = Σ_t=1…T CF_{t_equity} / (1 + r_equity)^t + Terminal Value / (1 + r)^T

Strengths of the DCF

You can already see that there are differences within one single model that need to be understood. In practice the method for the total company value is widely used. This is because of its fundamental strength, which is its simplicity and its convenience. It is very easy to follow and you can see how different assumptions will affect the firm value in different ways. It therefore forces the analyst to evaluate and model the key drivers of financial growth. Like looking at the growth rate, investments in working capital and the risk the company is currently facing. As a result, DCF valuations are often used for long-term strategic decisions, mergers and acquisitions, and fairness opinions.

Weaknesses of the DCF

Following this the major problems with the DCF-models are its assumptions. They are based on historical values and the CAPM, which both give no valuable outlook on the future. But as there is no better method currently to predict future cash flows, the method is holding strong in practice, although empirically it seems to be unsuitable. The resulting model is also very sensitive to the assumptions made. Especially looking at the growth rate or the discount rate which will accumulate over time.

Multiples valuation: estimating relative value

Now coming to the multiples-based valuation, this valuation method focuses on looking at the relative value of a company rather than the intrinsic value of a company. This means that the firm is compared to similar companies using different key values such as:

Price-to-Earnings (P/E)
Enterprise Value to EBITDA (EV/EBITDA)
Enterprise Value to Sales (EV/Sales)

The process of choosing and working with multiples is simple. There are two main approaches: the similar public company-method, which is used to create and compare multiples based on data from a company that is publicly traded on a stock market. The second method is the recent acquisition-method, which will look at the transaction prices for a similar company. As the name of the first method indicates, the chosen companies must be similar to the valued company. You can achieve this by looking at the size of the company, the industry and the location or other features and specifying different values for these aspects (i.e. number of employees, pharmacy, Germany).

Implicit assumptions behind multiples

Although multiples are often perceived as simpler ways of valuing a company, they embed the same fundamental assumptions as a DCF model, albeit in a less transparent way.

A valuation multiple implicitly reflects:

Expected growth
Risk and discount rates
Capital structure
Profitability and reinvestment needs

For example, a high EV/EBITDA multiple usually signals that the market expects strong future growth or low risk. In other words, the market has already performed a form of discounted cash flow analysis — but the assumptions are hidden inside the multiple.

Strengths of multiples

Multiples are an easy way to get an overview of the value of a company and compare the estimated values to other companies on the market. They can also be used to quickly check the plausibility of a firm value estimated with the DCF model. The main strength is again its simplicity but this time in a much faster and easier way. They are used to compare the company to competitors and to give insights on how the company would perform against them and on the stock market. It’s also very helpful when valuing smaller companies because they might not have the amount of historical data organized and needed to value this with a DCF method.

Weaknesses of multiples

One of the biggest weaknesses is the requirement of finding a similar company that is traded on the stock market, or which information is publicly available. They therefore can also be manipulated easily because they are less transparent than other methods and can be adjusted very easily (what is “similar”?). They also cannot be seen as objective values as the market is estimating them with no individual interferences. Therefore, they are not consistent and have to be used with care. You should always make plausible assumptions, that can be explained by the multiple and the current situation of the company.

When to use them and the “football field”

To really get behind the use of multiples and the DCF model all together we are looking how to combine them together in a meaningful way. Multiples are often used to create a “football field”. This technique describes a graph that is summarizing valuation ranges across methods rather than delivering a single point estimate. This is especially helpful when you are currently negotiating on an M&A deal to see if the offered prices are aligned with your assumptions and whether you want to accept or not.

A great example for the combination of the DCF model and multiples is the acquisition from Actelion by Johnson & Johnson. To see if the offer was acceptable and fair, they hired valuation professionals from Alantra. Alantra gathered data and estimated multiple values to compare the offer. They used the graph of the “football field” to make it visually appealing and instinctive. You can see that the green line is far right beyond the red line and therefore it can be seen as a fair offer considering the other values that have been estimated by Alantra in their fairness opinion for Actelion. This is because the more the value is on the right side of the graph, the higher it is.

Alantra Fairness Opinion example

You can download the full fairness opinion here

DCF vs. Multiples Example

You can download the Excel file provided below, which contains the “Football field” example.

You can see here that the estimated value from the DCF is a more on the lower end than the consensus of the market. This is not necessarily a problem as the market might have already considered synergies or future events that the DCF model did not capture or simply is not expecting, due to a lack of information (insiders etc.).

As you can see, rather than choosing between DCF and multiples, practitioners usually apply both approaches in a complementary way:

DCF models are well suited for estimating intrinsic value and analyzing long-term fundamentals.
Multiples are useful for understanding how the market currently prices similar firms.
In IPOs and M&A transactions, both methods are typically combined to form a valuation range.

A robust valuation rarely relies on a single number. Instead, it emerges from comparing and reconciling different approaches.

Conclusion

DCF and multiples-based valuation often lead to different results because they answer different questions. DCF models aim to estimate intrinsic value based on explicit assumptions, while multiples reflect relative value and prevailing market expectations.

Recognizing the strengths and limitations of each method is essential for sound financial analysis. By combining both approaches and critically assessing their underlying assumptions, analysts can arrive at more balanced and informative valuation outcomes.

To sum up…

Both DCF and multiples are useful tools, but neither should be applied mechanically. A solid valuation comes from understanding what each method captures, where it can mislead, and how results change when assumptions or peer groups change. In practice, triangulating across methods provides the most reliable foundation for decision-making.

Why should I be interested in this post?

For a student interested in business and finance, this post provides a concrete bridge between theory and practice. Valuation models such as the two-stage DCF are not only central to courses in corporate finance, but also widely used in internships, case interviews, and real-world transactions. Understanding how sensitive firm values are to assumptions on growth and discount rates helps students critically assess valuation outputs rather than taking them at face value, and prepares them for practical applications in consulting, investment banking, or asset management.

Useful resources

Paul Pignataro (2022) Financial modeling and valuation: a practical guide to investment banking and private equity Wiley, second edition.

Aswath Damodaran (2015)Explanations on Multiples

About the author

The article was written in December 2025 by Cornelius HEINTZE (ESSEC Business School, Global Bachelor in Business Administration (GBBA) – Exchange Student, 2025).

▶ Read all articles by Cornelius HEINTZE .

Risk-based Audit : From Risks to Assertions to Audit Procedures

December 20, 2025 by Iris ORHAND

In this article, Iris ORHAND (ESSEC Business School, Global Bachelor in Business Administration (GBBA), 2021-2026) shares a technical article about risk-based audit.

Introduction

Financial statements are not audited by “checking everything”. In practice, auditors use a risk-based approach: they identify what could materially go wrong, link those risks to specific financial statement assertions, and then design the right audit procedures to obtain sufficient and appropriate evidence. “Materially” means that an error or omission is significant enough to influence the decisions of users of the financial statements, meaning it has a real impact on how the financial information is interpreted.

This article explains a simple but powerful framework widely used in audit: Risks→Assertions→Procedures. It’s the logic I applied during my experience in financial audit at EY, where this methodology helps teams prioritize work, structure fieldwork, and produce clear conclusions.

The audit risk model: why “risk-based” makes sense

At a high level, auditors aim to reduce the risk of issuing an inappropriate opinion. A classic way to express this is:

Audit Risk (AR) = Inherent Risk (IR) × Control Risk (CR) × Detection Risk (DR)

Inherent risk (IR): the risk a material misstatement exists before considering controls (complexity, estimates, judgment, volatile business, etc.).
Control risk (CR): the risk that internal controls fail to prevent or detect a misstatement.
Detection risk (DR): the risk that audit procedures fail to detect a misstatement that exists.

In practice, when IR and/or CR are high, auditors respond by lowering DR through stronger procedures: more evidence, better targeting, larger samples, more reliable sources, and more experienced review.

Materiality: focusing on what matters

Because financial statement users care about decisions, audit planning relies on materiality (and performance materiality) to size the work. Materiality helps answer:

What could influence users’ decisions?
Which line items/disclosures require deeper work?
What magnitude of error becomes unacceptable?

This is also why “risk-based” is essential: the audit effort is scaled to what is material and risky, not what is merely easy to test.

Assertions: translating accounting lines into “what could be wrong”

Assertions are management’s implicit claims behind each number. Auditors use them to define the nature of possible misstatements. The most common are:

Existence / Occurrence: the asset/revenue is real and actually happened
Completeness: nothing important is missing
Rights & obligations: the entity truly owns/owes it
Valuation / Accuracy: amounts are measured correctly (estimates, provisions…)
Cut-off: recorded in the correct period
Presentation & disclosure: correctly described and disclosed

This is a key step: a “risk” becomes actionable only when you connect it to one (or several) assertions.

From risk to procedures: the core workflow

A practical “risk-based audit” workflow looks like this:

Firstly : Identify significant risks (business model, incentives, complexity, unusual transactions, estimates, prior year issues).
Secondly : Map each risk to assertions (e.g. : revenue fraud risk → occurrence, cut-off).
Thirdly : Choose the response: 1) Tests of controls (TOC) if relying on internal controls; 2) Substantive tests (analytical procedures + tests of details)
Finally : Execute, document, conclude: evidence must be sufficient, appropriate, and consistent.

Concrete examples: what we do in practice

Example 1: Revenue recognition

Typical risks : overstated revenue, early recognition, fictitious sales, side agreements. Key assertions : occurrence, cut-off, accuracy, presentation.

Common procedures:

Analytical review (trends, margins, monthly patterns) to spot anomalies
Cut-off testing around year-end (invoices, delivery notes, contracts)
Tests of details on samples (supporting documents, customer confirmations when relevant)
Review of revenue recognition policy and contract terms (IFRS 15 logic, performance obligations)

Example 2: Inventory (valuation and existence)

Typical risks : obsolete stock, wrong costing, missing inventory, poor count controls. Key assertions : existence, valuation, completeness, rights.

Common procedures:

Attendance/observation of physical inventory count
Reconciliation count-to-ERP, and ERP-to-FS
Price testing, cost build-up testing, NRV/obsolescence analysis
Movement testing and cut-off around receiving/shipping

Example 3: Provisions & estimates (judgment-heavy)

Provisions and estimates refer to amounts recorded in the accounts for obligations or future events that are uncertain but likely enough to require recognition, which means management must use judgment to estimate their value based on the best information available.

Typical risks : management bias, under/over provisioning, inconsistent assumptions. Key assertions: valuation, completeness, presentation.

Common procedures:

Understanding process + key assumptions and governance
Back-testing prior-year estimates vs actual outcomes
Sensitivity analysis on assumptions (rates, volumes, timelines)
Lawyer letters / review of claims, contracts, contingencies

Conclusion

Risk-based audit is more than a buzzword: it’s the method that turns financial statement complexity into a structured plan. By linking risks to specific assertions, auditors can design procedures that are both efficient and defensible, especially under time pressure and tight deadlines.

Why should I be interested in this post?

If you are interested in audit, accounting, corporate finance, or risk, understanding the risk-based approach is foundational. It explains how auditors prioritize, how they challenge information, and why audit work is ultimately about building confidence in financial reporting through evidence.

Useful resources

Site economie.gouv Méthodologie de conduite d’une mission d’audit interne

Site L-expert-comptable.com (25/02/2025) La méthodologie d’audit : Les assertions

Corcentric Les étapes clefs d’un processus d’audit comptable et financier

Cabinet Narquin & Associés Les méthodes d’audit utilisées par les commissaires aux comptes

About the author

The article was written in December 2025 by Iris ORHAND (ESSEC Business School, Global Bachelor in Business Administration (GBBA), 2021-2026).

▶ Read all articles by Iris ORHAND

My internship experience in Investor Relation at Eurazeo

December 19, 2025 by Adam MERALLI BALLOU

In this article, Adam MERALLI BALLOU (ESSEC Business School, Global Bachelor in Business Administration (GBBA), 2021-2026) shares his professional experience as Investor Relations at Eurazeo.

About the company

Eurazeo is one of the leading European investment groups specialized in private markets. Listed on Euronext Paris, the group has a market capitalization of approximately €3.62 billion. As of 2024–2025, Eurazeo manages around €37 billion in assets under management, investing on behalf of institutional investors, sovereign wealth funds, pension funds, insurers, family offices and high-net-worth individuals. Eurazeo supports a portfolio of more than 600 companies and relies on a team of over 400 investment professionals across Europe, North America and Asia.

The group operates a highly diversified private markets platform, covering a broad range of non-listed strategies. These include buyout funds, growth equity, venture capital, secondary funds, as well as private debt, infrastructure debt and real estate. Through these strategies, Eurazeo supports a wide range of companies, for example Aroma-Zone, Ozone and Eres in buyout; Vestiaire Collective and Doctolib in growth equity; and Deezer, Swile and JobTeaser in venture capital. This diversification allows Eurazeo to address different investor objectives, risk-return profiles and investment horizons across the private markets universe.

Logo of Eurazeo

Source: Eurazeo

My internship

I worked within the Investor Relations / Product Specialist team. This team plays a central role between the sales teams, whose responsibility is to maintain relationships with Limited Partners (LPs) and lead fundraising discussions, and the investment teams, which focus on sourcing, executing and managing investments.

The Product Specialist team acts as a bridge between these two functions. Its role is to translate investment strategies, portfolio construction, performance and market insights into clear, accurate and investor-ready materials. This positioning requires constant coordination with multiple internal teams to ensure consistency between what is communicated to investors and what is implemented by investment teams.

My missions

My missions were primarily centered on fundraising support and investor due diligence processes. I collaborated closely with all internal teams to respond as quickly and efficiently as possible to LPs’ Requests for Proposals (RFPs) and due diligence questionnaires. This involved collecting information from investment teams, coordinating with legal and compliance teams, and consolidating responses to meet institutional investors’ requirements. I was also responsible for managing and updating several fundraising data rooms using Intralinks. This included organizing documentation, ensuring version control, maintaining up-to-date information and supporting transparency throughout the fundraising process, which is essential for investor confidence.

In parallel, I contributed to the production of high-quality marketing materials such as fund presentations, teasers and fundraising documents. Producing these materials required a deep understanding of each fund’s investment thesis, portfolio composition, value creation strategy and track record, as well as the ability to present complex information in a clear and compelling way for institutional investors.

Finally, I conducted a competitive analysis of the European Private Equity, Private Debt and Real Assets markets. This analysis focused on peer fund strategies, fundraising trends, market positioning and competitive dynamics, and was used to support the sales and product teams in positioning Eurazeo’s funds relative to other major European players.

Required skills and knowledge

This internship required a strong combination of technical, analytical and interpersonal skills. From a technical perspective, a solid understanding of financial markets was essential, particularly across equities and fixed income. Beyond theoretical knowledge, closely following financial markets on a day-to-day basis was a key part of the role, in order to understand market movements, macroeconomic developments and their impact on asset prices.

I needed to be comfortable with portfolio management principles such as asset allocation, diversification, benchmarking and active management in order to contribute effectively to investment proposals and portfolio monitoring.

Proficiency in financial tools was also critical. I regularly used Bloomberg and FactSet to access market data, analyze securities, monitor portfolios and support performance and benchmark analysis. These platforms were essential for understanding market dynamics, tracking asset allocation and assessing portfolio positioning across different asset classes. Advanced Excel skills were used to consolidate data, build allocation summaries, perform basic performance calculations and prepare clear and accurate reports for internal use and client-facing deliverables, ensuring consistency and reliability across analyses.

Beyond technical skills, soft skills played a central role in my day-to-day work. Given the level of autonomy involved in preparing investment proposals for new clients, rigor, attention to detail and strong organizational skills were essential. Clear communication was also key, as I interacted frequently with private bankers, portfolio managers, middle office and management teams. This required the ability to translate complex financial analysis into clear and actionable insights adapted to different stakeholders. This internship required a solid understanding of private markets and institutional fundraising mechanisms. Knowledge of private equity, private debt, infrastructure and real assets was essential to accurately understand investment strategies and respond to investor inquiries.

Strong analytical skills were necessary to conduct competitive market analyses and synthesize complex information into concise and relevant messaging. Writing and presentation skills were also critical, given the importance of producing investor-facing materials that meet high professional standards.

