Four Mistakes to Avoid Making When Analyzing Profitability

business man drawing financial graph
By Steve Wofford

5 minutes

Failing to account for staff costs is the most common problem.

From time to time, Kohl is asked to do a comparative audit of a credit union’s internal systems. For example, we might compare the profitability servicing a credit card versus the profitability of servicing a car loan. When we do this, we commonly find that there are significant differences between the systems, and it often comes down to one specific issue.


Many credit union leaders don’t realize that just having employees drives about 75% of non-interest expense—50% of that is direct salaries and benefits and another 25% is everything related to keeping them productive. This includes a place to work and that predicates desks, chairs, HVAC, cleaning services, HR people, computer networks, etc. Surprisingly, not much has changed when accounting for remote staff members so far. Until the office space is jettisoned, the costs are still there. In fact, costs like network connection from home plus security have increased.

The errors we see are when profitability analysts attempt to use a cost driver other than the actual time employees spend on specific activities related to specific products are often frightening. Using such drivers as the number of loans or balances does not reflect the huge differences in the cost of servicing a credit card versus an auto loan. The total cost for people for a product must be based on the total cost of their time (salary/benefits etc.) plus directly related productive support costs.

When using the wrong drivers, we’ve seen cost assignment efforts miss the mark by hundreds of basis points. The result is useless information at best and, at worst, can “help” credit unions make wrong decisions.

In addition to mismanaging how you account for the cost of your people, here are three additional pitfalls to avoid when it comes to assessing profitability:

1. Poor Instrument Cash Flow Pro Forma Modeling

A major mistake we see in modeling cash flows for loans is the assumption that servicing costs are a function of loan balance. Many people think servicing costs are a static 35 basis points of the loan balance, but they’re not. If you analyze it this way, servicing a $100,000 loan costs $350 (100,000 x 0.0035) and servicing a $1,000 loan costs $3.50 ($1,000 x 0.0035). Using this approach, servicing costs go down as the loan balance goes down, which is simply not correct. If anything, servicing costs go up over time due to inflation. Basically, it costs the same to service a $60,000 auto loan as a $10,000 loan or even a $1,000 loan and that increases over time.

2. Thinking Loan Term Is a Strong Driver of Value

Many years ago, pricing loans by dollar size was common. During the 1980s, modern portfolio theory gained traction and loans began to be priced by loan term. This also coincided with a period of high interest rates and much steeper yield curves, so pricing by loan term made a lot of sense. Today, with historically low interest rates and corresponding historically flat yield curves, the term of the loan is an inferior determinant of value compared to the size of the loan. Instead, dollar amount and credit score are the strongest drivers of loan value.

3. Poor Understanding of the Difference Between Accounting and Finance

An area where we often see profitability analysts struggle is in the treatment of fees and costs at the origination of a loan. A common practice in accounting is to ignore FASB-91-type treatment for loans and instead immediately recognize those amounts as income. This is fine for accounting purposes but very problematic for profitability analytics.

The issues become apparent when looking at the value/profitability of a newly issued loan versus loans that were originated a few years ago. The newly issued loans will see the full impact of those origination amounts right now, today, if they are booked straight to income. In contrast, the older loans would see no impact today, as those amounts were already recognized years ago at the time of origination.

The result is that new loans look artificially less valuable because they are carrying the full origination burden in this period and the older loans look artificially good because they have no origination burden in this period. The solution is to apply FASB-91 concepts so that those origination burdens are amortized of the life of the loan, essentially setting new and old loans on equal footing.

Many accounting groups rationalize not using FASB-91 principles because they don’t have the mathematical tools to do so. What they don’t realize is the Microsoft Excel’s future value function handles these mathematical calculations very well. Provided the proper input, the future value function can calculate the outstanding balance of an amortizing loan at any point in the future which is the key to determining FASB-91 accounting.

Now that you’ve read this blog, we hope you can avoid these profitability analysis problems in the future!

Steve Wofford is CEO at Kohl Analytics Group. Before purchasing part ownership of Kohl, Wofford was director of financial analytics research for Oracle Corp. He also was the director of the Center of Excellence for Activity Based-Costing at SAP and their 3,000 ABC clients and led the Center of Excellence for EPM, BI, and Advanced Analytics for IBM’s consulting arm of 100,000 consultants. Wofford holds a master’s degree in finance with an emphasis in financial engineering/math.

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