Analyzing and Interpreting Data

Analyzing and interpreting data is the most complex phase of the TAP. In this portion, examiners:

  • Break down and reassemble data
  • Relate individual parts of the data to the whole
  • Note trends, and
  • Identify risk

The examiner’s ability, judgment, experience, and skill all come into play in the process of analyzing and interpreting data. If examiners place too much emphasis on minor facts or ignore significant facts, they may arrive at erroneous conclusions. When in doubt about the significance of an issue, examiners seek guidance from a supervisor.

Placing Data into Perspective

Credit unions are often chartered with the primary goal of providing loans to members. Lending programs require that the credit union take a reasonable business risk, which results in earnings sufficient to maintain or build net worth. However, by emphasizing zero delinquency and loan losses, the examiner could diminish a primary reason for the credit union’s existence and decrease its income.

Discussions with management to obtain additional information not readily available will increase an examiner’s understanding of issues, and potentially change the assessment of risk. Information regarding the sponsor’s support and future viability, local economic conditions, and other relevant information are necessary to properly assess risk.

To effectively interpret data, examiners establish a hypothesis and test it using available data. For example, if the delinquency ratio is high and increasing, an examiner may establish a hypothesis that either underwriting is weak, that there is a collection problem, or both. The examiner must then test this hypothesis by reviewing loan files for underwriting weaknesses and collection policies and procedures for effectiveness.

Table of Contents

Analysis Methods

Examiners use a variety of methods to interpret data, including:

Financial Data Analysis

Financial data analysis includes the review of the component parts of a financial statement in relation to the whole. There are two important aspects of this analysis:

  1. Financial data analysis is static in the sense that the examiner reviews the composition of a financial statement as of a specific date.
  2. The credit union’s financial ratios should fall within reasonable parameters. Examiners may use various workpapers to assist in making this determination.

During financial data analysis, the examiner will review statistical data in the examination software. Examiners generally use the financial data in the examination software to evaluate and appraise a credit union’s overall financial condition. However, examiners may use other financial ratios to complete an analysis or to corroborate hypotheses the examiner reached after reviewing the financial data in the examination software. Examiners can also evaluate management’s financial vision by reviewing ratios against the credit union’s projected ratios in the budget or business plan.

When analyzing the financial and operational structure of a credit union, examiners:

  • Step back from exam details and individual ratios (and often from the computer)
  • Think about the big picture, how the various aspects of the credit union’s operations interact, and how individual ratios relate to each other
  • Assess management’s ability to identify, measure, monitor, and control current and future risk

Numerous ratios which measure a variety of credit union functions provide the basis for analysis. Examiners must understand these ratios both individually and as a group, depending on the type of analysis being performed. Some individual ratios may not provide an accurate picture without a review of the related ratios. For example, operating income, gross income, and provision expense are all related to return on average assets. Analyzing a group of ratios may help an examiner determine why a ratio falls outside a reasonable parameter.

To identify risk, examiners analyze financial data and the ratios developed from that data. For example, the return on average assets is a financial data analysis ratio developed from net income and assets.

During the financial analysis, the examiner may compare a credit union’s ratios to the same ratios of similar size credit unions. Examiners can create a customized query based on a variety of criteria using Call Report data. In addition, a credit union may identify its own peer group to be used for comparative analysis.

Examiners exercise caution when comparing credit union ratios to peer averages. Economic, geographic, and other differences between credit unions may result in misleading comparisons. Peer ratios do not represent standards or goals for the credit union to attain; they serve only as benchmarks. Therefore, examiners only use peer ratios as analysis points. Examiners should not recommend specific action based solely on a peer or national average.

Trend Analysis

Trend analysis involves comparing a financial data ratio to itself over several time periods to help determine the level and direction of risk in a credit union. This analysis is generally conducted on annualized data; however, seasonal fluctuations may warrant an examiner using a different trend analysis period.

Example of an Alternative Trend Analysis Period

Typically, a teacher credit union will accumulate shares through the school year, until school adjourns in late spring. At this time, shares could decline significantly as members make withdrawals. Such seasonal fluctuations can cause wide variances in a credit union’s net worth ratio, which can be taken into account by adopting a trend analysis period to compare net worth ratios year-over-year (March to March, for instance) as opposed to on an annualized basis.