In addition, the role required strong organizational skills, attention to detail and the ability to work under time pressure, particularly during active fundraising phases. Soft skills such as communication, responsiveness and adaptability were essential, as the role involved constant interaction with sales, investment, legal and management teams.

What I learned

This experience provided me with a deep understanding of how private market fundraising operates within a large European investment platform. I learned how institutional investors evaluate funds, what they expect during due diligence processes and how investment strategies are assessed beyond pure financial performance.

Working at the interface between sales and investment teams highlighted the importance of internal coordination and message consistency in fundraising success. I gained insight into how investment strategies and track records are translated into investor-ready narratives, and how responsiveness and data quality play a critical role in building long-term LP relationships.

Overall, this internship strengthened my interest in private markets, investor relations and investment products, and complemented my previous experience in portfolio management by providing a broader perspective on the asset management value chain.

Financial and business concepts related to my internship

I present below three financial and business concepts related to my internship: private market fundraising and LP relations, product positioning and information asymmetry in private markets, and competitive dynamics in European private markets.

Private market fundraising and LP relations

Fundraising in private markets relies on long-term relationships between General Partners (GPs) and Limited Partners (LPs). Institutional investors conduct extensive due diligence before committing capital, assessing governance, risk management, team stability, operational infrastructure and alignment of interests.

My involvement in RFPs and due diligence processes illustrated how transparency, consistency and responsiveness are essential to maintaining investor trust. The Investor Relations and Product Specialist function plays a key role in reducing information gaps and ensuring that investors receive accurate and timely information throughout the fundraising process.

Product positioning and information asymmetry in private markets

Private market funds are characterized by a high degree of information asymmetry, as investment strategies, portfolio composition and value creation processes are not publicly observable. Effective product positioning is therefore crucial to help investors understand how a fund fits within their broader portfolio.

Through the preparation of fund presentations and marketing materials, I learned how complex investment strategies are translated into structured narratives supported by data and track records. Clear positioning helps differentiate funds in a competitive environment and facilitates investor decision-making.

Competitive dynamics in European private markets

European private markets have become increasingly competitive, with a growing number of fund managers competing for institutional capital. Differences in fund size, sector focus, geographic exposure and investment style play a major role in investor allocation decisions. The competitive analyses I conducted highlighted how Eurazeo positions its strategies relative to peers across private equity, private debt and real assets. Understanding these dynamics is essential for adapting fundraising strategies and maintaining competitiveness in evolving market conditions.

Why should I be interested in this post?

This experience offers valuable insight into the fundraising and investor relations side of private markets, which is often less visible than the investment process itself. For students interested in private equity, private debt or alternative investments, this role provides a unique perspective on how funds are raised, how investors evaluate strategies and how investment products are positioned in competitive institutional markets.

Useful resources

Eurazeo Official website

Eurazeo (2025) White Paper on why Investing in Europe

Invest Europe

About the author

The article was written in December 2025 by Adam MERALLI BALLOU (ESSEC Business School, Global Bachelor in Business Administration (GBBA), 2021-2026).

▶ Read all articles by Adam MERALLI BALLOU.

How networking helped me land a Transaction Services internship in Paris

December 18, 2025 by Daniel LEE

In this article, Daniel LEE (ESSEC Business School, Global Bachelor in Business Administration (GBBA) – 2023-2027) explains how to network to land internships.

Introduction

Finance is a highly competitive industry, whether it is investment banking, private equity or consulting roles. In 2025, Goldman Sachs’ summer internship acceptance rate was 0.7%. Candidates must stand out with prior internships, extracurricular activities or a referral. According to Dustmann et al. (2016), around 33% of workers obtained their jobs through personal networks, such as referrals from friends or family.

During my own internship search, networking played a decisive role, as it helped me secure a Transaction Services (TS) internship in Paris in a small boutique that also have other activities like audit and M&A. Over the past two years, I’ve contacted over 250 professionals, which led to 50+ coffee chats and four interview opportunities and 1 offer. If I had this offer, it is not because I had the strongest CV or the best grades. I was referred to by a senior because I networked with him and built a genuine relationship. Networking was not something I was born good at, I learned step by step.

In this article, I will share my vision of networking, even if I am not an expert, I simply want to give tips that worked for me and that you guys could use.

Why is networking important in finance?

In finance, analysts are close to each other. Often you will spend a lot of hours working on materials late at night. Being able to chat and laugh is important to keep a good atmosphere at work. Imagine working insane hours with someone who is grumpy, boring and unreliable. That is why your human side is more important than you think. Moreover, if someone who is trusted in the company refers to you during a hiring process, the firm will make sure to interview you. Yet, many students don’t dare to reach out to professionals.

What are the common mistakes?

Networking must not feel transactional. The person must be the one who is asking if you want an internship, not the contrary. Sending a message “Hi can you refer me for this role?” or just a generic application mail with your CV will make the person feel “used”. Sending a message that is personal and genuine will be much more appreciated.

On the other hand, I think that targeting analysts or associates is the best strategy. You will be around the same age, and they will have tips and information that are up to date. Moreover, seniors often don’t have time, but you can still try to contact them!

The method.

Obviously, the first step is to choose which field you want to break in: Mergers & Acquisitions (M&A), Private equity (PE), Asset Management (AM), etc. Then:

Use LinkedIn and your Alumni directory (using ESSEC alumnis increased 40% of my response rate compared to non-ESSEC professionals) to identify people you want to contact.
Send a short message that is simple and arrange a call. For example: Hi [Name], I’m a student at ESSEC currently exploring opportunities in Transaction Services. I saw that you are currently working at [firm] and I would love to learn more about your experience. Would you have 10–15 minutes for a quick call this week? I’d really appreciate your insights.
Prepare for the coffee chat: look at his LinkedIn profile, prepare some questions and smile! Being nice and kind is the bare minimum! The coffee chat is not an interview but a discussion, follow-up on what he says and be genuinely interested in the person and what he says. At the end of the discussion, always thank the person for their valuable time.
Never ask for a referral directly! If the conversation goes well two things can happen: 1) At the end of the call, he asks you directly if you are looking for an internship OR; 2) You can kindly ask if they are recruiting anyone now.

If they don’t mention anything about sending your CV or contacting another person, you can consider that the person won’t give you a referral. And that’s okay! You can still try with another person.

Conclusion

You now have an idea of how to network properly. Again, I am not an expert, and I do not claim that this method will work 100% but that is what I used to do for the past 2 years, and it worked well. Don’t forget that networking is a skill that you can learn, don’t be discouraged if the first calls are bad, that’s totally normal!

Useful resources

Dustmann, C., Glitz, A., Schönberg, U. & Brücker, H. (2016) Referral-based job search networks. The Review of Economic Studies, 83 (2) 514–546.

FoxBusiness (27/06/2025) Goldman Sachs’ Summer Internship Acceptance Rate

Scott Keller (24/11/2017) Attracting and retaining the right talent McKinsey.

About the author

In this article, Daniel LEE (ESSEC Business School, Global Bachelor in Business Administration (GBBA) – 2023-2027).

▶ Read all articles by Daniel LEE.

My internship experience in Portfolio Management at Mirabaud

December 19, 2025December 18, 2025 by Adam MERALLI BALLOU

In this article, Adam MERALLI BALLOU (ESSEC Business School, Global Bachelor in Business Administration (GBBA), 2021-2026) shares his professional experience as Portfolio Management at Mirabaud.

About the company

Founded in 1819, Mirabaud is an independent international banking group with strong Swiss roots and a long-standing presence in Europe. The group operates across private banking, asset management and investment services, serving private clients, families, entrepreneurs and institutional investors, and manages CHF 32.4 billion in assets under management. Mirabaud is recognized for its long-term investment philosophy, disciplined risk management and strong focus on capital preservation.

With offices in major financial centers such as Geneva, Zurich, Paris, London, Luxembourg and Madrid and more than 700 employees worldwide, Mirabaud combines local expertise with a global investment perspective. The group offers a wide range of investment solutions, including discretionary and advisory portfolio management, structured products, alternative investments and private market solutions, enabling clients to access diversified sources of return across market cycles.

Logo of Mirabaud

Source: Mirabaud

My internship

I joined Mirabaud in July 2024 as a Portfolio Management Analyst and remained in the team until January 2025. My role consisted in supporting portfolio managers in the construction, monitoring and analysis of client portfolios within a multi-asset framework. This included traditional asset classes such as equities and bonds, as well as exposure to alternative assets, including private equity through dedicated investment vehicles and funds. Working at the interface between portfolio management and private banking provided a comprehensive view of how investment decisions are translated into concrete client portfolios. I was exposed both to strategic asset allocation decisions and to more tactical adjustments driven by market dynamics, interest rate environments and client-specific constraints.

My missions

My missions covered a broad range of responsibilities within a multi-asset portfolio management framework. I was in charge to draft investment proposals for all new clients. These proposals were designed to reflect each client’s financial objectives, risk tolerance and specific investment preferences. The construction of these portfolios required the careful selection of appropriate underlying instruments, including investment funds and direct securities across equities, fixed income and alternative assets. In this process, I had to simultaneously integrate client-specific requirements, the portfolio managers’ convictions on asset classes and sectors, and the group-level strategic recommendations. This experience highlighted the importance of aligning top-down asset allocation with bottom-up security selection.

In parallel, I was involved in the execution of orders for discretionary and managed mandates, using both internal tools and external platforms such as Bloomberg. This allowed me to gain practical exposure to trade execution processes, market liquidity considerations and operational constraints.

I also contributed to the monitoring of portfolio managers’ strategies, focusing on portfolio performance analysis and deviations from benchmarks. This work helped assess the impact of allocation decisions and active management choices over time.

Finally, my role required close interaction with multiple internal stakeholders. I worked regularly with private bankers, middle office, marketing and management teams to ensure the smooth implementation of investment decisions and to provide both administrative and commercial support. This cross-functional exposure gave me a comprehensive view of how investment solutions are delivered within a private banking organization.

Required skills and knowledge

What I learned

This internship provided me with a comprehensive understanding of how multi-asset portfolio management operates within a private banking environment. I learned how investment strategies are built from both a top-down and bottom-up perspective, combining group-level strategic views, portfolio managers’ convictions and client-specific requirements.

One of the most valuable lessons was understanding how theory translates into real investment decisions. Concepts such as diversification, asset allocation and benchmarking became concrete through the construction and monitoring of client portfolios. I also gained practical exposure to trade execution and operational processes, which highlighted the importance of liquidity, timing and coordination between front and middle office teams.

In addition, working on structured products deepened my understanding of how customized investment solutions can be designed to respond to specific market conditions and client objectives. Overall, this experience strengthened my analytical skills, increased my autonomy and confirmed my interest in asset management, private banking and investment solutions.

Financial concepts related to my internship

I present below three financial concepts related to my internship: asset allocation and diversification in a multi-asset framework, benchmarking and active portfolio management, and structured products in wealth management.

Asset allocation and diversification in a multi-asset framework

Asset allocation refers to the distribution of investments across different asset classes such as equities, bonds and alternative assets, including private equity. In a multi-asset framework, this allocation is the primary driver of portfolio risk and long-term performance. Diversification aims to reduce portfolio volatility by combining assets with different risk, return and correlation characteristics.

During my internship, I observed how strategic asset allocation provides a long-term investment framework, while tactical adjustments allow portfolio managers to adapt to changing market conditions. The construction of investment proposals for new clients clearly illustrated how allocation choices are aligned with investment horizons, risk profiles and return objectives.

Benchmarking and active portfolio management

Benchmarking plays a central role in portfolio management, as it provides a reference framework to assess portfolio performance and risk. By comparing portfolios to appropriate benchmarks, portfolio managers can evaluate the impact of asset allocation and security selection decisions and determine whether performance deviations are driven by active management choices or market movements.

During my internship, I contributed to the monitoring of portfolio managers’ portfolios, focusing in particular on deviations from benchmarks. This analysis helped identify sources of over- or under-performance and assess the consistency of investment strategies over time. It also illustrated the trade-offs involved in active portfolio management, where deviations from benchmarks are necessary to generate alpha but must remain controlled to stay aligned with clients’ risk profiles and investment mandates.

Structured products in wealth management

Structured products are investment instruments that combine traditional securities, such as bonds, with derivatives to create customized risk-return profiles. In wealth management, products such as autocallables and capital-protected notes are used to offer conditional returns, yield enhancement or capital protection depending on market scenarios.

My exposure to these products helped me understand how structured solutions can complement traditional assets within diversified portfolios. Analyzing their payoff structures and underlying assets highlighted both their potential benefits and their risks, emphasizing the importance of suitability analysis and clear communication when integrating them into client portfolios.

Why should I be interested in this post?

This experience illustrates how multi-asset portfolio management operates within a private banking environment and how investment strategies are translated into tailored solutions for clients. For students interested in asset management, private banking or investment solutions, this experience provides valuable exposure to real-world portfolio construction, market analysis and cross-team coordination within a financial institution.

Useful resources

Business

Mirabaud

Bloomberg

Factset

Others

Kahlich, M. and co-authors (2025) Global Wealth Report 2025 BCG.

About the author

The article was written in December 2025 by Adam MERALLI BALLOU (ESSEC Business School, Global Bachelor in Business Administration (GBBA), 2021-2026).

▶ Read all articles by Adam MERALLI BALLOU.

Inside retail banking: My apprenticeship at Crédit Agricole des Savoie

December 17, 2025 by Mathilde JANIK

In this article, Mathilde JANIK (ESSEC Business School, Global Bachelor in Business Administration (GBBA), 2021-2025) shares her experience as a two-year apprentice in the retail banking sector at Crédit Agricole des Savoie.

Introduction

This article is aimed at presenting my apprenticeship as a personal banker within Crédit Agricole regional bank Crédit Agricole des Savoie and what it taught me. This apprenticeship at Crédit Agricole des Savoie represented a pivotal, two-year immersion into the complexities of mutualist retail banking, offering a unique platform to translate academic financial concepts into tangible professional practice. My experience was situated at the dynamic intersection of local development and high-demand client services, specifically within the demanding, fluctuating environment of the French Alpine ski economy. This role not only provided hands-on experience in portfolio management and commercial goal achievement but also served to rigorously develop my adaptability, regulatory compliance expertise, and client advisory capabilities across diverse economic cycles.

About the company

To give a bit more context I’m a fifth-year BBA student at ESSEC Business School , and I have been completing a two-and-a-half-year apprenticeship at Crédit Agricole des Savoie. This bank is an institution that’s been historically the oldest bank in the sector, deeply woven into the economic and social fabric of Savoie and Haute-Savoie departments. France’s largest mutual banking group (54 million clients), CASA operates on principles of proximity, responsibility, and solidarity, channeling its financial results back into local development projects. Established historically in 1894 to support the agricultural sector, the bank has long evolved into a universal bank, serving over half the local population with 716k clients for about 1.3M inhabitants in Savoie and Haute-Savoie, maintaining a leading position in supporting the region’s diverse economic activities, from tourism and industry to agriculture and cross-border workers. Even though those numbers tend to decrease with the surge of neobank and younger generations moving to digital establishments instead, Crédit Agricole still holds an important place in the local economy and people’s financial habits.

Logo Credit Agricole des Savoie.
Logo of Crédit Agricole des Savoie
Source: the company.

My apprenticeship was specifically within the retail network, where I served in two distinct local offices: Bozel and Courchevel. This placement provided a unique immersion into seasonal banking operations. Located in or near major ski resorts, these offices experience immense fluctuations in client volume and needs, adapting rapidly from high-demand winter seasons, catering to seasonal workers, holiday-home owners, and tourists, to the quieter periods of the off-season. This required a constant re-evaluation of customer relationship management (CRM) strategies and a heightened ability to handle diverse financial situations across different client segments (local residents, high-net-worth individuals, and professional clients tied to the tourism industry).

My apprenticeship

My tasks each day were dependent on the projects I was assigned to and the portfolio I was taking care of. Initially, my mission focused on establishing a solid operational foundation. I managed all routine banking operations and provided first-level customer assistance, responding to the daily needs of account holders. At the same time, a significant portion of my time was dedicated to ensuring the regulatory security of the branch portfolio, including performing KYC (Know Your Customer) updates across four portfolios, encompassing approximately 1,600 clients. This phase allowed me to master compliance imperatives and develop an initial commercial approach through targeted outbound calls, aiming at client prospecting and scheduling appointments to transform routine service interactions into business opportunities.

