The Second Edition of Commercial Loan Analysis Has Been Released

Big news!  The second edition of Commercial Loan Analysis is available.

The new print copy is available at Amazon.

I have made additions and improvements to every chapter and section.  I've added new chapters as well, including an intro to financial statements as well as analysis of commercial real estate and global cash flow analysis.

Let me know what you think about it...

Ken

The Gambler’s Fallacy and How Credit Decisions are Affected by Human Bias

Life is complicated, and we are busy.  People just don’t have the time or the energy to analyze everything.  So, we employ “heuristics” or “rules of thumb” to help us make judgments.  While these rules of thumb are often helpful, they also cause systematic biases which adversely affect our decisions.  This happens to all of us at home and at work.

And yes, if you work in any role related to credit underwriting, the chances are that these heuristics affect your decisions and the decisions of your coworkers.  Here are a few of the most common biases:

• Availability: Our judgments are affected by the ease of remembering or retrieving events, and more vivid or more recent events tend to be more memorable.
• Regression to the Mean: We assume that we can predict the future from the past, that this year’s cash flow will be similar to last year’s cash flow.  However, any extreme performance is likely to regress to the mean.
• Confirmation Bias: We tend to selectively search for information which supports the conclusion which we desire to reach (or which is located wherever we have found the information previously).
• Overconfidence: People tend to be overconfident in the accuracy of their predictions.
• Hindsight Bias: We assess the quality of a decision based upon whether the outcome was good or bad, not by whether the original decision-making process was sound.

The Gambler’s Fallacy is another bias, and this one has been shown by academic research to impact credit decisions.

People underestimate the likelihood of sequential streaks occurring by chance.  We tend to believe that things will even out.  This is the Gambler’s Fallacy.

For example, in roulette, if red has come up four times in a row, then people are more likely to bet on black.

If a Major League umpire has just called a strike, then he is slightly less likely to call a strike on the next pitch (after controlling for the actual position of the ball).

And, a study of lenders in India found that when an officer approved a loan, he or she was 8% more likely to decline the next loan application.

How can you combat this bias?  First, learn about it.  For an important decision, develop an algorithm that helps you decide, and have another set of eyes examine the outcome.  The right types of incentives can help too.  In fact, the lending study found that adverse effects were reduced when stronger incentives for accuracy (versus the number of approvals) were implemented.

If you are interested in learning more, then please contact me here.  I have been researching behavioral science for a few years along with reviewing actual loan approval processes and decisions.  I have lots of interesting examples and solutions (with a focus on commercial loans).

I will begin formally presenting this information later in the year, but in the meantime, I’d like to perform a couple of free trial presentations.  If your institution is interested, then please contact me.

Links:

·       https://www.washingtonpost.com/news/wonk/wp/2016/03/09/the-dumb-mistake-that-gamblers-judges-and-baseball-umpires-make/

·       https://academic.oup.com/qje/article/131/3/1181/2590011/

·       https://csbcorrespondent.com/blog/bias-your-loan-approval-process-part-i

·       https://csbcorrespondent.com/blog/bias-your-loan-approval-process-part-ii

This website has a new section! Check out the financial statement and ratio analysis information here...

http://www.financialstatements.commercialloananalysis.com/

Credit Decisions and Behavioral Science

The RMA recently passed along this very interesting article about credit decision-making and the behavioral biases exhibited by humans.

This is a topic that I have been researching myself.  In the future, I plan to consult with banks about improving credit decision-making processes in light of the biases and errors that are often unavoidable due to human nature.  It's a very interesting intersection between finance, credit, and psychology.  If you are interested in helping out, providing ideas, or learning about how your bank can benefit from the research in this field, then please contact me.

Here's the entire link to the RMA article:
https://www.rmahq.org/decision-making-and-corporate-culture-insider/

How to Order Commercial Loan Analysis: Principles and Techniques for Credit Analysts and Lenders

There are a couple of ways to obtain my book, Commercial Loan Analysis: Principles and Techniques for Credit Analysts and Lenders.

You may order on Amazon.

Or, you can check out the Financial Statement Analysis section of this website.  You will find that selected sections of the book (particularly financial ratios) are presented there.

Thanks for reading!

Ken Pirok

How Does Your Bank Calculate NOI?

When analyzing commercial real estate, most banks present columns with NOI listed for historical periods along with a column of pro forma or "underwriting" NOI.  Pro forma NOI is often calculated using “Potential Gross Income” (representing gross rents as if the property were 100% leased) less a vacancy factor.

In pro forma analyses, appraisers and banks often apply replacement reserve factors as well.  Recent appraisals may contain an appropriate vacancy factors, management fees, and replacement reserve assumptions to use in your analysis.

Your bank’s loan policy may also dictate standard amounts to use for vacancy, bad debt, replacement reserves, and management fees in the pro forma analyses.  If your bank has a policy on how to calculate pro forma or "underwriting" NOI, then I'd like to hear about it.  Feel free to leave a comment about how you make the calculation and which expenses are included and excluded.

Current and Non-Current Assets and Liabilities

There are two types of assets and liabilities, “current” and “non-current.”  Current assets are those that are expected to be converted to cash in one year or less, and current liabilities are those that will come due in one year or less.  So, cash, marketable securities, accounts receivable, and inventory are all considered current assets, while accounts payable and the principal amounts of loans due within a year are considered current liabilities.

Non-current assets and non-current liabilities are due or converted to cash in more than a year.  Fixed assets and intangible assets are considered non-current, and loan amounts which are due in more than a year are also considered non-current.