It is very hard or impossible to figure out what was happening in one individual's life with this limited data.
The debts that are shown in the credit data may not be all of this fellow's debts.
Even something as simple as a credit card... All credit cards are not reported to all three agencies. LC uses one agency. Some cards are missed.
Other debts that don't show up... Alimony. That loan from the loan shark. (Can you imagine the possibility of there being a loan shark in Las Vegas?)
So it is quite possible that he was more stressed financially at the time he took out the loan than showed up in the data you had available.
There were several accounts listed. We don't know the terms of those accounts. Maybe some one of them "came due".
We just don't know enough about his situation and life events.
You're right about one thing ... Some people pay down their debt with proceeds of an LC loan, and some don't. You already commented on the FICO bump.
If you backtest LC loans, you can see that loans which have a close match between the amount of existing debt an the amount of the loan generate slightly higher returns. This fact has been discussed here from time to time. This result of course is a measure of the average performance of many loans, so while I believe that it means just what you think in general, it means nothing for one loan in particular.
You can do this kind of analysis on nsrplatform.com . I created a "formula" which was revolving balance divided by loan amount. (Loan amount is never zero, so is a safe denominator.) I then asked nsrplatform to calculate for all LC loans (no filter) for all time, broken down by my formula, and finally told them to display this as a chart.
The horizontal axis is the revbal/loanamt ratio. Sorry that the axis labels aren't tidy. This is an artifact of the way NSR autogenerates labels. Look at the blue curve. You can see that there's a broad optimum near the ratio = 1. Not a big variation, except when the ratio is very low, which is the case where a person borrows a lot more than he owes on his revolving accounts.
Before using this idea for your own investments, I suggest you use nsr to recalculate this for your particular loan filters, and for a limited set of years. You'll get a different result depending on the set of loans you use. Your other filters, for example, might already filter out the bad guys which filtering on this ratio would catch.
Author