Afterwards, my responsibilities evolved toward the structured support of client projects. I conducted detailed credit analysis for financing consumer projects and home ownership (real estate loans). This expertise was complemented by accelerated skill development in the insurance sector: following specialized training, I obtained the necessary certification to market and advise on property and personal insurance. Every client interaction required a rigorous analysis and evaluation of risks inherent to the retail clientele, thereby ensuring the financial viability of proposed solutions while protecting the bank’s interests. I took full ownership of the entire advisory cycle, from the preparation to the actual execution of client appointments.

Finally, the experience led to access to more complex financial engineering missions. I actively participated in financial investment advisory, assisting clients, from general public profiles to the so-called high-net-worth clientele, in optimizing their savings. The most enriching dimension was the wealth advisory and asset analysis conducted in tandem with the sector’s dedicated wealth manager. This collaboration exposed me to strategies for tax and inheritance optimization, as well as the selection of sophisticated placements, confirming my ability to mobilize cross-functional knowledge to propose tailored, high-value-added solutions.

Financial concepts related to my internship

I would like to focus on three financial concepts I learnt during my apprenticeship: credit risk analysis, regulatory compliance and financial product suitability, and portfolio segmentation.

Credit risk analysis

The first one is the retail credit risk analysis, the systematic analysis is foundational to a banker’s role, ensuring long-term solvency of the portfolio. My task of analyzing both consumer and real estate loan applications required applying a 5Cs framework (Character, Capacity, Capital, Collateral and Conditions) specifically tailored for retail customers. It goes beyond calculating simple debt ratios; it involves a qualitative assessment of the client’s financial stability such as employment history, savings behavior and the project’s feasibility. This direct exposure to the underwriting process provided practical knowledge on mitigating default risk and managing the bank’s capital adequacy requirements at the individual level.

Regulatory compliance and financial product suitability

The second concept is regulatory compliance and financial product suitability with MiFID regulation and AMF directives. My role, particularly in investment advisory and insurance sales (supported by my new certification; the AMF Certification), centered entirely on the concept of suitability. This mandated thoroughly assessing the client’s risk tolerance, financial knowledge, investment horizon, and objectives to ensure that any product recommendation, whether a life insurance contact (“assurance vie” in French) or a specific investment fund was appropriate, ethically sound, and legally compliant. This principle forms the bedrock of customer protection in modern finance.

Portfolio segmentation

The third concept was portfolio segmentation. In fact, managing a portfolio of 300 clients across diverse profiles necessitated a disciplined approach to client portfolio segmentation. This concept involves classifying clients (e.g., mass market, affluent, high-net-worth) based on their assets under management, complexity of needs, and perceived Client Lifetime Value (CLV). This segmentation guided my commercial strategy: targeting high-potential clients for outbound calls and wealth advisory, while reserving complex financial engineering (done in tandem with the senior advisor) for high-net-worth clients. Segmentation ensures that the branch allocates its limited advisory resources efficiently, maximizing both commercial returns and the depth of client relationship management.

Why should I be interested in this post?

If you are a student aiming for a career in Wealth Management, Private Banking, Portfolio Management, or Asset Management, this post is highly relevant. While many students focus exclusively on capital markets or institutional roles, they often overlook the foundational importance of retail banking as the starting point for true client relationship expertise and core financial risk analysis.

My apprenticeship at Crédit Agricole des Savoie demonstrates how the local branch provides unparalleled, holistic exposure to the core mechanics of a financial institution. You gain hands-on knowledge of credit risk assessment for individuals and SMEs, navigate direct AMF/ACPR regulatory compliance on suitability, and master the art of client relationship management and advisory sales. These are all essential skills for building and managing complex portfolios and high-net-worth relationships, providing a robust, client-centric view of finance that is invaluable in these careers.

Useful resources

Banks

Crédit Agricole des Savoie – Site Officiel

Le Groupe Crédit Agricole

La BNP, la Société Générale, CIC, et le Crédit Mutuel vont déployer des distributeurs d’argent communs

AMF : Certification professionnelle des acteurs de marché

Les métiers de l’accueil clientèle dans le secteur bancaire

Le Crédit Agricole se veut « plus conquérant », plus international et passe à l’offensive en Allemagne

Un euro numérique à l’ère numérique – Banque Centrale Européenne

Responsabilité sociale des banques : enjeux et initiatives

Management methods

Qu’est-ce que la méthode des 5 C ?

Méthode CROC : définition et exemples pour l’entretien téléphonique

About the author

The article was written in December 2025 by Mathilde JANIK (ESSEC Business School, Global Bachelor in Business Administration (GBBA), 2021-2025).

▶ Read all articles by Mathilde JANIK.

My internship experience in a Multi-Family Office

December 17, 2025 by Jules HERNANDEZ

In this article, Jules HERNANDEZ (ESSEC Business School, Global Bachelor in Business Administration (GBBA), 2021-2025) shares his professional experience as Financial Analyst in a Multi-Family Office.

About the company

I worked two years in a Multi-Family Office (MFO) as a Financial Analyst. The purpose of this wealth management firm is to support families and executives across multiple dimensions of their wealth. Their comprehensive wealth management approach offers highly personalized, long-term service focused on objective advice, with a broad scope of expertise spanning legal, tax, financial, and real estate matters.

What is a MFO ?

According to the AFFO (The French Family Association), a Family Office is a advisory structure designed to support one or several families in the management, organization, and long-term preservation of their wealth. Its mission extends across all dimensions of patrimonial oversight and is carried out in close alignment with the family’s objectives, values, and governance framework. Acting solely in the interest of the families it serves, a Family Office adheres strictly to the principles of independence, confidentiality, and full alignment of interests. It typically operates as a multidisciplinary coordinator, bringing together and overseeing the work of various external advisors and partners, including lawyers, notaries, chartered accountants, financial and real estate asset managers, and insurance specialists. The role of a Family Office (FO) or a Multi-Family Office (MFO), who supports several families instead of one, delivering services to each on a strictly individualized and confidential basis, is to cover a broad spectrum of responsibilities, ranging from financial advisory and asset management to wealth strategy and structuring. Where relevant, it also integrates the personal values and convictions of its clients into wealth management decisions. For instance, when a family seeks to invest with an environmentally responsible or impact-driven approach, the Family Office will orient investment choices toward solutions that meet these specific criteria. The financial advisors leading a FO or a MFO must manage their clients’ wealth with a 360-degree vision, as emphasized by Charles-Henri Bujard, President of the AFFO, in his perspective on the Family Office model.

My internship

In January 2024, I joined the team as a financial analyst as part of a two-year work-study program. This experience consisted of two six-month full-time periods at the office, a university exchange, and a period of academic coursework. I worked closely with the Head of Investments on various assignments. Although I was attached to the investment division, I had to fully immerse myself in the firm and understand the role played by each department. The back office, the tax division, and the financial division are highly interconnected and must work hand in hand to ensure efficient and effective wealth management for clients.

My missions

Working in a small structure meant that the tasks were highly varied, and I had the opportunity to take on a wide range of responsibilities. To present this more clearly, let’s divide these tasks into three main categories: Front Office, Middle Office, and Reporting & Sales/Marketing.

Front-Office missions

My front-office responsibilities were multifaceted. The first focused on designing the allocation of our clients’ listed portfolios. This involved identifying the best investment opportunities in public markets, deciding where to invest and selecting the most suitable investment funds in order to capture the highest possible performance. These funds were UCITS available through life insurance contracts. According to the European Fund and Asset Management Association (EFAMA), UCITS (Undertakings for Collective Investment in Transferable Securities) are EU-regulated investment funds designed to protect investors through strict rules on diversification, liquidity and transparency. In simple words, Insurance companies provides a list of EU-regulated investment funds in which a contracted client can invest in. These allocations were reviewed and adjusted regularly, which required carrying out portfolio rebalancing operations (the process of modifying a portfolio’s allocation by divesting from certain holdings and investing in new ones). As part of my role, I was therefore also responsible for executing these rebalancing transactions across clients’ accounts. In addition, in the pursuit of increasingly efficient diversification, I was tasked with conducting due diligence on several ranges of fixed-maturity bond funds with the objective of building a “buy-and-hold” bond strategy for our clients. This due diligence process gave me the opportunity to analyze multiple funds from different asset managers, both from a quantitative and qualitative perspective.

Middle-Office missions

Middle-office responsibilities mainly involved investment continuity management and portfolio monitoring tasks. As some clients were invested in private equity or private debt funds, it was necessary to respond to capital calls issued by fund managers, ensuring that clients’ accounts held sufficient cash to meet these capital requirements. I was also responsible for verifying portfolio data on tools such as Quantalys in order to accurately calculate and present performance results to clients. Quantalys is a tool used mainly by wealth managers (but also asset managers) to back test and build hypothetical portfolios, in order to analyze what would have been the performance over time. We used it to build portfolios and to track their associated performance. Each time we made allocation decisions, we had to update the portfolio data in the tool. This tool is also a huge database gathering all the funds available in the world.

Reporting & Marketing

I was responsible for producing client reporting. This involved preparing portfolio reports using various portfolio management and analytics tools such as FactSet, a leading financial data and analytics platform widely used by investment professionals to access market data, company financials, fund analytics, and performance metrics (basically a concurrent of Bloomberg, which is more known), and Quantalys, which I already mentioned previously. I then led a reporting automation project, streamlining and significantly accelerating the production process. Initially, reports were produced manually using Excel; we transitioned the reporting framework to Power BI, Microsoft’s business intelligence and data visualization tool, which enables the automation of data processing and the creation of interactive dashboards and dynamic reports. Within this framework, I fully developed both the quantitative data models and the visual reporting architecture, improving both accuracy and usability of client reports. In addition, when we conducted webinars or presentations for clients and prospective investors, I was responsible for producing ad hoc analyses on a range of topics, including macroeconomic developments, in-depth analysis of investment funds within our portfolios, and performance presentations supported by detailed charts. Finally, with the aim of demonstrating to potential prospects what their returns could have been if they had invested with us from a given starting point, I built an Excel-based model tracking the performance of the proposed model portfolio.

Required skills and knowledge

In this profession, and particularly within this firm, the required knowledge primarily relates to financial markets. We must have a solid understanding of a wide range of financial investments (equities, bonds and different bond structures, private markets such as private equity, private debt including secondary markets, infrastructure, specialized investment funds such as semi-liquid evergreen funds, structured products, etc.). It is also essential to be comfortable with economic and geopolitical news, as well as macroeconomic analysis, in order to build the most suitable portfolios for clients. In terms of skills, strong data analysis capabilities and a high level of rigor are required when interpreting financial information. Finally, strong communication skills are essential: being comfortable speaking with clients, demonstrating active listening, and providing tailored analysis to meet each client’s specific needs.

What I learned

First, I strengthened my knowledge of financial markets. Being attached to the investment management team, I discovered numerous asset classes that I had not previously been familiar with. I then gained an understanding of how investments work in practice and which vehicles are available in France to invest. Taxation plays a central role in wealth management, and I learned to understand its constraints in order to grasp how it impacts an individual’s overall wealth. Finally, I learned how to work cross-functionally with multiple teams, an essential aspect of the financial advisor’s role. This experience also allowed me to develop key professional qualities: rigor, analytical thinking, autonomy, as well as collaboration and a strong sense of collegiality.

Financial concepts related to my internship

I present below three financial concepts related to my internship: investment horizon, diversification, and the importance of a qualitative relationship with clients.

Investment Horizon

As a financial advisor, wealth manager or even a regular investor, before building a portfolio or making any investment, it is essential to define a key parameter, a parameter that even takes precedence over the client’s risk aversion: the investment horizon. According to the French Regulator (Autorité des Marchés Financiers or AMF), the investment horizon corresponds to the period during which an investor plans to hold a financial product. In other words, the investor identifies their liquidity needs beforehand and ensures they will not need to unwind their positions before the end of that period. This concept matters because there is a significant difference between the ease of selling an asset and the speed at which cash can be withdrawn without loss. Consider an equity portfolio, for example. While stocks are known for being liquid, meaning investors can buy or sell them with relative ease, it is risky to invest in equities with a short investment horizon. John Maynard Keynes often reminded us that no one, ever, was and will be able to time the market consistently. Because of this structural uncertainty, an investor may suddenly face substantial losses, as it happened during the subprime crisis. It took roughly five years for the S&P 500 to recover its pre-crisis levels and erase the losses caused by the collapse of the U.S. housing market. If an investor had needed liquidity only two years after the crisis, they would have locked in heavy losses. But had they waited longer, exiting after the recommended 7 to 8-year horizon for an equity portfolio, they would not only have recovered from the 2008 downturn, but also benefited from strong capital gains. Therefore, it is crucial for any client to understand their investment horizon and anticipate potential liquidity needs. With this mindset, they can better protect themselves against the inherent uncertainty of financial markets.

Diversification

Diversification is one of the fundamental principles of portfolio management. Throughout this experience, I realized that it goes far beyond simply spreading investments across several assets: it involves building an allocation capable of withstanding various market scenarios. To diversify is to accept that we can never predict with certainty which asset will outperform, but that we can significantly reduce risk by avoiding dependence on a single source of performance. Diversification can be applied at multiple levels. Within an equity portfolio, for example, it can be beneficial to gain exposure to different geographical regions (US, Europe, Asia, Emerging Markets, etc.), to different currencies (EUR, USD, GBP, etc.), and to various economic sectors (healthcare, financials, industrials, etc.). But diversification must also be executed on a broader scale, across the entire wealth base. It is essential to split the overall assets into several relatively small investments across different vehicles. To ensure efficient diversification, it is crucial to explore and invest in multiple asset classes. Part of the portfolio should be dedicated to growth, invested in riskier assets with higher return potential (equities, structured products, private equity, venture capital, cryptocurrencies, commodities…). Another portion should be allocated to defensive assets to preserve wealth (income-producing real estate, bonds, private debt, or precautionary cash reserves). This approach to diversification achieves several objectives: first, it breaks down wealth into multiple sources of income that do not depend on one another. Second, it helps dilute risk by investing in assets that are uncorrelated. Finally, it allows for a strategic allocation of resources across different investment goals: income generation, growth, and capital preservation.

Importance of a qualitative relationship with clients

To conclude this article, I would like to highlight the importance of the relationship between the advisor and the client. Beyond the technical aspects of investing, this relationship forms the true foundation of successful wealth management. An allocation can be perfectly constructed, a portfolio ideally diversified, and an investment horizon carefully respected… but without a relationship built on trust, no strategy can truly succeed. I understood that this relationship relies above all on attentive listening and a deep understanding of the client’s objectives: their projects, constraints, personal situation and family situation. An advisor is not only a financial technician, he or she is a reliable source of support in whom the client can place their trust. The advisor must also demonstrate strong pedagogical skills to help clients navigate a complex and time-consuming financial environment. In 2023, Danielle Labotka, a behavioral scientist, conducted a study for Morningstar involving a large sample of clients working with financial advisors. The study revealed that 21% of respondents (3,003 respondents) consider the quality of the relationship with their advisor to be the most important factor, surpassing all other aspects shown below :

Importance of concepts among financial advisors’ customers

Source: Morningstar, April 2023, Danielle Labotka, “Why Do Investors Fire Their Financial Adviser?”

Why should I be interested in this post?

The world of wealth management and financial advisory is experiencing strong growth, particularly in France, a country where financial literacy is steadily increasing and where individuals are increasingly aware that putting their savings to work is essential to building long-term wealth. According to the CNCGP (the national chamber of financial advisors, “Chambre Nationale des Conseils en Gestion de Patrimoine”), and their last report in 2025, called Baromètre 2025, France was counting in 2023, 23,16 structures providing financial advisory services to French customers. In 2024, this number rose to 2,439, which represents a +5,3% increase. This number is expected to grow, since according to studies made by Statista in October 2025, the number of assets under management by wealth managers in France should rise at a rate of +1,6% per year until between 2025 and 2029. This means that they will have that wealth managers will have to deal with more and more clients and therefore, investments. Certain structural issues in France, such as the pension system, are beginning to reveal their limitations, making it important for individuals to no longer rely solely on the State to finance their post-career years. As a result, the wealth management industry presents significant opportunities for the future. This profession also represents a balance between market finance, corporate finance, and client relationship management, fields that are deeply interconnected in the day-to-day practice of the role.

