Financial Statement Analysis Phases

Financial analysis is the process of interpreting and evaluating a company’s performance and position in the context of its economic environment. Analysts use financial analysis to make investment decisions and recommendations.

As a generic term, the financial statement analysis framework describes the process of assessing financial statements, supplemental information, and other sources of information. Essentially, the framework helps analysts draw conclusions and make informed recommendations, such as whether to invest in a company or extend a loan.

Phases Involved in the Financial Statement Analysis Framework

The financial statement analysis framework involves six phases. These include:

Phase 1: Articulate the Purpose and Context of the Analysis

Articulating the purpose of the analysis in financial statement analysis is important due to the variety of techniques and the significant amount of data involved. Some analytical tasks are straightforward, with a clear purpose, making it easier for the analyst to proceed. For instance, a periodic credit review of an investment-grade debt portfolio is governed by established institutional norms.

For other analytical tasks, defining the purpose involves decisions about the approach, tools, data sources, reporting format, and the importance of various aspects of the analysis.

When dealing with extensive data, less experienced analysts might be tempted to calculate ratios without considering their relevance to the decision at hand. It is advisable to resist this and focus on pertinent calculations. Questions to consider include the following: What questions will the completed calculations and ratios answer? What decisions will the answers support?

Defining the contact of the analysis involves answering questions such as: Who is the intended audience? What is the deliverable, such as a final report with conclusions and recommendations? What is the timeline? What resources and constraints affect the analysis? Institutional standards may also predefine the context.

Once the purpose and context are clarified, the analyst should compile specific questions the analysis will address.

The sources of data at this stage include:

• The specific role of the analyst, whether it involves assessing an equity or debt investment or assigning a credit rating.
• Interaction with clients or supervisors to understand their particular needs and concerns.
• Adherence to institutional guidelines for creating specific work products.

The output from this phase includes:

• Timetable and proposed budget.
• Nature and content of the expected report.
•  A list of written or unwritten questions to be answered.
• The stated objective of the analysis.

Phase 2: Collect Data

Next, the analyst gathers the necessary information to address the specific questions. A crucial aspect of this phase is understanding the target company’s business model, financial performance, and financial position, including trends over time and in comparison to peer companies.

In some cases, financial statement data alone may suffice. For example, when screening numerous companies to identify those with a minimum level of historical profitability or sales growth. However, additional information is required to answer more complex questions, such as why and how one company outperformed or underperformed its competitors.

Additionally, understanding the economic and industry context is essential to grasping the environment in which the company operates. Analysts often use a top-down approach, first gaining insight into the issuer’s macroeconomic environment, including growth prospects and inflation. They then analyze the industry in which the company operates, considering the anticipated macroeconomic conditions. Finally, they assess the company’s prospects based on the expected industry and macroeconomic environments.

Note that past company data provide a basis for statistical predictions when forecasting a company’s future earnings growth. However, a thorough understanding of economic and industry conditions can enhance the accuracy of these forecasts.

The sources of information at this phase include:

• Financial statements, other financial data, questionnaires, and industry or economic data.
• Company site visits.
• Discussions with issuer investor relations, management, suppliers, customers, competitors, and company or industry experts.

At this phase, the analysts should be able to produce output such as:

• Completed questionnaires where applicable.
• Financial statements and other quantitative data structures in a consumable form.

Phase 3: Process Data

At this stage, a thorough financial analysis may include:

• Reviewing and assessing the financial results of each company under analysis involves understanding factors that could affect comparability, such as differences in business models and tax jurisdictions.
• Making necessary adjustments to the financial statements or employing alternative measures to facilitate comparison.
• Preparing or gathering common-size financial statement data and financial ratios.

Phase 4: Analyze and Interpret the Data

The analyst assesses the input data and the data processed in phase 3. The analyst should be able to interpret the analysis’ output and use it to support a conclusion or recommendation. The results from this phase include analytical results, forecasts, and valuations.

Phase 5: Develop and Communicate Conclusions and Recommendations

The analyst should communicate the conclusion and recommendations derived from the analysis in an appropriate format that answers the questions posed in Phase 1. The analyst uses analytical results and previous reports based on institutional guidelines to answer the questions in Phase 1.

The format of communicating conclusions or recommendations depends on the analytical objectives, institution guidelines, audience, and requirements of the regulatory agencies or professional standards. For instance example

Standard V(B) requires members and candidates to clearly communicate the key factors influencing their investment recommendation.

In summary, the source of data in this phase include:

• Analytical results and previous reports.
• Institutional guidelines for published reports.

On the other hand, this phase results in (output):

• Analytical report answering questions developed
  in Phase 1.
• Recommendation regarding the purpose of
  the analysis, such as whether to make an
  investment or extend credit.

Phase 6: Follow-up

Writing a report does not mean the end of the financial analysis framework. The analyst should perform periodic reviews to determine if the initial conclusions and recommendations still hold. This may require a periodic repeat of all the previous phases.

In summary, follow-up requires the use of information collected by regularly revisiting the previous phases to assess if adjustments to holdings or recommendations are needed. This may result in:

• Comparison of actual to expected results.
• Revised forecasts.
• Updated reports and recommendations.

Question

In which phase of the financial statement analysis framework would performing sensitivity analysis most likely be involved?

1. Follow-up.
2. Processing data.
3. Collecting input data.

Solution

The correct answer is B.

In the financial statement analysis framework, performing sensitivity analysis is most appropriately categorized under the phase of “Processing Data.” Sensitivity analysis is a technique used to assess the impact of changes in input variables on the outcome of a financial model. It involves varying key assumptions or parameters within the model to evaluate how these changes affect the results. This process is a part of data processing, as it involves manipulating and analyzing the collected data to gain deeper insights into the financial performance and risks associated with a company.

A is incorrect. “Follow-up” is concerned with reviewing the conclusions and recommendations of the analysis over time to ensure their continued validity. It does not involve the actual processing or analysis of data.
C is incorrect. “Collecting input data” involves gathering the necessary financial statements, economic data, and other relevant information required for the analysis. It precedes the processing of data and does not encompass the analytical techniques such as sensitivity analysis that are applied to the collected data.