In this article I will walk you through a high level view of how to assess credit risk and compare it with how a bank may approach the same problem.
Let’s say that someone approached you and asked to borrow $100 dollars. Would you lend it to them? Well let’s see, your immediate question may be “what do I get out of it?” or maybe “who’s this person who is asking for the loan?”
Those would be good questions.
If you’re unlikely to make any money out of the loan, unless you are truly altruistic and charitable, you are unlikely to grant the loan. I know you’re not a bank, but for a bank there would be no point in taking a risk to lend money if there is nothing to get out of it.
For your other response “who’s this person?” it seems obvious that someone who walked off the street and asked you to lend them some money is very different from say your sibling or a close friend asking you to lend them money. If you don’t know the person at all, you cannot judge whether they would be able to repay the loan or not. Since you know your sibling or friend you would be in a better position to judge whether they are able or likely to repay you and therefore you would be able to make a more informed decision.
Same way with a bank, the more they know about the person, their job situation, how much they are stretched with expenses, how many other loans they have and obliged to pay back, the better they are able to assess their ability to repay a loan.
So let’s say this is your friend now who is asking for the loan. You know him well and you know his financial situation. But he has never borrowed from you before and therefore you don’t know how good he would be when it comes to borrowing money. Would you would be more hesitant to lend him money then if you had done so before and he had repaid it promptly and fully?
Same way with banks, if you have some credit history they are in a better position to tell whether you would honour your obligations.
Ok, let’s continue with this analogy. Your friend, you know him very well, you know his financial situation, he has a good steady job and his expenses as far as you know are under control, he has borrowed from you before and had repaid his loan on time and in full and with interest. Should you lend him the money based on that alone? Well, probably not. You may want to ask what the loan is for.
What if this reliable friend was asking to borrow money because he wants to take a chance at the roulette table at the casino? Hmm. A bank asks for the purpose of a loan because the risk of what that loan will be used for is a factor in estimating the overall risk. From experience the bank would know that loans taken for similar purposes have similar risks. You know that borrowing money to play at the casino is a problem because you know that people who have done that in the past usually lost it.
Again, what if your friend is asking to borrow the money to gamble at the casino, but to put your mind at rest, he says that you can hold on to his Rolex watch which is worth twice the amount he is borrowing and that if he does not repay you in full with interest in three months, you get to keep the watch. Are you more inclined to lend him now? Very likely. You are protected by collateral. In fact you may even go easy on him with the interest rate since you basically can’t lose. If he pays you back, you get your money and interest and if he defaults you get to cover your loss with the value of the watch. Same way with a bank, there are secured loans such as mortgages that are protected by the value of the house or unsecured loans like credit cards. The willingness of the bank to lend either is different and the rates of interest they charge on either is also different because of the associated risk.
So we can see that a credit risk assessment is a combination of a few elements. There is how much you are lending: obviously lending $100 is not the same as lending $1000. You are taking a bigger gamble with the second amount since there is more to lose. The second element is the likelihood of your getting your money back which is affected by many factors, the reliability of the borrower, their financial situation, what they’re using the money for. The third element is how much you are going to lose if they don’t repay you which is affected by how much you can recover: if you have collateral, then you can sell it and recover all or part of the money.
In a nutshell credit risk = exposure x probability of default x loss rate.
Exposure is the amount that you are lending. The probability of default is how likely it is that the borrower will not meet their payments. The loss rate is the percentage of the money that you are likely to lose in case they don’t repay.
So in the case of your friend needing $1000, he is reliable and you are 80% sure he would repay his money because he is borrowing it to fix his furnace this month, in the event that he is unable for repay you, he has given you his Rolex which is worth $600, your risk is:
$1000 x 0.8 x 0.4 = $320.
Where did we get that 0.4 from? Well, we already said that the collateral amount is for $600. That is what you would recover. Since we are looking at your loss rate, then we are focused on what you would lose which is the balance $1000 – $600 = $400. $400 is 40% or 0.4 of $1000. 0.4 is therefore the loss rate.
So, using the equation above, we now know your risk would be $320.
What if the Rolex watch was worth $1000? Well that would mean that your rate of loss would be zero. If we plug that in the equation we will have your credit risk as:
$1000 x 0.8 x 0 which equals zero.
Meaning, that if the collateral is the same value as your loan, then you have no risk. Unless you can’t sell that watch of course. But we don’t want to complicate things in this post because we are trying to use a simple analogy to explain basic credit risk.
Hey wait a minute, some of you may ask. Where did you get the “you are 80% sure he would repay” from? Well maybe you got this from just “gut feel”. The bank on the other hand would use “expert” risk analysts to make that judgement by comparing similar situations and their outcomes. It is also possible that the bank used statistical analysis or a combination of expert judgement and statistical analysis to come up with that number.
Hope you found this useful.
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