Useful resources

Labotka, D. (2023) Why do investors ‘break up’ with their financial adviser? Morningstar.

Autorité des Marchés Financiers Horizon de placement

European Fund and Asset Management Association (EFAMA) UCITS

Macrotrends S&P 500 Historical chart

French Family Office Association (AFFO) Family Office : Definition and Mission

Leclerc C. (26/09/2025) Les family offices au service des patrimoines sophistiqués ClubPatrimoine.

Chambre Nationale des Conseils en Gestion de Patrimoine (CNCGP) Baromètre 2025, état des lieux de la profession.

Statista (October 2025) Wealth Management – Data for France

About the author

The article was written in December 2025 by Jules HERNANDEZ (ESSEC Business School, Global Bachelor in Business Administration (GBBA), 2021-2025).

▶ Read all articles by Jules HERNANDEZ.

“The stock market is filled with individuals who know the price of everything, but the value of nothing.” – Philip Fisher

December 17, 2025 by Hadrien PUCHE

Financial markets are filled with numbers that move every second, yet many investors miss the most important insight: true value often lies hidden beneath the surface of the price.

In this article, Hadrien Puche (ESSEC, Grande École, Master in Management, 2023-2027) comments on this quote by Philip Fisher, who reminds us that understanding a stock’s price does not equal understanding the business it represents.

About Philip Fisher

Philip Fisher

Source: Banco Carregosa

Philip Fisher was one of the most respected investors of the twentieth century, and a true pioneer of growth investing. His book Common Stocks and Uncommon Profits (1958) profoundly influenced generations of investors, including Warren Buffett. Fisher was known for his focus on long-term thinking, innovation, and the qualitative aspects of companies, such as the quality of their management and their ability to grow sustainably, rather than on short-term market fluctuations.

Fisher wanted to emphasize that many players focus only on fleeting gains. Many market participants look only at short-term movements. They react to price changes, trends, and market noise, trying to profit quickly without ever questioning what those prices truly represent. They know the numbers, but they ignore the narrative and substance behind them.

By contrast, value-oriented investors, a movement beautifully illustrated by Benjamin Graham and his work The Intelligent Investor, seek to understand the fundamentals. They analyze business models, competitive advantages, and long-term prospects. They recognize that real wealth creation comes not from anticipating market swings, but from identifying companies that generate lasting value over time.

Analysis of the Quote

Most people active in financial markets are obsessed with prices. They can quote them instantly, track them in real time, and build strategies around them. Yet, few take the time to understand the real worth of what they are trading. They follow market sentiment and aim for short-term profits, often ignoring the bigger picture.

At his time, by “individuals”, Philip Fisher mostly meant individual investors. Nowadays, whilst financial institutions play a much larger role in financial markets, it’s very interesting to see that it still applies to many of them. Just like individuals in the past, and despite being much more aware of this issue, they too focus mostly on momentum and very short-term price signals over in-depth fundamental analysis. Ask a trader to price any derivative, and he will do so without ever even trying to understand the quality of the underlying asset.

True investors think differently. They are less concerned with what the market says today and more interested in what a company will be worth in five or ten years. They try to connect numbers with meaning, and prices with fundamentals. Fisher’s quote is a warning against superficiality, and a call to think independently, with patience and perspective.

Economic and Financial Concepts Related to the Quote

We can now introduce four financial concepts that are related to the quote, and that are interesting for you to understand.

1 – Financial Markets and Capital Allocation

At their core, financial markets exist to efficiently allocate capital between those who need it and those who can provide it. There are mostly two kind of capital markets :

The primary market allows companies to issue new stocks or bonds to raise fresh capital (fundraising).
The secondary market (the stock exchanges like NYSE or Euronext) allows these securities to be traded among investors.

These two markets are intrinsically linked: the valuation on the secondary market (the price investors are willing to pay) determines the ease and cost for a company to raise funds in the primary market.

The NYSE trading floor

Source: NBC News

In theory, market prices should reflect all available information about an asset’s value. However, in practice, markets are influenced by emotion, speculation, and herd behavior, leading to what economist Robert Shiller termed “irrational exuberance.”

When investors focus only on short-term price movements, markets lose their function as efficient resource allocators. Instead of financing innovation and productive activity, they become driven by speculation and volatility.

Fisher’s quote is therefore a reminder that the health of financial markets depends on the ability of participants to look beyond immediate prices and evaluate the long-term value of what they are trading.

2 – Intrinsic Value vs. Market Price

The distinction between intrinsic value and market price lies at the heart of investing. The market price represents what buyers and sellers agree upon at a given moment. It fluctuates constantly, influenced by supply, demand, and investor psychology. Intrinsic value, on the other hand, is the true economic worth of an asset, based on fundamentals such as earnings potential, discounted cash flows, and long-term growth prospects.

Fisher, like Graham, believed that markets often misprice securities in the short term. The wise investor’s role is therefore to identify when the market price diverges from intrinsic value, and to act accordingly. This requires patience, analysis, and a willingness to go against the crowd.

This idea resonates particularly in the context of private companies and Private Equity. When a private equity firm buys a public company to take it private, it is often because it perceives a significant intrinsic value that the public market, obsessed with prices and quarterly results, has ignored or underestimated. By delisting it from the Stock Exchange, the firm can focus on long-term value creation, away from the pressures of public trading. The transaction itself is a materialization of the conviction that the market has confused price with value.

3 – Fundamental Analysis versus Technical Analysis

Fundamental analysis is the process of determining a company’s intrinsic value by studying its financial statements, business model, and broader environment. It involves assessing profitability, growth potential, competitive positioning, and management quality. Fisher elevated this approach by emphasizing qualitative aspects: how innovative a company is, how it treats employees, and what it is currently planning for the future.

In contrast, technical analysis focuses exclusively on studying past price movements and trading volumes to anticipate future market trends. It relies on charts, indicators (like moving averages or the RSI), and patterns to identify entry and exit points. The technical analyst knows the price perfectly, but the foundation of their strategy is that history (the price) repeats itself, without requiring an understanding of the fundamental “why” of the business.

Example of a technical analysis on the IBM stock

Fundamental analysis delves into balance sheets and income statements to construct a valuation (the value), while technical analysis interprets graphical signals and market statistics to determine the probable direction of the price. Fisher’s quote is a direct critique of this latter approach, as it completely dissociates price from its underlying economic reality.

4 – Active versus Passive Asset Management

Fisher’s opposition between price and value also resonates in a frequent debate in the asset management industry : active versus passive investing.

– Active management is based on the conviction that superior analysis can “beat the market” by precisely identifying undervalued (more value than price) or overvalued assets. Active managers, like Fisher, are the direct inheritors of the quest for intrinsic value.

– Passive management (index funds, ETFs) adopts a radically different approach. Instead of seeking value, it accepts the market price and aims to replicate an index’s performance. It is based on the Efficient Market Hypothesis, where prices are generally “fair.”

In a way, the passive investor only cares about the average price, and never looks at the underlying value of what he is buying. On the other hand, for an active investor, price is only a starting point of a reflection that must somehow lead to a good understanding of value.

My Opinion on this Quote

This quote immediately brings to mind the 2008 financial crisis. At the time, banks and investors were trading increasingly complex financial products (such as mortgage-backed securities and other structured instruments) whose complexity made it hard, if not impossible, to understand what they were actually made of. Everybody knew their price, but few questioned their real value. The result was a global collapse, driven by overconfidence and a lack of due diligence by many.

Finance should serve as a tool to support economic growth, and channel capital towards the most productive projects. But instead, it is too often turned into a casino, where speculation replaces understanding and greed overrides prudence. Fisher’s quote reminds us that financial markets should serve society, not the other way around.

Why Should You Be Interested in this Post?

Because Fisher’s insight remains as relevant today as it was decades ago. Whether you are investing, studying finance, or simply following the markets, remember that prices only tell part of the story. Always take the time to understand what lies beneath them: the business, the people, the ideas.

Knowing the price is easy. Understanding the value is not.

Useful Resources

Fisher, P. (1958). Common Stocks and Uncommon Profits. New York, NY: Harper & Brothers.

Graham, B. (1949). The Intelligent Investor. New York, NY: Harper & Brothers.

Buffett, W. E. (1977–present). Annual Letters to Shareholders of Berkshire Hathaway Inc. Omaha, NE: Berkshire Hathaway Inc.

About the Author

This article was written in 2025 by Hadrien Puche (ESSEC, Grande École, Master in Management – 2023/2027).

My work-study experience in the Middle Office at Amundi

December 17, 2025December 15, 2025 by Clara COMBELLES

In this article, Clara COMBELLES (ESSEC Business School, Global Bachelor in Business Administration (GBBA), 2021-2025) shares her professional experience as a Middle Office analyst at Amundi, Europe’s leading asset manager.

About the company

Amundi is the largest asset manager in Europe and among the top ten worldwide. Created in 2010 through the merger of Crédit Agricole Asset Management and Société Générale Asset Management, Amundi now manages more than €2,000 billion in assets for retail, institutional and corporate clients.

Logo of Amundi.

Source: the company.

Amundi offers a wide range of investment solutions including active management, passive strategies, responsible investment, real assets, and advisory services. The group operates in over 35 countries with more than 5,000 employees and is listed on Euronext Paris.

Within Amundi, I worked in the Middle Office Department, which plays a crucial operational role by ensuring the accuracy, reliability, and daily monitoring of all portfolio transactions. It acts as a bridge between portfolio managers, operations teams, accounting, risk management, and institutional clients.

My work-study program

My one-year work-study program immersed me in the operational heart of asset management. Working in the Middle Office gave me a transversal view of financial markets, portfolio management, and the full lifecycle of a transaction. I learned to manage time-sensitive tasks, handle large volumes of data, and collaborate with teams from different domains.

My missions

My daily tasks included several key responsibilities essential to the proper functioning of portfolios.

✔ Daily cash flow monitoring
Every morning, I reviewed all cash movements to ensure they aligned with portfolio expectations. This work prevents valuation errors and helps anticipate liquidity needs.

✔ Monthly securities position analysis
I carried out detailed monthly reconciliations between internal systems and accounting data to ensure that positions were accurately reflected and discrepancies were identified.

✔ Resolution of discrepancies and anomaly analysis
Whenever inconsistencies appeared — unexpected movements, trade errors, incorrect positions — I investigated their origin by liaising with operational teams such as trading, subscriptions/redemptions, fees, and accounting.

✔ Support to portfolio managers
I provided portfolio managers with operational insights, including historical flows and position analyses, to support their investment decisions.

✔ Production of client reporting
I contributed to the preparation of periodic reports sent to institutional clients, including asset allocation, performance, and risk indicators.

Required skills and knowledge

This role required strong analytical skills, attention to detail, and the ability to work under time pressure. On the technical side, I used portfolio management systems, Excel, and internal monitoring tools. Soft skills such as communication, teamwork, and problem-solving were essential to collaborate with multiple departments and resolve anomalies efficiently.

What I learned

This experience gave me a concrete understanding of the full lifecycle of a financial transaction, from order execution to final accounting. I developed strong operational and analytical skills, improved my ability to manage risks, and gained a transversal vision of asset management. I also learned the importance of precision, reliability, and responsiveness in the financial industry.

Financial concepts related to my internship

I present below three financial concepts related to my internship and explain their relevance to my missions: the lifecycle of a financial transaction, Net Asset Value (NAV), Operational risk management.

The lifecycle of a financial transaction

Every trade goes through several steps: order initiation, execution, settlement, booking, reconciliation and final reporting. My role in the Middle Office was directly linked to the final steps of this lifecycle, where accuracy and consistency are essential to ensure proper valuation of portfolios.

Net Asset Value (NAV)

Accurate valuation of funds depends on precise cash balances, up-to-date positions, and correctly recorded transactions. My checks on cash flows and monthly reconciliations ensured NAV reliability, which is crucial for investment decisions and client reporting.

Operational risk management

Operational errors—missing trades, incorrect positions, or inconsistent data—can lead to significant financial and reputational risks. By identifying anomalies, coordinating with teams, and resolving breaks, I actively contributed to reducing operational risk within the portfolios.

Why should I be interested in this post?

Students interested in finance often focus on front-office roles, but the Middle Office offers a unique opportunity to understand the full operational framework behind investment decisions. It is an excellent entry point into asset management, providing exposure to financial instruments, risk control, portfolio valuation, and cross-team collaboration. This experience builds a solid foundation for future careers in investment management, risk, operations, or financial analysis.

Useful resources

Amundi – Official Website

Basel Committee on Banking Supervision (2011) Principles for the Sound Management of Operational Risk.

About the author

The article was written in December 2025 by Clara COMBELLES (ESSEC Business School, Global Bachelor in Business Administration (GBBA), 2021-2025).

▶ Read all articles by Clara COMBELLES.

Historical Volatility

December 20, 2025December 14, 2025 by Saral BINDAL

In this article, Saral BINDAL (Indian Institute of Technology Kharagpur, Metallurgical and Materials Engineering, 2024-2028 & Research Assistant at ESSEC Business School) explains the concept of historical volatility used in financial markets to represent and measure the changes in asset prices.

Introduction

Volatility in financial markets refers to the degree of variation in an asset’s price or returns over time. Simply put, an asset is considered highly volatile when its price experiences large upward or downward movements, and less volatile when those movements are relatively small. Volatility plays a central role in finance as an indicator of risk and is widely used in various portfolio and risk management techniques.

In practice, the concept of volatility can be operationalized in different ways: historical volatility and implied volatility. Traders and analysts use historical volatility to understand an asset’s past performance and implied volatility as a forward-looking measure of upcoming uncertainties in the market.

Historical volatility measures the actual variability of an asset’s price over a past period, calculated as the standard deviation of its historical returns. Computed over different periods (say a month), historical volatility allows investors to identify trends in volatility and assess how an asset has reacted to market conditions in the past.

Practical Example: Analysis of the S&P 500 Index

Let us consider the S&P 500 index as an example of the calculation of volatility.

Prices

Figure 1 below illustrates the daily closing price of the S&P 500 index over the period from January 2020 to December 2025.

Figure 1. Daily closing prices of the S&P 500 index (2020-2025).

Source: computation by the author.

Returns

Returns are the percentage gain or loss on the asset’s investment and are generally calculated using one of two methods: arithmetic (simple) or logarithmic (continuously compounded).

Returns Formulas

Where R_i represents the rate of return, and P_i denotes the asset’s price at a given point in time.

The preference for logarithmic returns stems from their property of time-additivity, which simplifies multi-period calculations (the monthly log return is equal to the sum of the daily log returns of the month, which is not the case for arithmetic return). Furthermore, logarithmic returns align with the geometric mean thereby mathematically capture the effects of compounding, unlike arithmetic return, which can overstate performance in volatile markets.

Distribution of returns

A statistical distribution describes the likelihood of different outcomes for a random variable. It begins with classifying the data as either discrete or continuous.

Figure 2 below illustrates the distribution of daily returns for S&P 500 index over the period from January 2020 to December 2025.

Figure 2. Historical distribution of daily returns of the S&P 500 index (2020-2025).

Source: computation by the author.

Standard deviation of the distribution of returns

In real life, as we do not know the mean and standard deviation of returns, these parameters have to be estimated with data.

The estimator for the mean μ, denoted by μ̂, and the estimator for the variance σ², denoted by σ̂², are given by the following formulas:

Formulas for the mean and variance estimators

With the following notations:

R_i = rate of return for the i^th day
μ̂ = estimated mean of the data
σ̂² = estimated variance of the data
n = total number of days for the data

These estimators are unbiased and efficient (note the Bessel’s correction for the standard deviation when we divide by (n–1) instead of n).

Unbiased estimators of the mean and variance

For the distribution of returns in Figure 2, the mean and standard deviation calculated using the formulas above are 0.049% and 1.068%, respectively (in daily units).

Annualized volatility

As the usual time frame for human is the year, volatility is often annualized. In order to obtain annual (or annualized) volatility, we scale the daily volatility by the square root of the number of days in that period (τ), as shown below.

