FICO scores, by far the most popular credit score system, seem to be set up in a strange way. Their purpose is to measure the quality of a loan application, and yet their methodology seems quite suboptimal to do that.
From Patrick Mackenzie (Bits About Money):
FICO scores are unreasonably effective. Many, many, many teams have thought “I bet I can get better loss rates if I supplement FICO scores with another data source”, and just about the only data sources for which that is actually true are illegal to use.
And yet, if you look at the calculation of these scores, it basically is this:
Payment history (35%)
Amount owed (30%)
Length of credit history (15%)
New credit (10%)
Credit mix (10%)
Basically, this seems to just be
1 is obvious, and likely why it is a ~third of the score. However, this is clearly not unreasonably effective.
2a seems less effective than a bank worker directly looking at a customer's financial situation: these factors are basically a way to check someone's financial health without access to their income, as that is much messier.
2b seems to not be important enough to make up a significant portion of the score. The risk from credit not intended to be repaid is separate from risk accounted for via past loan delinquency base rates and future changes in financial situations, mostly as a separate, rare-but-consequential event. I don't think that adding the two tells you a lot about the person.
I think the most probable answers are the top-level bullets below, from most to least likely:
Essentially, FICO scores do not seem to be made with a special process. How can they be especially good data?