What are some ways to ensure financial analysis is not biased or misleading? (2024)

Last updated on Mar 7, 2024

1

Use consistent and relevant data

2

Apply appropriate methods and assumptions

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Avoid confirmation and cognitive biases

4

Communicate clearly and transparently

5

Here’s what else to consider

Financial analysis is a crucial skill for corporate finance professionals, as it helps them evaluate the performance, value, and risk of a company or a project. However, financial analysis can also be subject to bias or misinterpretation, which can lead to poor decisions or misleading reports. How can you ensure that your financial analysis is not biased or misleading? Here are some ways to improve the quality and reliability of your financial analysis.

1 Use consistent and relevant data

One of the most important aspects of financial analysis is the data that you use to perform calculations, ratios, and projections. You should always use consistent and relevant data that reflects the current and historical situation of the company or the project. For example, you should use the same accounting standards, time periods, and currency conversions for all the data sources that you compare or analyze. You should also avoid using outdated or incomplete data that does not capture the recent changes or trends in the market or the industry.

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Shirley Bruna
L'analyse financière démarre d'une base d'informations non trompeuses (bilans publiés). Si l'analyse a vocation à servir de comparatif, les ratios d'observation doivent être les mêmes pour tous les audités. D'après moi, une bonne analyse doit également prendre en compte ce que j'appellerais les "softskills" de l'entreprise. Mais le sujet de fond, reste pour moi la raison pour laquelle on fait l'analyse et quoiqu'on en dise, c'est un biais cognitif. Quand j'avais l'intuition qu'il fallait investir, je mettais inconsciemment en valeur les ratios qui confirmaient mes croyances. Heureusement que j'étais chargée de clientèle Entreprise et pas Analyste crédit. Quoique ma connaissance du tissu économique m'a souvent donné raison...

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Data consistency is an under-rated and under-appreciated concept. Consistency has various dimensions: time period (annual vs quarterly), same calculation methodology, and firm size.For example, consider 2 firms, where one records depreciation in COGS, and the second records depreciation in "other expenses" below the operating income line. To calculate the EBITDA margin consistently, we would need to back out the depreciation (out of COGS) from the first firm's EBITDA margin calculation.
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2 Apply appropriate methods and assumptions

Another key factor in financial analysis is the methods and assumptions that you use to interpret the data and draw conclusions. You should always apply appropriate methods and assumptions that suit the purpose and context of your analysis. For example, you should use different valuation methods depending on the type and stage of the company or the project, such as discounted cash flow, multiples, or net present value. You should also state and justify the assumptions that you make, such as the discount rate, the growth rate, or the inflation rate, and test their sensitivity and impact on the results.

3 Avoid confirmation and cognitive biases

A common pitfall in financial analysis is the confirmation and cognitive biases that can influence your judgment and perception of the data and the outcomes. You should avoid confirmation bias, which is the tendency to seek or interpret information that confirms your pre-existing beliefs or expectations. You should also avoid cognitive biases, such as anchoring, framing, or overconfidence, which can affect how you process and evaluate information. To overcome these biases, you should seek diverse and objective sources of information, challenge your own assumptions and opinions, and solicit feedback and peer review from others.

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Stefano Passarello Accountant and Tax expert | Crypto Tax Specialist | CFO and Digital CFO Mentor | Co-founder of The Kapuhala Longevity Retreats
We all have biases, and it's important to be aware of them so that they don't cloud our judgment when we're doing financial analysis
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Vishvanath Krishnan Head of Finance | Finance Director | Financial Consultant | Fractional CFO | Chartered Accountant | Ex-PwC | Ex-Crescent Group
In my experience, starting your analysis with an end objective is likely to result in confirmation/cognitive bias. The focus should be on the process and not the result. It is important to get the basics right. Focus on data reliability, accuracy, and completeness. Ensure that the right analysis tools and techniques are used. Derive insights from the analysis. If any particular part of the data is distorting the output, cross-check the data and extend the analysis or exclude that data. Conduct a secondary analysis from a different perspective to confirm the insights derived or the conclusion reached. The insights must support a coherent story. Let the data drive the storytelling rather than the story driving the data and analysis.
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4 Communicate clearly and transparently

The final step in financial analysis is to communicate your findings and recommendations to your audience, whether it is your manager, your client, or your stakeholders. You should communicate clearly and transparently, using simple and accurate language, charts, and tables. You should also disclose the data sources, methods, assumptions, and limitations of your analysis, and explain how they affect your conclusions and implications. You should also acknowledge the uncertainties and risks involved in your analysis, and provide alternative scenarios or options for decision making.

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Tom Auden Finance Business Partner, Abbvie
Less is nearly always more when presenting data. Important to be concise, consider the audience and have the detail ready to support any points made. As analysts we'll tend towards data overkill so having this attitude helps to present clearly.
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Attributing data sources (for internal and external references) in footnotes works wonders for clear communication and transparency.Example for internal data: Forecast v3 approved 02/15/20x2Example for external data: 2022 Gartner Revenue Survey
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Some of the attributes which ensure that Financial Analysis is fair and not misleading areTransparentReliableError freeAnalysis with different perspectives
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Erich Runzer Corporate Finance / Finance Manager / Business Planning
Utiliza un lenguaje claro y preciso.Utiliza gráficos y tablas para visualizar la información.Revela las fuentes de datos y los métodos utilizados.Explica los supuestos y las limitaciones de tu análisis.Reconoce las incertidumbres y los riesgos asociados.

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5 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?

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Yogesh Sakunia Finance Expert| Trainer| Product Management
It's difficult to avoid biases at times. Getting the analysis done by multiple people or multiple people critically evaluating the analysis could be a good idea. Use of AI tools could also be helpful.
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Dilnoza Y. Financial Controller at Saunderson House, part of Rathbones Group Plc
If I have to short list, from my personal experience I have learned the following to be the most important:1. Use reliable data and methods: Base analysis on accurate, up-to-date data from credible sources. Apply consistent methodologies to maintain comparability.2. Verify assumptions and be objective: Critically evaluate assumptions. Ensure independence and objectivity, free from biases or conflicts.3. Transparency and continuous improvement: Document methods and limitations transparently. Encourage peer review and feedback. Continuously refine processes to improve quality.
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Cristian E. Economía, finanzas corporativas
Identificar la relación de causalidad y hacer una inferencia adecuada de los cambios en los resultados al manifestarse variaciones en el origen

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What are some ways to ensure financial analysis is not biased or misleading? (2024)

1

2

3

4

5

1 Use consistent and relevant data

2 Apply appropriate methods and assumptions

3 Avoid confirmation and cognitive biases

4 Communicate clearly and transparently

5 Here’s what else to consider

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