Annual Volatility formula

Where  is the number of trading days during the calendar year.

In the U.S. equity market, the annual number of trading days typically ranges from 250 to 255 (252 tradings days in 2025). This variation reflects the holiday calendar: when a holiday falls on a weekday, the exchange closes ; when it falls on a weekend, trading is unaffected. In contrast, the cryptocurrency market has as many trading days as there are calendar days in a year, since it operates continuously, 24/7.

For the S&P 500 index over the period from January 2020 to December 2025, the annualized volatility is given by

S&P500index Annual Volatility formula

Annualized mean

The calculated mean for the 5-year S&P 500 logarithmic returns is also the daily average return for the period. The annualized average return is given by the formula below.

Annualized mean formula

Where τ is the number of trading days during the calendar year.

For the S&P 500 index over the period from January 2020 to December 2025, the annualized average return is given by

Annualized mean formula

If the value of daily average return is much less than 1, annual average return can be approximated as

Annualized mean value

Application: Estimating the Future Price Range of the S&P 500 index

To develop an intuitive understanding of these figures, we can estimate the one-standard-deviation price range for the S&P 500 index over the next year. From the above calculations, we know that the annualized mean return is 12.534% and the annualized standard deviation is 16.953%.

Under the assumption of normally distributed logarithmic returns, we can say approximately with 68% confidence that the value of S&P 500 index is likely to be in the range of:

Upper and lower limits

If the current value of the S&P 500 index is $6,830, then converting these return estimates into price levels gives:

Upper and lower price limits

Based on a 68% confidence interval, the S&P 500 index is likely to trade in the range of $6,526 to $8,838 over the next year.

Historical Volatility

Historical volatility represents the variability of an asset’s returns over a chosen lookback period. The annualized historical volatility is estimated using the formula below.

Historical volatility formula

With the following notations:

σ = Standard deviation
R_i = Return
n = total number of trading days in the period (21 for 1 month, 63 for 3 months, etc.)
τ = Number of trading days in a calendar year

Volatility calculated over different periods must be annualized to a common timeframe to ensure comparability, as the standard convention in finance is to express volatility on an annual basis. Therefore, when working with daily returns, we annualize the volatility by multiplying it by the square root of 252.

For example, for the S&P 500 index, the annualized historical volatilities over the last 1 month, 3 months, and 6 months, computed on December 3, 2025, are 14.80%, 12.41%, and 11.03%, respectively. The results suggest, since the short term (1 month) volatility is higher than medium (3 months) and long term (6 months) volatility, the recent market movements have been turbulent as compared to the past few months, and due to volatility clustering, periods of high volatility often persist, suggesting that this elevated turbulence may continue in the near term.

Unconditional Volatility

Unconditional volatility is a single volatility number using all historical data, which in our example is the entire five years data; It does not account for the fact that recent market behavior is more relevant for predicting tomorrow’s risk than events from past years, implying that volatility changes over time. It is frequently observed that after any sudden boom or crash in the market, as the storm passes away the volatility tends to revert to a constant value and that value is given by the unconditional volatility of the entire period. This tendency is referred to as mean reversion.

For instance, using S&P 500 index data from 2020 to 2025, the unconditional volatility (annualized standard deviation) is calculated to be 16.952%.

Rolling historical volatility

A single volatility number often fails to capture changing market regimes. Therefore, a rolling historical volatility is usually generated to track the evolution of market risk. By calculating the standard deviation over a moving window, we can observe how volatility has expanded or contracted historically. This is illustrated in Figure 3 below for the annualized 3-month historical volatility of the S&P 500 index over the period 2020-2025.

Figure 3. 3-month rolling historical volatility of the S&P500 index (2020-2025).

Source: computation by the author.

In Figure 3, the 3-month rolling historical volatility is plotted along with the unconditional volatility computed over the entire period, calculated using overlapping windows to generate a continuous series. This provides a clear historical perspective, showcasing how the asset’s volatility has fluctuated relative to its long-term average.

For example, during the start of Russia–Ukraine war (February 2022 – August 2022), a noticeable jump in volatility occurred as energy and food prices surged amid fears of supply chain disruptions, given that Russia and Ukraine are major exporters of oil, natural gas, wheat, and other commodities.

The rolling window can be either overlapping or non-overlapping, resulting in continuous or discrete graphs, respectively. Overlapping windows shift by one day, creating a smooth and continuous volatility series, whereas non-overlapping windows shift by one time period, producing a discrete series.

You can download the Excel file provided below, which contains the computation of returns, their historical distribution, the unconditional historical volatility, and the 3-month rolling historical volatility of the S&P 500 index used in this article.

You can download the Python code provided below, which contains the computation of returns, first four moments of the distribution, and experiment with the x-month rolling historical volatility function to visualize the evolution of historical volatility over time.

Alternatively, you can download the R code below with the same functionality as in the Python file.

Alterative measures of volatility

We now mention a few other ways volatility can be measured: Parkinson volatility, Implied volatility, ARCH model, and stochastic volatility model.

Parkinson volatility

The Parkinson model (1980) uses the highest and lowest prices during a given period (say a month) for the purpose of measurement of volatility. This model is a high-low volatility measure, based on the difference between the maximum and minimum prices observed during a certain period.

Parkinson volatility is a range-based variance estimator that replaces squared returns with the squared high–low log price range, scaled to remain unbiased. It assumes a driftless (expected growth rate of the stock price equal to zero) geometric Brownian motion, it is five times more efficient than close-to-close returns because it accounts for fluctuation of stock price within a day.

For a sample of n observations (say days), the Parkinson volatility is given by

Parkinson Volatility formula

where:

H_t is the highest price on period t
L_t is the lowest price on period t

Implied volatility

Implied Volatility (IV) is the level of volatility for the underlying asset that, when plugged into an option pricing model such as Black–Scholes–Merton, makes the model’s theoretical option price equal to the option’s observed market price.

It is a forward looking measure because it reflects the market’s expectation of how much the underlying asset’s price is likely to fluctuate over the remaining life of the option, rather than how much it has moved in the past.

The Chicago Board Options Exchange (CBOE), a leading global financial exchange operator provides implied volatility indices like the VIX and Implied Correlation Index, measuring 30-day expected volatility from SPX options. These are used by traders to gauge market fear, speculate via futures/options/ETPs, hedge equity portfolios and manage risk during volatility spikes.

ARCH model

Autoregressive Conditional Heteroscedasticity (ARCH) models address time-varying volatility in time series data. Introduced by Engle in 1982, ARCH models look at the size of past shocks to estimate how volatile the next period is likely to be. If recent movements were big, the model expects higher volatility; if they were small, it expects lower volatility justifying the idea of volatility clustering. Originally applied to inflation data, this model has been widely used in to model financial data.

ARCH model capture volatility clustering, which refers to an observation about how volatility behaves in the short term, a large movement is usually followed by another large movement, thus volatility is predictable in the short term. Historical volatility gives a short-term hint of the near future changes in the market because recent noise often continues.

Generalized Autoregressive Conditional Heteroscedasticity (GARCH) extends ARCH by past predicted volatility, not just past shocks, as refined by Bollerslev in 1986 from Engle’s work. Both of these methods are more accurate methods to forecast volatility than what we had discussed as they account for the time varying nature of volatility.

Stochastic volatility models

In practice, volatility is time-varying: it exhibits clustering, persistence, and mean reversion. To capture these empirical features, stochastic volatility (SV) models treat volatility not as a constant parameter but as a stochastic process jointly evolving with the asset price. Among these models, the Heston (1993) specification is one of the most influential.

The Heston model assumes that the asset price follows a diffusion process analogous to geometric Brownian motion, while the instantaneous variance evolves according to a mean-reverting square-root process. Moreover, the innovations to the price and variance processes are correlated, thereby capturing the leverage effect frequently observed in equity markets.

Applications in finance

This section covers key mathematical concepts and fundamental principles of portfolio management, highlighting the role of volatility in assessing risk.

The normal distribution

The normal distribution is one of the most commonly used probability distribution of a random variable with a unimodal, symmetric and bell-shaped curve. The probability distribution function for a random variable X following a normal distribution with mean μ and variance σ² is given by

Normal distribution function

A random variable X is said to follow standard normal distribution if its mean is zero and variance is one.

The figure below represents the confidence intervals, showing the percentage of data falling within one, two, and three standard deviations from the mean.

Figure 4. Probability density function and confidence intervals for a standard normal varaible.
Standard normal distribution” width=
Source: computation by the author

Brownian motion

Robert Brown first observed Brownian motion was as the erratic and random movement of pollen particles suspended in water due to constant collision with water molecules. It was later formulated mathematically by Norbert Wiener and is also known as the Wiener process.

The random walk theory suggests that it’s impossible to predict future stock prices as they move randomly, and when the timestep of this theory becomes infinitesimally small it becomes, Brownian Motion.

In the context of financial stochastic process, when the market is modeled by the standard Brownian motion, the probability distribution function of the future price is a normal distribution, whereas when modeled by Geometric Brownian Motion, the future prices are said to be lognormally distributed. This is also called the Brownian Motion hypothesis on the movement of stock prices.

The process of a standard Brownian motion is given by:

Standard Brownian motion formula.

The process of a geometric Brownian motion is given by:

Geometric Brownian motion formula.

Where, dS_t is the change in asset price in continuous time dt, dX_t is a random variable from the normal distribution (N (0, 1)) or Wiener process at a time t, σ represents the price volatility, and μ represents the expected growth rate of the asset price, also known as the ‘drift’.

Modern Portfolio Theory (MPT)

Modern Portfolio Theory (MPT), developed by Nobel Laureate, Harry Markowitz, in the 1950s, is a framework for constructing optimal investment portfolios, derived from the foundational mean-variance model.

The Markowitz mean–variance model suggests that risk can be reduced through diversification. It proposes that risk-averse investors should optimize their portfolios by selecting a combination of assets that balances expected return and risk, thereby achieving the best possible return for the level of risk they are willing to take. The optimal trade-off curve between expected return and risk, commonly known as the efficient frontier, represents the set of portfolios that maximizes expected return for each level of standard deviation (risk).

Capital Asset Pricing Model (CAPM)

The Capital Asset Pricing Model (CAPM) builds on the model of portfolio choice developed by Harry Markowitz (1952), stated above. CAPM states that, assuming full agreement on return distributions and either risk-free borrowing/lending or unrestricted short selling, the value-weighted market portfolio of risky assets is mean-variance efficient, and expected returns are linear in the market beta.

The main result of the CAPM is a simple mathematical formula that links the expected return of an asset to its risk measured by the beta of the asset:

CAPM formula

Where:

E(R_i) = expected return of asset i
R_f = risk-free rate
β_i = measure of the risk of asset i
E(R_m) = expected return of the market
E(R_m) − R_f = market risk premium

CAPM recognizes that an asset’s total risk has two components: systematic risk and specific risk, but only systematic risk is compensated in expected returns.

Returns decomposition fromula.

Where the realized (actual) returns of the market (R_m) and the asset (R_i) exceed their expected values only because of consideration of systematic risk (ε).

Decomposition of risk.
Decompositionion of risk

Systematic risk is a macro-level form of risk that affects a large number of assets to one degree or another, and therefore cannot be eliminated. General economic conditions, such as inflation, interest rates, geopolitical risk or exchange rates are all examples of systematic risk factors.

Specific risk (also called idiosyncratic risk or unsystematic risk), on the other hand, is a micro-level form of risk that specifically affects a single asset or narrow group of assets. It involves special risk that is unconnected to the market and reflects the unique nature of the asset. For example, company specific financial or business decisions which resulted in lower earnings and affected the stock prices negatively. However, it did not impact other asset’s performance in the portfolio. Other examples of specific risk might include a firm’s credit rating, negative press reports about a business, or a strike affecting a particular company.

Why should I be interested in this post?

Understanding different measures of volatility, is a pre-requisite to better assess potential losses, optimize portfolio allocation, and make informed decisions to balance risk and expected return. Volatility is fundamental to risk management and constructing investment strategies.

Useful Resources

Academic research

Bollerslev, T. (1986). Generalized Autoregressive Conditional Heteroskedasticity, Journal of Econometrics, 31(3), 307–327.

Engle, R. F. (1982). Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation, Econometrica, 50(4), 987–1007.

Fama, E. F., & French, K. R. (2004). The Capital Asset Pricing Model: Theory and Evidence, Journal of Economic Perspectives, 18(3), 25–46.

Heston, S. L. (1993). A Closed-Form Solution for Options with Stochastic Volatility with Applications to Bond and Currency Options, The Journal of Finance, 48(3), 1–24.

Markowitz, H. M. (1952). Portfolio Selection, The Journal of Finance, 7(1), 77–91.

Parkinson, M. (1980). The extreme value method for estimating the variance of the rate of return. Journal of Business, 53(1), 61–65.

Sharpe, W. F. (1964). Capital Asset Prices: A Theory of Market Equilibrium under Conditions of Risk, The Journal of Finance, 19(3), 425–442.

Tsay, R. S. (2010). Analysis of financial time series, John Wiley & Sons.

Other

NYU Stern Volatility Lab Volatility analysis documentation.

Extreme Events in Finance Risk maps: extreme risk, risk and performance.

About the author

The article was written in December 2025 by Saral BINDAL (Indian Institute of Technology Kharagpur, Metallurgical and Materials Engineering, 2024-2028 & Research Assistant at ESSEC Business School).

▶ Read all articles by Saral BINDAL.

The “lemming effect” in finance

December 14, 2025 by Lang Chin SHIU

In this article, SHIU Lang Chin (ESSEC Business School, Global Bachelor in Business Administration (GBBA), 2024-2026) explains the “lemming effect” in financial markets, inspired by the animated movie Zootopia.

About the concept

The “lemming effect” refers to situations where individuals follow the crowd unthinkingly, just as lemmings are believed to follow one another off a cliff. In finance, this idea is linked to herd behaviour: investors imitate the actions of others instead of relying on their own information or analysis.

The image above is a cartoon showing a line of lemmings running off a cliff, with several already falling through the air. The caption “The Lemming Effect: Stop! There is another way” warns that blindly following others can lead to disaster, even if “everyone is doing it.” The message is to think independently, question group behaviour, and choose an alternative path instead of copying the crowd.

In Zootopia, there is a scene where lemmings dressed as bankers leave their office and are supposed to walk straight home after work. However, after one lemming notices Nick selling popsicles and suddenly changes direction to buy one, the rest of the lemmings automatically follow and queue up too, even though this is completely different from their original route and plan. This illustrates how individuals can abandon their own path and intentions simply because they see someone else acting first, much like investors may follow others into a trade or trend without conducting independent analysis.

Watch the video!

Source: Zootopia (Disney, 2016).

The first image shows Nick Wilde (the fox) holding a red paw-shaped popsicle. In the film, Nick uses this eye‑catching pawpsicle as a marketing tool to attract the lemmings and earn a profit.

zootopia lemmings
Source: Zootopia (Disney, 2016).

The second image shows a group of identical lemmings in suits walking in and out of a building labelled “Lemming Brothers Bank.” This is a parody of the real investment bank “Lehman Brothers,” which collapsed during the 2008 financial crisis. When one lemming notices the pawpsicle, it immediately changes direction from going home and heads toward Nick to buy the product, illustrating how one individual’s choice triggers the rest to follow.

zootopia lemmings
Source: Zootopia (Disney, 2016).

The third image shows Nick successfully selling pawpsicles to a whole line of lemmings. Nick is exploiting the lemmings’ herd‑like behaviour: once a few begin buying, the others automatically copy them and all purchase the same pawpsicle. The humour lies in how Nick profits from their conformity, using their predictable group behaviour—the “lemming effect”—to make easy money.

zootopia lemmings
Source: Zootopia (Disney, 2016).

Behavioural finance uses the lemming effect to describe deviations from perfectly rational decision-making. Rather than analysing fundamentals calmly, investors may be influenced by social proof, fear of missing out (FOMO) or the comfort of doing what “everyone else” seems to be doing.

Understanding the lemming effect is important both for professional investors and students of finance. It helps to explain why markets sometimes move far away from fundamental values and reminds decision-makers to be cautious when “the whole market” points in the same direction.

