Jeff Judy

Jeff's Thoughts - January 29, 2014

Of Analysis, Questions, and Answers

Credit analysis is a central process that contributes significantly to the bank's success. It is also a complex process. There are a lot of individual data points, a lot of calculations, a lot of rules. And especially in business lending, every "case" is unique to some extent.

As an industry, we deal with a lot of that complexity with technology, using computing power to organize information and crunch numbers. You might say that our industry has spawned a sub-industry of analysis software and systems.

I certainly think that using technology to manage complexity makes sense. The word "manage" is the key. I don't believe the purpose of technology is to eliminate complexity.

Rather, I believe the proper use of technology is to free up time and attention so that we can think properly about complex issues and decisions. Unfortunately, all too many institutions, perhaps in an overzealous quest for efficiency, use the credit analysis process to eliminate complexity rather than to deal with it.

These are institutions where the thinking is, "Collect data, run analysis, get answers." In my opinion, that's only a first step to understanding whether a potential borrower makes good sense for your bank.

To be really good at not only managing risk but seizing opportunity, you need to get beyond simple answers. In fact, you need to get beyond answers, period.

You need to get to questions!

One of the most useful outcomes of proper credit analysis is an awareness of what we don't know, what we are making assumptions about, what the borrower is making assumptions about. Good credit analysis includes some "what-if" thinking, which usually points to more questions to ask the borrower. It also points to questions to ask about broader economic and business trends in your marketplace. What will happen if conditions change (for better or worse)?

Answers to those questions may lead you to reconsider the recommendation from the initial analysis. Or they may lead you to opportunities to enhance the profitability of the relationship with additional services.

One question that should be automatic, after every analysis, is "Why are we seeing these numbers, instead of other numbers?" After all, maybe a particular numeric result is "2". You can just look at that number, compare it to a range or threshold, and leave it at that.

Or you can ask, "Why is that 2 and not 1.5 or 2.5? How are management actions affecting that number, and where will it be in a year if they continue that way? How do business conditions affect that number? Does the borrower know why that result is what it is? Do they have the knowledge and skills to deliberately modify that result going forward?"

Credit analysis is not just about what you know about the borrower. It is about what you want to know. "Answers" are great, but they should be just one part of a credit analysis process that will help you pick winners again and again.