There are two words that finance leaders at banks and credit unions should take away from this blog post. You won’t have to remember anything else. I encourage you to read through the narrative and examples, but all you really need to remember are those two words.

When you go to a management meeting or disseminate information in your organization, think about the various reports that are requested or those that the finance team believes are important. How many different reports are there? 10, 15, 50? Don’t just consider reports for the CEO, department managers, or board.  Whether produced electronically or printed in a large binder, a large number of reports likely are generated in your institution.

About those two words—the ones you need to remember? When generating those reports, you should be able to answer this question: “So what?” Of prime importance are the critical underlying questions the reports help to answer:

  • Why do these results matter?
  • What can be learned from these numbers?
  • How can management make better decisions based on these reports?

Descriptive Analysis versus Diagnostic Analysis

The first step toward answering the “so what” question is to look at the difference between descriptive analysis and diagnostic analysis.

  • Descriptive analysis answers the question, “What are my results?” This type of reporting is important and certainly necessary, but does not always lead to informed decision making.
  • Diagnostic analysis answers the question, “Why did I get those results?” For example, why did net interest margin change or why did return on assets fall 5 basis points? By drilling into the factors that led to change, it is much easier to use diagnostic insights to inform decisions and actions.

A specific example about net interest margin illustrates how these two types of analyses influence decision making.

Net interest margin (NIM) is an important metric for all financial institutions, typically representing 50 to 85 percent of total income. The example below for ABCD Bank that displays a five-quarter NIM trend. It shows that after declining in the first half of 2016, the bank’s NIM improved during the second half of the year.

 

This descriptive analysis is interesting information, but what can we do with it?  Margin improvement of about 9 basis points occurs, but what does this mean? Should we simply be pleased with the results and move on to other indicators or probe further? How can this information be used to make strategic or tactical decisions for the institution?

 

Diagnostic Analysis: Peer Groups

 

The next step would be to start ’diagnosing’ the information by producing a report that compares the institution’s margin to others in its peer group, gaining some insight into performance against that of similar institutions:      

When presented in a comparative format, ABCD Bank clearly is underperforming by 15 to 35 basis points. We now know that underperformance is an issue, but so what?  The report displays descriptive information and solid comparison data for some diagnostics, but on its own, it doesn’t facilitate decision making.

 

Diagnostic Analysis: Pricing

 

To dig into the institution’s underperformance, it’s useful to perform additional diagnostic analysis. Since net interest margin is driven by pricing, review of a product pricing report, such as the “quarter to date origination spread by product,” can be helpful.

This report provides the last three months of originations for the institution’s top 10 products in two categories: the volume originated and the funds transfer pricing (FTP) spread originated by product.

 

In the top left of the chart, the light blue bar shows that mortgage loans have the second highest volumes originated among loan products, only surpassed by commercial loans. Looking at the top 10 products in the chart on the right reveals that those same mortgage loans have the lowest FTP spread. This should be of concern because FTP is a key measurement of contribution to net interest margin.  

 

There can be many reasons for such a low spread, such as fierce competition that requires lower rates to attract borrowers. The key questions to ask are:

 

  • Is the institution compromising profitability (net interest margin) for the sake of bringing in new borrowers?
  • Can pricing be improved to increase mortgage loan net interest margin?

 

More diagnostic analysis to answer these questions can be obtained by drilling into a risk-based pricing analysis report.

This report examines the same mortgage portfolio, but looks at detailed account information. The scatterplot section illustrates the relationship between the risk rating of the account holder (in this case the FICO score) and the FTP spread on each loan. It shows whether there is ample return (margin) for the risk being taken based on the borrower’s credit score. In this case, the report displays a very flat pattern, indicating that the institution is not being paid sufficiently for the amount of risk it takes. The bank should be getting paid more (in the form of FTP spread) for its lower quality loans (to borrowers with lower credit scores). In other words, points on the FTP spread (Y axis) should be higher on the lower end of the credit score (X axis).

 

Although there is very little the institution can do about changing the rates on its current portfolio, this report may prompt review of the institution’s pricing policies, which could result in setting higher rates for lower quality new originations. This change would increase new volume spreads, therefore resulting in higher net interest margins going forward. Without additional diagnostic analyses, the institution likely would not have made this pricing policy decision.

 

The Bottom Line

 

Returning to our original “so what” question, the example in this post illustrates the power of this inquiry. Before generating any report, ask every report recipient the same thing:  How does the report contribute to strategic or tactical decisions that are going to improve our institution’s bottom line?

 

This simple exercise should help eliminate unnecessary analyses and replace them with enhanced reporting activities that answer the “so what” question.