How the lemming effect appears in markets

In practice, the lemming effect can be seen when large numbers of investors buy the same “hot” stocks simply because prices are rising, they assume that so many others doing the same thing cannot be wrong.

It applies in reverse during market downturns. Bad news, rumours, or sharp price declines can trigger a wave of selling. The fear of being the last one can push them to copy others’ behaviour rather than stick to their original plan.

Such herd-driven moves can amplify volatility, push prices far above or below intrinsic value, and create opportunities or risks that would not exist in a purely rational market. Recognising these dynamics helps investors to step back and question whether they are thinking independently.

Related financial concepts

The lemming effect connects naturally with several basic financial ideas: diversification, risk-return trade-off, market efficiency, Keynes’ beauty contest and gamestop story. It shows how human behaviour can distort these textbook concepts in real markets.

Diversification

Diversification means not putting all your money in the same blanket (asset or sector), so that the poor performance of one investment does not destroy the whole. When the lemming effect is strong, investors often forget diversification and concentrate on a few “popular” stocks. From a diversification perspective, following the crowd can increase risk without necessarily increasing expected returns.

Risk and return

Finance said that higher expected returns usually come with higher risk. However, when many investors behave like lemmings, they may underestimate the true risk of crowded trades. Rising prices can create an illusion of safety, even if fundamentals do not justify the move. Understanding the lemming effect reminds investors to ask whether a sustainable increase in expected return really compensates the extra risk taken by following the crowd.

Market efficiency

In an efficient market, prices should reflect all available information. Herd behaviour and the lemming effect demonstrate that markets can deviate from this ideal when many investors react based on emotions or social cues rather than information. Short-term mispricing created by herding can eventually be corrected when new information becomes available or when rational investors intervene. For students, this illustrates why theoretical models of perfect efficiency are useful benchmarks but do not fully capture real-world behaviour.

Keynes’ beauty contest

Keynes’ “beauty contest” analogy describes investors who do not choose stocks based on their own view of fundamental value, but instead try to guess what everyone else will think is beautiful.Instead of asking “Which company is truly best?”, they ask “Which company does the average investor think others will like?” and buy that, hoping to sell to the next person at a higher price. This links directly to the lemming effect: investors watch each other and pile into the same trades, just like the lemmings all changing direction to follow the first one who goes for the pawpsicle.

GameStop story

The GameStop short squeeze in 2021 is a modern real‑world illustration of herd behaviour. A large crowd of retail investors on Reddit and other forums started buying GameStop shares together, partly for profit and partly as a social movement against hedge funds, driving the price far above what traditional valuation models would suggest. Once the price started to rise sharply, more and more people jumped in because they saw others making money and feared missing out, reinforcing the crowd dynamic in a very “lemming‑like” way.

Why should I be interested in this post?

For business and finance students, the lemming effect is a bridge between psychology and technical finance. It helps explain why prices sometimes move in surprising ways, and why sticking mindlessly to the crowd can be dangerous for long-term wealth.

Whether you plan to work in banking, asset management, consulting or corporate finance, understanding herd behaviour can improve your judgment. It encourages you to combine quantitative tools with a critical view of market sentiment, so that you do not become the next “lemming” in a crowded trade.

Useful resources

BBC Five animals to spot in a post-Covid financial jungle

Tversky, A., & Kahneman, D. (1973). Availability: A heuristic for judging frequency and probability. Cognitive psychology, 5(2), 207-232.

Gupta, S., & Shrivastava, M. (2022). Herding and loss aversion in stock markets: mediating role of fear of missing out (FOMO) in retail investors. International Journal of Emerging Markets, 17(7), 1720-1737.

Gupta, S., & Shrivastava, M. (2022). Argan, M., Altundal, V., & Tokay Argan, M. (2023). What is the role of FoMO in individual investment behavior? The relationship among FoMO, involvement, engagement, and satisfaction. Journal of East-West Business, 29(1), 69-96.

About the author

The article was written in December 2025 by SHIU Lang Chin (ESSEC Business School, Global Bachelor in Business Administration (GBBA), 2024-2026).

▶ Read all articles by SHIU Lang Chin.

Time value of money

December 13, 2025December 13, 2025 by Lang Chin SHIU

In this article, SHIU Lang Chin (ESSEC Business School, Global Bachelor in Business Administration (GBBA), 2024-2026) explains the time value of money, a simple but fundamental concept used in all areas of finance.

Overview of the time value of money

The time value of money (TVM) is the idea that one euro today is worth more than one euro in the future because today’s money can be invested to earn interest. In other words, receiving cash earlier gives more opportunities to save, invest, and grow wealth over time. This principle serves as the foundation for valuing loans, bonds, investment projects, and many everyday financial decisions.

To work with TVM, finance uses a few key tools: present value (the value today of future cash flows), future value (the value in the future of money invested today),etc. With these elements, it becomes possible to compare different cash-flow patterns that occur at various dates consistently.

Future value

The future value (FV) of money answers the question: if I invest a certain amount today at a given interest rate, how much will I have after some time? Future value uses the principle of compounding, which means that interest earns interest when it is reinvested.

For a simple case with annual compounding, the formula is:

Future Value (FV)

where PV is the amount invested today, r is the annual interest rate, and T is the number of years.

For example, if 1,000 euros are invested at 5% per year for 3 years, the future value is FV = 1,000 × (1.05)^3 = 1,157.63 euros. This shows how even a modest interest rate can increase the value of an investment over time.

Compounding frequency can also change the result. If interest is compounded monthly instead of annually, the formula is adjusted to use a periodic rate and the total number of periods. The more frequently interest is added, the higher the future value for the same nominal annual rate, illustrating why compounding is such a powerful mechanism in long-term investing.

Compounding mechanism with monthy and annual compounding.

You can download the Excel file provided below, which contains the computation of an investment to illustrate the impact of the frequency on the compounding mechanism.

Present value

Present value (PV) is the reverse operation of future value and answers the question: how much is a future cash flow worth today? To find PV, the future cash flow is “discounted” back to today using an appropriate discount rate that reflects opportunity cost, risk and inflation.

For a single future cash flow, the present value formula is:

Present Value (PV)

Where FV is the future amount, r is the discount rate per period, and T is the number of periods.

For example, if an investor expects to receive 1,000 euros in 2 years and the discount rate is 5% per year, the present value is PV = 1,000 / (1.05)^2 = 907.03 euros. This means the investor would be indifferent between receiving 907.03 euros today or 1,000 euros in two years at that discount rate.

Choosing the discount rate is a key step: for a safe cash flow, a risk-free rate such as a government bond yield might be used, while for a risky project, a higher rate reflecting the required return of investors would be more appropriate. A higher discount rate reduces present values, making future cash flows less attractive compared to money today.

Applications of the time value of money

The time value of money is used in almost every area of finance. In corporate finance, it forms the basis of discounted cash-flow (DCF) analysis, where the expected future cash flows of a project or company are discounted to estimate the net present value. Investment decisions are typically made by comparing the present value to the initial cost.

DCF

In banking and personal finance, TVM is essential to design and understand loans, deposits and retirement plans. Customers who understand how interest rates and compounding work can better compare offers, negotiate terms and plan their savings. In capital markets, bond pricing, yield calculations and valuation of many other instruments depend directly on discounting streams of cash flows.

Even outside professional finance, TVM helps individuals answer simple but important questions: is it better to take a lump sum now or a stream of payments later, how much should be saved each month to reach a future target, or what is the true cost of borrowing at a given interest rate? A good intuition for TVM improves financial decision-making in everyday life.

Why should I be interested in this post?

As a university student, understanding TVM is essential because it underlies more advanced techniques such as discounted cash-flow (DCF) valuation, bond pricing and project evaluation. It is usually one of the first technical topics taught in introductory corporate finance and quantitative methods courses.

Useful resources

Harvard Business School Online Time value of money

Investing.com Time value of money: formula and examples

About the author

The article was written in December 2025 by SHIU Lang Chin (ESSEC Business School, Global Bachelor in Business Administration (GBBA), 2024-2026).

▶ Read all articles by SHIU Lang Chin.

Deep Dive into evergreen funds

December 12, 2025 by Emmanuel CYROT

In this article, Emmanuel CYROT (ESSEC Business School, Global Bachelor in Business Administration (GBBA), 2021-2026) introduces the ELTIF 2.0 Evergreen Fund.

Introduction

The asset management industry is pivoting to democratize private market access for the wealth segment. We are moving from the rigid Capital Commitment Model (the classic “blind pool” private equity structure) to the flexible NAV-Based Model, an open-ended structure where subscriptions and redemptions are executed at periodic asset valuations rather than through irregular capital calls. For technical product specialists, the ELTIF 2.0 regulation isn’t just a compliance update, it’s the architectural blueprint for the democratization of private markets. Here is the deep dive into how these “Semi-Liquid” or “Evergreen” structures actually work, the European landscape, and the engineering behind them.

The Liquidity Continuum: Solving the “J-Curve” Problem

To understand the evergreen structure, you have to understand what it fixes. In a traditional Closed-End Fund (the “Old Guard”):

The Cash Drag: You commit €100k, but the manager only calls 20% in Year 1. Your money sits idle.
The J-Curve: You pay fees on committed capital immediately, but the portfolio value drops initially due to costs before rising (the “J” shape).
The Lock: Your capital is trapped for 10-12 years. Secondary markets are your only (expensive) exit.

The Evergreen / Semi-Liquid Solution represents the structural convergence of private market asset exposure with an open-ended fund’s periodic subscription and redemption framework.

Fully Invested Day 1: Unlike the Capital Commitment model, your capital is put to work almost immediately upon subscription.
Perpetual Life: There is no “end date.” The fund can run for 99 years, recycling capital from exited deals into new ones.
NAV-Based: You buy in at the current Net Asset Value (NAV), similar to a mutual fund, rather than making a commitment.

The difference in investment processes between evergreen funds and closed ended funds

Source: Medium.

The European Landscape: The Rise of ELTIF 2.0

The “ELTIF 2.0” regulation (Regulation (EU) 2023/606) is the game-changer. It removed the extra local rules that held the market back in Europe. These rules included high national minimum investment thresholds for retail investors and overly restrictive limits on portfolio composition and liquidity features imposed by national regulators.

Market Data as of 2025 (Morgan Lewis)

Volume: The market is rapidly expanding, with over 160+ registered ELTIFs now active across Europe as of 2025.
The Hubs: Luxembourg is the dominant factory (approx. 60% of funds), followed by France (strong on the Fonds Professionnel Spécialisé or FPS wrapper) and Ireland.
The Arbitrage: The killer feature is the EU Marketing Passport. A French ELTIF can be sold to a retail investor in Germany or Italy without needing a local license. This allows managers to aggregate retail capital on a massive scale.

Structural Engineering: Liquidity

This section delves into the precise engineering required to reconcile the illiquidity of the underlying assets with the promise of periodic investor liquidity in Evergreen/Semi-Liquid funds. This is achieved through a combination of Asset Allocation Constraints and robust Liquidity Management Tools (LMTs).

The primary allocation constraint is the “Pocket” Strategy, or the 55/45 Rule. The fund is structurally divided into two distinct components. First, the Illiquid Core, which must represent greater than 55% of the portfolio, is the alpha engine holding long-term, illiquid assets such as Private Equity, Private Debt, or Infrastructure. Notably, ELTIF 2.0 has broadened the scope of this core to include newer asset classes like Fintechs and smaller listed companies. Second, the Liquid Pocket, which can be up to 45%, serves as the fund’s buffer, holding easily redeemable, UCITS-eligible assets like money market funds or government bonds. While the regulation permits a high 45% pocket, efficient fund operation typically keeps this buffer closer to 15%–20% to mitigate performance-killing “cash drag”.

Crucial to managing liquidity risk is the Gate Mechanism. Although the fund offers conditional liquidity (often quarterly), the Gate prevents a systemic crisis if many investors attempt to exit simultaneously. This mechanism works by capping redemptions at a specific percentage of the Net Asset Value (NAV) per period, commonly set at 5%. If aggregate redemption requests exceed this threshold (e.g., requests total 10%), all withdrawing investors receive a pro-rata share of the allowable 5% and the remainder of their request is deferred to the next liquidity window.

Finally, managers utilize Anti-Dilution Tools like Swing Pricing to protect the financial interests of the long-term investors remaining in the fund. In a scenario involving heavy redemptions, where the fund manager is forced to sell assets quickly and incur high transaction costs, Swing Pricing adjusts the NAV downwards only for the exiting investors. This critical mechanism ensures that those demanding liquidity—the “leavers”—bear the transactional “cost of liquidity,” thereby insulating the NAV of the “stayers” from dilution.

Why should I be interested in this post?

Mastering ELTIF 2.0 architecture offers a definitive edge over the standard curriculum. With the industry pivoting toward the “retailization” of private markets, understanding the engineering behind evergreen funds and liquidity gates demonstrates a level of practical sophistication that moves beyond theory—exactly what recruiters at top-tier firms like BlackRock or Amundi are seeking for their next analyst class.

Useful resources

Société Générale Fonds Evergreen et ELTIF 2 : Débloquer les Marchés Privés pour les Investisseurs Particuliers

About the author

The article was written in December 2025 by Emmanuel CYROT (ESSEC Business School, Global Bachelor in Business Administration (GBBA), 2021-2026).

▶ Read all articles by Emmanuel CYROT.

How to stay up to date with financial news

December 12, 2025 by Zineb ARAQI

In this article, Zineb ARAQI (ESSEC Business School, Global Bachelor in Business Administration (GBBA), 2021-2025) shares advice about how to keep up with financial news for all aspiring finance professionals.

Why It Is Important to Stay Up to Date with Financial News

Financial news is the lens through which we understand how the world’s economies, companies, and markets evolve. Every major financial decision from central bank rate changes to corporate mergers or geopolitical shocks has immediate and long-term effects on asset prices and business trends. Staying informed allows you to interpret these signals early, understand their implications, and make better strategic decisions.

For aspiring finance professionals, this habit is essential. Recruiters expect candidates to follow markets closely and to demonstrate an ability to connect recent news to broader macroeconomic themes. Whether you are preparing for interviews in investment banking, private equity, asset management, consulting, or fintech, the ability to discuss current events intelligently can significantly strengthen your profile. Beyond interviews, developing strong market awareness helps you stand out in internships and early career roles, where teams rely on juniors who can quickly contextualize news and anticipate its impact on clients, sectors, or investment strategies.

How to Stay Up to Date with Financial News

A practical guide to staying informed in fast-moving markets

Why Staying Informed Matters

Financial markets evolve at incredible speed. A policy announcement, an earnings release, or a geopolitical event can move markets within minutes, shaping investment decisions, risk perception, and overall confidence. Staying updated is essential for investors, analysts, entrepreneurs, and business leaders, and it is especially critical for students who aspire to build a career in finance.

For future financiers, staying informed is non-negotiable. Whether you aim to work in investment banking, private equity, asset management, consulting, or sustainable finance, you will be expected to understand market trends, macroeconomic developments, and sector dynamics. Interviewers routinely test candidates on their financial awareness, and teams rely on juniors who can connect the dots between daily news and strategic decisions. Developing this habit early provides a strong competitive advantage and prepares you for the fast-paced environment of modern finance.

Use Traditional Media

Newspapers

Established financial newspapers remain among the most reliable sources for in-depth reporting, analysis, and opinion pieces.

Financial Times – excellent global coverage and ESG/sustainable finance insights.
The Wall Street Journal – strong focus on U.S. markets and corporate news.
Les Échos – the go-to source for French and European economic updates.

Digital Tools & Apps

Digital platforms offer free and accessible ways to follow markets on the go.

Google Finance – clean dashboards for watchlists and news.
Yahoo Finance – good for company pages and basic charts.
Investing.com – economic calendars, real-time quotes, and commodity data.
MarketWatch – accessible journalism and market commentary.

Subscribe to Quality Newsletters

Newsletters provide concise daily updates that fit easily into your morning routine.

Bloomberg – “Five Things to Start Your Day” – short, sharp, and market-focused.
FT Moral Money – For sustainable finance and ESG trends.
Morning Brew (Markets) – fun and accessible, it is a great source for beginners.
The Economist Weekly – broader macro and geopolitical analysis.

