Bad Credit Decisions and how to make them
A man we know went to test drive a luxury four-wheel-drive vehicle. He was wearing a pair of shorts and a singlet. The car salesman sized him up as someone who couldn’t possibly afford such a car and ignored him. After a while the customer walked out, crossed the road, and bought a $70,000 RangeRover at a rival dealership. He may not be the snappiest dresser in the world but he has pots of money.
This is a nice example of one of the ways in which we can make bad and hugely expensive credit decisions. This article is about how we make bad credit decisions and why. It’s said that economists are experts who will know tomorrow why the things they predicted yesterday did not happen today and that they exist for the purpose of making weather-forecasters look good. Well, we think the level of bad decision-making in credit management is far greater than in either of these professions.
Here are five things that go wrong with the credit decision-making process. The ability of creditors to work this out who will pay and who won’t is often vastly overestimated. Bear in mind that we’re not saying that predicting this is easy, but that there are avoidable errors being made.
We overestimate the accuracy of our judgements
If you give Joe Credit Controller a marginal credit application and report, he looks at it with reasonable objectivity and probably turns it down. If he meets and talks to the applicant, and he or she turns out to be a nice person, Joe is much more likely to approve the application. In credit, and perhaps in life, we all overestimate our ability to judge people face-to-face.
This is largely because of what psychologists call "the overconfidence phenomenon". We all want to think we make good judgements, so after we’ve made a decision we seek evidence to confirm that decision. It’s hard for us to discard our ideas because we do not want to be wrong. We don’t seek information to disprove what we think, so we rarely find it. Once we have a belief, it influences how we perceive all other relevant information. The corollary of this is that if things do go wrong we tend to find something other than our own decision-making to blame.
We are easily distracted by useless information
Sales people and branch managers often tell us something along the lines of, "I didn’t get a credit check because I knew the guy. His kids are at school with mine." Sure, but what do you really know about him? You see the external assets that may well be rented or mortgaged to the hilt. You might think he’s a nice bloke but that doesn’t mean he will have the money to pay his accounts in 50 days time. Credit reports that show past payment history are a much better indication. Nice guys who can’t pay their bills go bankrupt just like bad guys.
Lack of research on the signs of future business failure
There is very little published statistical information on the best predictors of bad debt. Weather forecasters have statistical data on New Zealand weather going back 100 years or more. Credit staff don’t have that luxury. Where there is data, they are often unaware of it.
There is overseas data which suggests, for example, that one of the best indicators of future business failure is involvement in a past business failure. Our credit decision-makers don’t seem to know that. We’ve asked a number of groups of managers in the builders’ supply industry recently whether they had builders on their ledger who had had previous failed businesses. Most hands have gone up.
We make high return decisions using the same criteria as low return decisions
This is particularly relevant to the assessment of risk. Other things being equal, a higher return makes a higher risk more attractive. Front-line staff often forget to think about the return. They treat the customer on whom they would make a 5% profit the same as the customer on whom they would make a 100% profit.
In practice, it may also be that the credit staff don’t understand the potential return. One company we know had a gross profit margin of around 80%. In an in-house seminar we asked the credit staff what they thought the profit margin was. Most thought about 10 or 15%. These were people who were involved in the collection of debt. They were taking a conservative approach to the repayment deals they would accept and the conditions on which they would continue to supply. In fact they should have been prepared to take greater risks to keep these highly valuable customers.
We don’t get all the feedback that we need
Human beings modify their behaviour in response to feedback. Weather forecasters and economists can at least see if their predictions turned out to be correct. Someone who makes a decision on a credit application gets to see the results in respect of the customers who are approved, but seldom for the customers who are rejected. The salesman in our RangeRover story is probably still blissfully ignorant of the amount of commission he passed up.
Because of this problem we think many creditors are more likely to be making the mistake of turning away good customers than accepting bad. In some of our seminars we ask credit staff to indicate how many credit applicants they would expect to reject out of 100. We often find that some people are turning away 20 or 30 more customers than other businesses in similar situations.
For example, we know of a woman who, with little credit management experience, was thrown into the job of credit approval team leader and told to do her best. There were no guidelines in place but she was very pleased with the diligence with which she identified and turned away bad risk applicants. After a year of this, she was instructed to approve more applications.
Over the next year her team approved an extra 5000 customers - customers whom they would previously have turned away - with no obvious detriment to the company. In fact, because of other initiatives, all the other measures of credit performance improved markedly over that period. The increased profit from the extra customers was in the hundreds of thousands of dollars. Or looked at another way, that was how much the overly cautious attitude the year before had cost the business.
There are three concrete suggestions we can make that will apply to most businesses and which will improve credit approval decision-making. The first is to seek out objective information for all credit decisions. Have a rule that says that standard information - application forms, credit checks, and the like - are obtained for all accounts. Invest in a new credit report for large accounts annually.
Second, carry out post-mortems on your bad debts. Look at what you knew about the customer when you approved credit, and whether there were warning signs in the months preceding the debt going bad. What can you learn from this bad debt? If you turn down a company, make a note to do a credit check on them in a year’s time. Are they still in existence? Do they have subsequent bad debts?
And third, don’t throw staff into the deep end of credit reporting and tell them to do their best. We see a lot of credit staff who know they have to do a credit report but have no idea of how to interpret the information on the report. Give them guidelines and training. Predicting who will pay is far from being a precise science, but nor is it just a matter of being a good judge of character.