Trend analysis lets examiners identify, question, and evaluate operational changes at a credit union. Examiners allocate extra time for trend analysis in credit unions that have recently implemented new strategies or programs. While these are not always an indication of higher risk, poorly implemented and controlled programs are often a contributing factor noted in MLRs.

Where new strategies or programs have been implemented by a credit union, examiners review recent and projected growth and compare actual results to projections. This can help an examiner identify unreasonable growth rates and determine if additional analysis is warranted. While trend analysis often requires looking back at prior ratios, it also serves as a valuable forecasting tool.

Reasonableness Analysis

When one or more ratios fall outside reasonable parameters, as defined by the NCUA or the examiner, a credit union’s financial condition may be at-risk, misstated, or otherwise suspect. Examiners analyze financial performance ratios to determine if they are reasonable. For example, the following unreasonable ratios would merit a reasonableness analysis:

  • The cost of funds exceeds the average stated share dividend rates
  • The yield on loans in a highly-loaned-out credit union with no reported delinquency equals less than half the stated loan rates
  • The yield on investments falls well below market in comparison to the balance

Applying Reasonable Parameters

Consider the close relationship between asset composition and gross income. If loans comprise 90 percent of a credit union’s assets and those loans have a 15 percent APR and nominal loan delinquency, the examiner would expect relatively high gross income. However, if gross income as a percentage of average assets equals only 6.9 percent, the results fall outside the examiner’s reasonable parameters or expectations and warrants further review.

Examiners determine the cause of an unreasonable ratio by conducting a reasonableness analysis. The examination software can compute share costs and loan yields within optional workpapers for shares and loans. It can also calculate reasonableness ratios. By performing reasonableness tests, the examiner might identify transaction risks such as:

  • Unauthorized disbursements
  • Out-of-balance conditions
  • Negative share accounts (overdrafts)
  • Payment of personal expenses from credit union funds
  • Fictitious loan or share accounts or other fictitious records

Fraud or embezzlement often cause the financial performance ratios to fail tests of reasonableness, which may serve as a red flag indicating the need for more in-depth review. Examiners evaluate all available data before drawing a conclusion regarding fraud or embezzlement within a credit union.

Examiners may find the Reasonableness Ratio worksheet useful in determining reasonable parameters.

Qualitative Data Analysis

The main purposes for reviewing qualitative data are to help project a credit union's future viability and to determine the control environment surrounding various operations. In an effective exam, qualitative analysis requires examiners to go beyond merely identifying trends; they must look for causes behind a credit union’s quantitative performance.

Qualitative data includes information and conditions that are not measurable in dollars and cents, percentages, numbers, etc. It can have an important bearing on a credit union's current condition, and can be used to more fully assess a credit union. Examples of qualitative data include:

  • Loan file reviews
  • Investment file reviews
  • Comments from officials and employees who have been interviewed
  • Meeting minutes,
  • Information derived from direct observation (for example, witnessing internal control procedures/separation of duties in effect)
  • Internal operating procedures and board level policies
  • Attitude and ability of credit union officials
  • Economic conditions within the general economy
  • Financial condition of the sponsoring organization

A credit union's future heavily depends on management's ability to identify, measure, monitor, and control risk. When a credit union implements new strategies or programs, examiners perform extensive qualitative data analysis on management’s tools for mitigating risk.

Multi-View Analysis

Just as a single product can present multiple risks, examiners can perform a variety of analyses—a multi-view analysis—on any product. For example, examiners can evaluate loans by analyzing:

  • The amount current and the amount delinquent (the amount delinquent can be further broken down into length of delinquency)
  • Concentrations of specific loan types or to single borrowers, geographic locations, etc.
  • The loan turnover rate
  • The percentage of high risk loans (may require profiling loans)
  • The amount allocated to a new loan program
  • The amount unsecured and secured

This approach allows examiners to look beyond static balance sheet figures to more accurately assess a credit union’s financial condition and risk potential.

Last updated November 02, 2021