Listen to Podcasts & Watch Videos

Audio and video formats are perfect for learning while commuting, cooking, or working out.

Bloomberg Surveillance – expert interviews and macroeconomic analysis.
FT News Briefing – a concise summary of global business news.
Planet Money (NPR) – accessible, entertaining explanations of complex topics.
CNBC Squawk – real-time market commentary.

Follow Trusted Sources on Social Media

Social media delivers information in real time, but the key is following verified and credible accounts.

Twitter/X: Bloomberg Markets, Reuters Business, Holger Zschaepitz, Morgan Stanley Research.
LinkedIn: Economists, asset managers, and thought leaders.
YouTube: Bloomberg, WSJ, CFA Institute, finance educators.

The Jamie Dimon Way: How a Top CEO Stays Informed

One of the most respected figures in global finance, Jamie Dimon, CEO of JPMorgan Chase has built a disciplined routine around staying informed. His approach is simple but extremely rigorous: every morning, he wakes up before 5 a.m. and reads multiple newspapers in a precise order to get a balanced, global perspective.

Dimon has shared in interviews that he starts with The Washington Post and The New York Times to understand national headlines and political dynamics. He then moves to The Wall Street Journal for corporate and market-focused coverage. Finally, he reads the Financial Times for a more international and less U.S.-centric viewpoint. On weekends, he adds The Economist, which he considers essential for deep macroeconomic and geopolitical insights.

Beyond what he reads, Dimon’s philosophy is equally revealing. He avoids distractions, rarely checks his phone during the day, and refuses to let notifications drive his attention. Instead, he prioritizes thoughtful reading, focused work, and long-term thinking.

For students and young professionals aiming for a career in finance, Dimon’s approach offers a clear lesson: serious finance careers require serious information habits. The ability to understand market movements, connect events across regions, and think strategically starts with a consistent, deliberate daily routine grounded in high-quality, diverse sources of information.

How I Stay Informed

As a finance student preparing for interviews, case studies, and technical assessments, staying informed quickly became a daily habit rather than an academic requirement. During my time at ESSEC, and later through interviews for finance roles, I realized that strong market awareness often makes the difference between a good candidate and an outstanding one.

To keep up, every morning, I scan the Financial Times to get a first sense of macroeconomic movements, overnight market performance, and key corporate stories. I then check Yahoo Finance to review charts, earnings updates, and sector-specific developments. Throughout the day, I rely on newsletters such as Bloomberg’s “Five Things to Start Your Day” and FT Moral Money for ESG trends, which are particularly relevant to my academic and professional interests.

My commute has also become part of my learning routine. When I take the tube, I often listen to The Clark Howard Podcast, a show focused on personal finance, smart money habits, and consumer insights. Although it is not a markets podcast, it helps me better understand everyday financial decisions, interest rates, and economic trends from a practical perspective. It is one of the easiest ways to stay informed without feeling like I’m “studying,” and it keeps me grounded in real-world financial thinking even during busy weeks.

Before interviews, I also prepare short summaries on major themes such as inflation trends, geopolitical risks, and standout M&A deals. This practice not only helped me perform well during recruiting processes, but also strengthened my analytical thinking and confidence when discussing financial topics with professionals.

Staying informed, for me is about building intuition. Over time, this routine has helped me better understand how markets react, how narratives evolve, and how events connect across regions. It is a habit that continues to shape my education and my career aspirations in finance.

Conclusion

Staying up to date with financial news does not require hours of daily reading. With the right combination of traditional media, digital tools, and consistent habits, you can easily stay informed and understand the major trends shaping markets. Start small, be consistent, and over time you will build strong financial awareness that gives you a real edge in both academic and professional settings.

Useful resources

About the author

This article was written in December 2025 by Zineb ARAQI (ESSEC Business School, Global Bachelor in Business Administration (GBBA), 2021–2025).

▶ Read all articles by Zineb ARAQI.

My internship experience at HSBC

December 9, 2025 by Lang Chin SHIU

In this article, SHIU Lang Chin (ESSEC Business School, Global Bachelor in Business Administration (GBBA), 2024-2026) shares her professional experience at HSBC in Hong Kong.

About the company

HSBC (The Hongkong and Shanghai Banking Corporation) is one of the world’s largest banking and financial services organisations, serving millions of customers through Retail Banking, Wealth Management, Commercial Banking, Global Banking and Markets, and other specialised businesses.

In Hong Kong, HSBC plays a key role as a leading provider of corporate and investment banking, trade finance, and wealth management products, making it a central player in the regional and global financial system.

Logo of HSBC.

Source: the company.

My internship

During my internship in the Wealth and Personal Banking team in Hong Kong, I assisted with daily operations supporting client relationship managers and investment advisors. My work involved preparing client onboarding documents, updating records in the bank’s management system, and ensuring compliance with Know Your Customer (KYC) and internal policy requirements. I also helped compile client portfolio summaries, draft investment proposals, and conduct market research to support financial planning and investment recommendations.

Beyond these tasks, I gained exposure to a wide range of wealth management products including mutual funds, equity and bonds, structured products, and insurance solutions. I participated in internal meetings to observe how product specialists, compliance officers, and relationship managers collaborate to deliver integrated services for clients. Additionally, I contributed to the preparation of client presentations and market updates, which strengthened my understanding of how macroeconomic trends influence individual investment strategies.

My missions

My missions included supporting relationship managers and product managers with the preparation of client materials, such as simple financial summaries and presentation slides for internal and external meetings. I also assisted with internal reports, helped update client information in our internal systems, and observed calls and meetings to understand client needs and identify follow-up actions.

Required skills and knowledge

This internship required strong analytical skills, attention to detail and a solid foundation in finance and banking concepts, such as understanding financial statements, basic risk metrics and common banking products. At the same time, soft skills such as communication, time management, and professionalism were crucial, as I had to collaborate with different team members, handle confidential information carefully, and deliver work under tight deadlines.

What I learned

Through this experience, I learned how front-office and support teams interact to serve clients and manage risks within a large universal bank. I developed a more concrete understanding of how theoretical concepts from corporate finance and financial markets are applied in real transactions and client discussions, and I improved my ability to structure quantitative information clearly in reports.

Financial concepts related to my internship

Three financial concepts related to my internship: relationship banking, risk-return and capital allocation, and regulation and compliance. These concepts help explain how my daily tasks fit into the broader functioning of the bank.

Relationship banking

Relationship banking refers to building long-term relationships with clients rather than focusing only on individual transactions. In practice, this means understanding clients’ businesses, industries and strategic priorities to provide tailored solutions over time. By helping prepare client materials and following up on information requests, I contributed to the relationship-building process that supports client retention and opportunities.

Risk-return and capital allocation

Banks constantly balance risk and return when they grant loans, underwrite deals or hold assets on their balance sheet, subject to capital and liquidity constraints. Internal analyses, credit information, and financial ratios are used to assess whether the expected return of a client or transaction justifies the associated risk and capital consumption. My exposure to simple financial analysis and internal reporting showed how data and models support these risk-return decisions.

Regulation and compliance

Banking is a highly regulated industry, with strict rules on capital, liquidity, anti-money laundering (AML), know-your-customer (KYC) and conduct. Many processes in the bank, from onboarding to reporting and product approval, are shaped by these regulatory requirements. During my internship, I observed how documentation, data accuracy, and internal controls are integrated into daily workflows to ensure that business growth aligns with regulatory expectations and internal risk appetite.

Why should I be interested in this post?

An internship at HSBC offers exposure to a global banking environment, sophisticated financial products and real client situations. It also provides a strong platform to develop quantitative skills, professional communication and an understanding of how large financial institutions create value while managing complex risks—skills that are highly transferable to careers in banking, consulting, corporate finance and risk management.

Useful resources

HSBC – Official website

HSBC Internships for students and graduates

HSBC Financial Regulation

About the author

The article was written in December 2025 by SHIU Lang Chin (ESSEC Business School, Global Bachelor in Business Administration (GBBA), 2024-2026).

▶ Read all articles by SHIU Lang Chin.

My Apprenticeship Experience at Capgemini Invent

December 9, 2025 by Zineb ARAQI

In this article, Zineb ARAQI (ESSEC Business School, Global Bachelor in Business Administration (GBBA), 2021-2025) shares her experience as an apprentice at Capgemini Invent within the Data & AI practice for Financial Services, where she contributed to major digital transformation programs across global banking institutions.

About the company

Capgemini Invent is the digital innovation, design and transformation brand of the Capgemini Group. Created in 2018, it combines strategy, technology, data, and creative design to help organizations reinvent their business models. Capgemini Invent operates in more than 30 countries and brings together over 10,000 consultants, data scientists, designers, and industry experts.

Capgemini Invent works at the intersection of strategy and execution, supporting clients through their end-to-end transformation journeys. Its expertise spans digital transformation, artificial intelligence, cloud modernization, sustainability strategy, customer experience, and data-driven operating models.

Within the wider Capgemini Group (over 340,000 employees worldwide), Invent plays a critical role in bridging management consulting with advanced technological execution. This unique positioning allows consultants to work on strategic topics while staying close to the technical realities of implementation, particularly in fast-evolving domains like AI, data governance, and digital banking.

Logo of Capgemini.
Logo Capgemini
Source: Capgemini Invent

About the department: Data & AI for Financial Services

I completed my apprenticeship within the Data & AI Financial Services practice, the division supporting major French and international banks in their data strategy and AI-driven transformation. This department works closely with Chief Data Officers (CDOs), Chief Analytics Officers, and executive committees to design, deploy, and govern enterprise-wide data architectures and AI solutions.

During my apprenticeship, I worked on strategic missions covering Europe, Middle East, and Africa, the Americas, and Asia-Pacific. Our team addressed high-impact topics such as data governance, regulatory compliance and Environmental, Social, and Governance reporting, customer intelligence, risk modelling, AI use-case acceleration, cloud migration, and the operationalization of large-scale data platforms. The practice serves flagship clients across retail banking, corporate & investment banking, insurance, and payments.

My apprenticeship experience at Capgemini Invent

My Missions

Throughout my apprenticeship, I contributed to large digital transformation programs for top French banks. My work spanned across all regions, EMEA, the Americas, and Asia reflecting the global scale of modern banking operations and the cross-regional governance challenges faced by CDOs.

My missions included:

Supporting Chief Data Officers in defining and implementing enterprise-wide data governance frameworks (metadata, lineage, quality, operating models).
Designing AI use-case portfolios, including prioritization matrices, feasibility assessments, and Return on Investment evaluations for retail and corporate banking.
Analyzing cross-regional data issues across APAC, the Americas, and EMEA to harmonize data standards and reporting structures.
Contributing to ESG & sustainable finance reporting, helping banks adapt to emerging CSRD (the EU’s new mandatory sustainability reporting directive), TNFD (the global framework for nature-related risk disclosures) and ESRS (the detailed European sustainability reporting standards) requirements using improved data pipelines.
Supporting cloud transformation initiatives by assessing data migration readiness and defining new operating models for data platforms.
Supporting cloud transformation initiatives by assessing data migration readiness and defining new operating models for data platforms.
Building dashboards and analytics tools using SQL, PowerBI, and Python to transform raw data into clear insights that support risk, compliance, and business teams in their decision-making.

These projects exposed me to the complexity of financial data ecosystems, the challenges of legacy infrastructures, and the role of AI in reshaping operational models at scale.

Required skills and knowledge

Working at the intersection of consulting, data governance, and financial services required a combination of analytical, technical, and communication skills. On the technical side, I relied on knowledge of banking business lines (retail, Corporate & Investment Banking, payments), data modelling fundamentals, SQL, cloud concepts, and AI/ML logic. Understanding regulatory frameworks and risk data aggregation standards was essential, especially when advising CDOs on compliance or data lineage workflows.

Soft skills were equally important: client communication, structured problem-solving, stakeholder management, and the ability to translate complex data topics into actionable recommendations. Working across multiple regions strengthened my adaptability and cross-cultural communication, as I collaborated with teams in Europe, the U.S., and Asia.

What I learned

This apprenticeship taught me how central data has become to the competitiveness and resilience of financial institutions. I learned how banks leverage data to enhance customer experience, reduce risk, improve compliance, and accelerate digital transformation. I also gained firsthand exposure to how global banks structure their operating models, from governance to platforms to analytics, and how AI can be responsibly integrated into decision-making processes.

Most importantly, working with CDO organizations helped me understand the strategic importance of data leadership and the challenges of transforming legacy institutions into data-driven organizations. This experience reinforced my interest in financial technology, analytics, and sustainable finance.

Business concepts related to my internship

I present below three financial, economic, and management concepts related to my apprenticeship. These concepts illustrate how data strategy, regulatory expectations, and AI-driven transformation shape the operating models of large financial institutions and how my work experience aligned with these challenges.

Data Governance and Regulatory Compliance (BCBS 239, CSRD, ESRS)

During my missions, the concept of data governance was central. Financial institutions operate under strict regulatory expectations such as BCBS 239 (risk data aggregation), CSRD (corporate sustainability reporting), and ESRS (European sustainability standards). These frameworks require banks to demonstrate full control of their data including lineage, quality, documentation, accessibility in order to produce reliable regulatory reports. My role consisted in helping banking groups structure governance models, build data quality controls, and harmonize data definitions across regions. This concept is at the heart of banking transformation, as regulatory pressure and data modernization are now inseparable.

AI Use-Case Prioritization and ROI Evaluation

A second concept I applied throughout my apprenticeship is the prioritization of AI use-cases based on business value, feasibility, and risk. Banks often have dozens of potential AI initiatives, but only a fraction deliver measurable Return on Investment (ROI). My work involved constructing prioritization matrices, evaluating data readiness, estimating financial impact, and supporting executive committees in building realistic AI roadmaps. This required balancing quantitative evaluation (cost savings, efficiency gains) with qualitative factors (regulatory risk, bias mitigation, ethical constraints). This concept is fundamental to ensuring that AI programs are scalable, responsible, and aligned with strategic objectives.

Operating Model Transformation for Data Platforms and Cloud Migration

The third concept closely linked to my missions is the transformation of operating models for data platforms migrating to the cloud. Banks are progressively replacing legacy infrastructure with modern cloud-based architectures to improve scalability, reduce costs, and accelerate analytics capabilities. My work consisted in assessing migration readiness, defining roles and responsibilities, and designing new governance processes adapted to cloud environments. This concept is essential because technology alone cannot transform an organization, it must be accompanied by clear processes, change management, and redesigned workflows.

About the author

This article was written in December 2025 by Zineb ARAQI (ESSEC Business School, Global Bachelor in Business Administration (GBBA), 2021–2025).

▶ Read all articles by Zineb ARAQI.

My apprenticeship experience as a Junior Financial Auditor at EY

December 9, 2025 by Iris ORHAND

In this article, Iris ORHAND (ESSEC Business School, Global Bachelor in Business Administration (GBBA), 2021-2026) shares her professional experience as a Junior Financial Auditor at Ernst & Young.

About the company

EY (Ernst & Young) is one of the “Big Four” professional services firms, supporting companies across audit, consulting, strategy, tax, and transactions. In audit, EY’s mission is to provide reasonable assurance on financial statements, bringing together financial analysis, an understanding of risks, internal control review, and clear, structured documentation to back audit opinions and reinforce stakeholder trust. Today, the firm brings together nearly 400,000 professionals across more than 150 countries and generated around USD 51.2 billion in revenue in its 2024 fiscal year.

Logo of EY

Source: the company.

My internship

In 2024, I joined EY in Paris La Défense as a Junior Financial Auditor on a 12-month apprenticeship. This experience gave me hands-on exposure to the audit cycle, from planning to fieldwork to final deliverables, and helped me understand how auditors balance technical rigor, deadlines, and client interaction.

My missions

Over the year, I worked on the financial analysis of seven companies, ranging from €10 million to €1.5 billion in revenue. I was part of a business unit focused on associations and the public sector, which allowed me to discover organizations with very different missions and financial setups. My largest and longest engagement was with Universal, where I really had the chance to follow a full audit cycle and understand how such a large structure operates. On a daily basis, I reviewed financial statements like the P&L, balance sheet and cash flow, identified unusual trends, dug into variances, and tried to understand the story behind the numbers. I also prepared financial analyses and draft audit conclusions for internal teams as well as for client discussions.

