On PeerCube, I started a peer filter for Bad-Loan Experience Index that I will continue to enhance as I review BLE Index for different loan parameters. In this post, I will review the two loan parameters that I had previously analyzed using default rate: Loan Length and Interest Rate.
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BLE Index for Loan LengthThe table below shows the calculated BLE Index according to loan length. While reviewing the table, we need to keep in mind that 60 month loans were only started to be issued in 2010. The green color represents loan length that has BLE index less than 0.90 and light red color represents loan length that has BLE index greater than 1.10. As a refresher, the smaller the BLE index, the better it is in reducing the credit risk.
It appears that loans with 36 month loan length are better loans with reduced credit risk than loans with 60 month loan length. This observation is consistent with general tendency of shorter loan length with better credit risk mentioned in 1940 study in NBER publication [PDF]. I also reviewed the BLE index for loan length for year 2010 through 2012 as shown in table below. The trend consistently shows 36 month loans having better credit risks but the gap is closing over past three years.
BLE Index for Interest RateThe table below shows the BLE Index according to interest rate buckets. Each bucket is 3.00% interest rate wide. The BLE index ranges from 0.35 for loans with interest rate of 3 - 6% to 3.09 for loans with interest rate of 21 - 24%. It appears that interest rate is significantly related to credit risk. The rising BLE index pattern with rising interest rate is also very consistent. Logically, it makes sense: the higher the return, the greater the risk.
The table below shows the BLE index for interest rate for year 2007 through 2012. The BLE index pattern is pretty consistent: the higher the interest rate, the higher the risk.
BLE Index CaveatsNo measurement is perfect and BLE Index has its own caveats that we need to consider.
Finding tendencies and not certainties
The following quote from the NBER publication sums it up nicely. It was true in 1940 and, in my opinion, it is true in 2012, too.
"Statistical analysis of the kind we are here attempting are necessarily based on averages and probabilities, and therefore can reveal only tendencies, not certainties."Weigh the advantage of eliminating X% of bad loans against the disadvantage of eliminating Y% of good loans
Let's take a hypothetical scenario of deciding whether to eliminate loans with interest rate between 15 and 18% from consideration. Your decision to review this class of loans is driven by the findings above. The BLE index of 1.91 is much higher than your benchmark of 1.10, so you are deciding not to invest in such loans.
Instead of using a redline approach to eliminate all classes of loan that have BLE index higher than 1.10, weigh the advantage of eliminating, for example in this case, 21.59% of bad loans against the disadvantage of eliminating 11.28% of good loans.
Let's assume there were total 2,000 bad loans and 10,000 good loans and loans with 15 - 18% interest rate have 22% bad loans and 12% good loans. These number are approximate from above and previous post for easier calculations. If you decided to eliminate loans with 15 - 18% interest rate, you will be eliminating 440 bad loans and 1,200 good loans.
You are the only one who can decide whether missing out on 1,200 good loans in order to avoid 440 bad loans is worth or not. Once I finish reviewing all parameters for default rate and BLE index, I will review another measure that may help in this aspect.
- To reduce credit risk, lenders may consider avoiding loans with 60 month term.
- Though BLE Index indicates loans with interest rate less than 12% are better, lenders looking for higher yield may need to consider the advantage of eliminating X% of bad loans against disadvantage of eliminating Y% of good loans.