Even though my main focus was on the non-profit and public sector, EY gives motivated juniors the chance to work with other business units from time to time, and I really wanted to take advantage of that. Thanks to this, I was able to join a mission in the defense sector for Thalès, which was a completely different environment and pushed me to adapt quickly and broaden my understanding of industry specific risks.

Throughout the year, I relied a lot on audit tools and automation, using audit software, macros and advanced Excel to structure testing, make our work more traceable, and gain efficiency during busy periods. I was also involved in internal control assessments and risk management topics, which helped me understand how processes and day to day workflows can directly impact the reliability of financial reporting. I also participated in reviewing management forecasts, comparing them with historical results, challenging assumptions and pointing out areas where further evidence was needed. Overall, this experience helped me build a strong analytical mindset and gave me a much clearer view of how different types of organizations operate behind their financial statements.

Required skills and knowledge

This role required a combination of both hard and soft skills, and I quickly realized how important it was to balance the two. On the technical side, I relied a lot on advanced Excel, basic automation and macro logic, and a structured approach to financial analysis. A solid understanding of accounting fundamentals was essential, as well as developing strong documentation habits to keep our work clear, traceable, and easy for reviewers to follow. But beyond the technical knowledge, soft skills mattered just as much, if not more. Attention to detail was key, as was maintaining a sense of professional skepticism without falling into mistrust. Clear and calm communication helped a lot, especially when dealing with tight deadlines or last-minute requests during busy periods. I also learned how important it is to be pedagogical and professional with clients. Sometimes, audit questions can make clients feel like they are being challenged or judged, even when that’s not the intention. Taking the time to explain why we need certain information, reassuring them, and keeping the conversation constructive made the whole process smoother and helped build trust. Overall, this mix of technical rigor and human sensitivity was at the core of the role.

What I learned

This apprenticeship strengthened my ability to turn raw financial data into meaningful audit insights. Over time, I became much more comfortable linking business reality to accounting outcomes, understanding why a number moved, what it implied, and what kind of evidence was needed to support it. I also learned to think with a risk-based mindset, focusing my attention on the areas that had the greatest impact on the reliability of the financial statements. Finally, working under tight deadlines taught me how to stay organized and efficient while still maintaining high quality standards and keeping my work clear and ready for review. This combination of technical understanding, prioritization, and discipline is something I really developed throughout the year.

Financial concepts related to my internship

I present below three financial concepts related to my internship: financial statement analysis, internal control and audit risk, and forecasts, assumptions and professional skepticism.

Financial statement analysis

Audit work involves understanding not only the numbers, but also the story behind them and the operational reality that drives financial performance. Financial statement analysis played a central role throughout my apprenticeship. Trend analysis, ratio analysis, and variance explanations were essential tools to detect anomalies, identify risks, and guide the direction of our testing. By comparing periods, analyzing shifts in key indicators, and questioning unusual movements, I learned to form a more accurate picture of how an organisation truly operates.

This analytical process goes far beyond reading figures. It requires understanding the client’s business model, the context behind certain decisions, and the internal processes that ultimately shape the financial statements. Through this approach, I learned to prioritize the most sensitive areas, challenge assumptions that did not align with expectations, and connect accounting outcomes to the real functioning of the organisation. This ability to translate raw numbers into meaningful insights became one of the most valuable skills I developed during the apprenticeship.

Internal control and audit risk

Internal control quality plays a key role in shaping audit strategy. Throughout my apprenticeship, I saw how understanding a client’s processes, identifying where the risks lie, and evaluating the controls in place helps determine the likelihood of misstatements. When controls are strong and consistently applied, the risk is lower, which allows auditors to adjust their testing. When controls are weak or not operating as intended, the audit must be more detailed and rely on additional evidence.

In practice, this involved mapping processes, speaking with client teams, and observing how transactions were handled on a daily basis. It also required professional judgment to identify the areas where real vulnerabilities might exist. This experience helped me understand how internal control and audit risk are linked, and how this relationship influences the entire audit approach.

Forecasts, assumptions and professional skepticism

Comparing forecasts with historical figures is a practical way to assess the reasonableness of management’s assumptions, whether they relate to growth, margins, or cash generation. This exercise helps identify when projections are aligned with past performance and market dynamics, and when they seem overly optimistic or require stronger supporting evidence. It is also a direct application of professional skepticism, since the auditor must question the logic behind the assumptions without falling into mistrust. Over time, this analysis strengthens judgment and helps determine what is reasonable, what needs to be challenged, and where additional documentation or explanations are necessary.

Why should I be interested in this post?

This experience is especially valuable for anyone interested in audit, accounting, corporate finance, risk, or advisory. It gave me a strong understanding of financial statements, but also taught me discipline, structure, and a more analytical way of thinking. Throughout the year, I learned how to interpret numbers in a real-life context, how to stay organised under pressure, and how to communicate clearly with both clients and team members. What I liked is that these skills are not limited to audit. They can be applied in many areas such as transaction services, FP&A, or even banking. Being able to analyze financial data, understand risks, and form a well-reasoned judgment is useful in almost any finance role, which makes this apprenticeship a great foundation for whatever comes next in a finance-related career.

Useful resources

EY Official website

L’Expert-comptable.com La méthodologie d’audit : Les assertions

Wikipedia EY (entreprise)

Wikipedia Big Four (audit et conseil)

About the author

The article was written in December 2025 by Iris ORHAND (ESSEC Business School, Global Bachelor in Business Administration (GBBA), 2021-2026).

▶ Read all articles by Iris ORHAND

The four most dangerous words in investing are, it’s different this time.

December 9, 2025 by Hadrien PUCHE

Financial markets are filled with stories of bubbles, crashes, and periods of extreme optimism or pessimism. Yet human nature remains surprisingly constant, as we are prone to believe that “this time is different.” Sir John Templeton’s famous quote reminds investors that historical patterns, lessons, and cautionary tales are often ignored in the face of conviction, novelty, or excitement.

In this article, Hadrien Puche (ESSEC, Grande École, Master in Management, 2023 / 2027) comments on this quote, exploring why believing that history will not repeat itself can be one of the most dangerous biases in investing.

About Sir John Templeton

Sir John Templeton

Source: John Templeton Foundation

Sir John Templeton was a legendary investor and philanthropist, renowned for his disciplined approach to value investing, a strategy that involves seeking out companies, markets or assets that are deeply undervalued compared to their true long term potential. Rather than following the crowds, value investors analyze the fundamentals of companies (earnings, balance sheets, management…) to make investment decisions.

Born in 1912 in the United States, he built a global investment career by seeking opportunities where others saw only risk. In 1939, at the outbreak of WW2, he borrowed money to buy shares when the market was at its lowest, including shares in 34 bankrupted companies, only 4 of which turned out to be worthless. In 1954, he founded the Templeton Growth Fund, a diversified mutual fund that sought bargains in depressed markets around the world.

Although the exact origin of this quote is unclear, it reflects Templeton’s belief that market cycles tend to repeat themselves. Investors often dismiss historical lessons when conditions seem unprecedented. In periods of optimism, they believe innovation or policy changes make downturns impossible. But Templeton argued this mindset is even more dangerous during crises: each time recession, war or financial turmoil hits, people insist the situation is entirely different from past downturns and ignore proven patterns of recovery. This leads to panic selling and missed opportunities at the moment of greatest long term value. Markets may change, but human psychology and systemic risks tend to repeat in predictable ways.

Analysis of the quote

At the heart of Templeton’s statement lies a timeless observation about human behavior. Investors frequently convince themselves that new technologies, policies, or financial instruments render past risks irrelevant. They see bubbles in real time but rationalize them as unique and unrepeatable events.

This attitude is perilous. By assuming “it is different this time,” investors often take excessive risk, neglect proper analysis, and overvalue assets. History shows that the same patterns, including leverage, speculation, overconfidence, and panic, tend to recur regardless of the era or instrument. The global financial crisis of 2008, the dot com bubble of 2000, and the 1929 crash illustrate the consequences of ignoring these lessons.

Templeton’s advice is simple yet profound. Treat each investment with humility, respect historical precedents, and avoid the hubris of believing novelty exempts you from risk. Recognizing that “this time” may not be different is not a rejection of innovation or change. It is an acknowledgment of patterns, limits, and the laws of risk.

Economic and financial concepts related to the quote

Let’s go into more details over three interesting financial concepts that are linked to this quote.

Market cyclicity

Financial markets naturally tend to move in cycles. Bull markets are followed by corrections; recessions are followed by recoveries. This inherent cyclicity explains why Templeton’s warning is so critical: periods of euphoria are often followed by downturns regardless of how unique the circumstances appear.

This cyclical pattern is most vividly illustrated by the formation of financial bubbles; situations where asset prices rise far above their intrinsic value due to speculation and excessive optimism. Investors frequently underestimate these cycles when past trends have been unusually profitable. For example, during the dot com boom, many believed that technology’s growth would render traditional valuation metrics irrelevant. The result was a speculative bubble followed by a sharp market correction.

As documented by economist Charles P. Kindleberger in his classic work, Manias, Panics, and Crashes: A History of Financial Crises, these bubbles follow a predictable, recurring pattern.

Stages of a market bubble

He argued that financial crises typically progress through phases of displacement, boom, euphoria, and eventually distress and panic. By ignoring history and assuming that novelty exempts them from these fundamental laws, investors risk participating in the formation and painful bursting of the bubble.

Understanding market cyclicity encourages investors to remain vigilant, diversify their holdings, and respect the natural flow of markets even when conditions seem unprecedented.

The Tranquility Paradox and Minsky’s Hypothesis

The tranquility paradox describes a simple but dangerous human habit: when the economy feels stable for long enough, we start believing that this stability will last forever. Rising markets, low volatility, and strong indicators give investors a sense of comfort. They begin to assume that risk has disappeared, that the system is safer than ever, and that the future will look just like the present.

This mindset is exactly what Templeton warned against, and it sits at the center of economist Hyman P. Minsky’s Financial Instability Hypothesis. Minsky’s core idea is counterintuitive: periods of stability create the conditions for instability. In other words, stability is not the end of risk, it’s the beginning of the next one.

The graph below illustrates this dynamic. When things look calm for long enough, investors slowly shift from safe financing to riskier forms, without even realizing it.

Graph of the Minsky moment

Minsky identified three stages:

Hedge financing, the safe zone: Cash flow covers both interest and principal.
Speculative financing, the risky zone: Cash flow covers interest only; principal is rolled over.
Ponzi financing, the danger zone: Cash flow covers neither interest nor principal. Survival depends on continuous borrowing or rising asset prices.

Over time, more and more activity moves into those speculative and Ponzi stages, pushing the system closer to what Minsky called a Minsky Moment, the sudden realization that debts can’t be serviced, asset values drop, confidence collapses, and panic selling begins.

This is the heart of the paradox: calm markets create overconfidence, overconfidence leads to excessive risk taking, and excessive risk taking triggers the crisis. Understanding this pattern helps investors maintain discipline, stay cautious during good times, and avoid falling for the seductive idea that “this time is different.”

Historical bias in personal finance

Templeton’s warning is not limited to market professionals; personal finance and long term investing are equally susceptible to the belief that history will not repeat itself. This risk is rooted in historical bias, a cognitive shortcut where many individuals assume that high past returns on stock indexes, real estate, or other assets will continue indefinitely, often ignoring the possibility of lower future growth or structural changes in the economy.

This bias, a form of extrapolation bias, can be highly dangerous in retirement planning, risk allocation, and portfolio construction. Relying solely on historical equity returns may lead to severe overestimation of future wealth and underestimation of risks during periods of low growth or inflation.

As articulated by economist Burton Malkiel in A Random Walk Down Wall Street, the historical record provides valuable context, but it must not be treated as a definitive forecast. Malkiel’s work supports the idea that, in an efficient market, all available information is already reflected in current prices, meaning past price movements hold no predictive power for the future.

Therefore, Templeton encourages reflection: a disciplined investor balances cautious optimism about the future with a realistic understanding of historical realities, recognizing that past performance of market indexes does not guarantee future results.

My opinion about this quote

Templeton’s insight is essential for both students and seasoned professionals. It serves as a reminder that neither euphoria nor fear should dictate investment decisions. Markets will always fluctuate, and history often rhymes if it does not repeat exactly.

However, it is also true that sometimes conditions are different, and excessive caution can prevent individuals from capitalizing on genuine opportunities. Innovation, technological change, and macroeconomic shifts can justify deviations from historical trends. The challenge lies in distinguishing between real novelty and wishful thinking.

In personal finance, this principle is particularly relevant. Many investors assume that past returns on broad indexes such as the S&P 500 are a reliable guide for the future. Structural changes, low interest rates, and demographic shifts may produce different outcomes.

Market performance of the SP500 over 30 years and different crises

Although global stock markets have historically recovered after crises, this cannot be taken as definitive evidence that they will always do so in the future.

Balancing historical awareness with flexibility and critical thinking is the essence of sound investing.

Why should you be interested in this post?

Templeton’s warning is not only a lesson in investing. It is a lesson of humility, discipline, and critical thinking. Believing “this time is different” can blind both students and professionals to risks, patterns, and opportunities. Studying history, understanding cycles, and acknowledging psychological biases improves decision making in finance and beyond.

Whether you are building a portfolio, analyzing market trends, or planning for the future, this insight encourages you to respect the lessons of the past while remaining vigilant and adaptable.

Useful resources

Investment Wisdom & Discipline

These resources provide practical advice on long term, non emotional investing and avoiding market fads.

Templeton, John. The Templeton Plan.
Malkiel, Burton G. A Random Walk Down Wall Street.

History of Financial Crises

These essential books and papers explain why markets crash and the patterns those crises follow.

Kindleberger, Charles P. (1978). Manias, Panics, and Crashes: A History of Financial Crises.
Minsky, Hyman P. (1992). The Financial Instability Hypothesis, Working Paper No. 74, Jerome Levy Economics Institute.

Market Psychology & Valuation

These sources examine the role of human behavior, psychology, and valuation issues in speculative bubbles.

Shiller, Robert. Irrational Exuberance.
Blanchard, Olivier J., and Mark W. Watson. (1982). “Bubbles, Rational Expectations and Financial Markets.”
Tirole, Jean. (1982). On the Possibility of Speculation under Rational Expectations, Econometrica, 50(5) 1163–1181.

About the Author

This article was written in 2025 by Hadrien Puche (ESSEC, Grande École, Master in Management 2023 / 2027)

About the company

My internship

My missions

Required skills and knowledge

What I learned

Financial concepts related to my internship

Liquidity management and forecasting

Rolling planning and forecasting

Foreign exchange risk management

Why should I be interested in this post?

Related posts on the SimTrade blog

Profesional experiences

Financial techniques

Useful resources

Business

Academic articles and books

About the author

About the company

My internship

My missions

Required skills and knowledge

What I learned

Financial and business concepts related to my internship

Investment horizon

Qualitative analysis through on-site due diligence

Importance of qualitative relationships with stakeholders

Why should I be interested in this post?

Related posts on the SimTrade blog

About the author

Why this is important

The DCF model: measuring intrinsic value

Strengths of the DCF

Weaknesses of the DCF

Multiples valuation: estimating relative value

Implicit assumptions behind multiples

Strengths of multiples

Weaknesses of multiples

When to use them and the “football field”

Conclusion

To sum up…

Why should I be interested in this post?

Related posts on the SimTrade blog

Useful resources

About the author

Introduction

The audit risk model: why “risk-based” makes sense

Materiality: focusing on what matters

Assertions: translating accounting lines into “what could be wrong”

From risk to procedures: the core workflow

Concrete examples: what we do in practice

Conclusion

Why should I be interested in this post?

Related posts on the SimTrade blog

Professional experiences

Useful resources

About the author

About the company

My internship

My missions

Required skills and knowledge

What I learned

Financial and business concepts related to my internship

Private market fundraising and LP relations

Product positioning and information asymmetry in private markets

Competitive dynamics in European private markets

Why should I be interested in this post?

Related posts on the SimTrade blog

Useful resources

About the author

Introduction

Why is networking important in finance?

What are the common mistakes?

The method.

Conclusion

Related posts on the SimTrade blog

Useful resources

About the author

About the company

My internship

My missions