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There is a long discussion over at Saul's of the efficacy of UPST's AI/ML and its regulatory issues. I'm not sure if it is a conundrum or a paradox or maybe something else. I am loathe to comment over there due to that boards own off topic regulations.

Currently, UPST has a sort of Good Housekeeping Seal of Approval from regulators and advocate groups with regard to fair lending. But, reading Kendi and others, I come away with the understanding that the systemic negative treatment of disadvantaged communities results in unequal outcomes. Therefore, the "system" needs overhauling. It is institutional, not personal. Taking that as a given, then the disadvantaged communities will, in the macro, have have higher loan payment risk. So no matter how community-neutral the AI/ML is superficially, the very accuracy of the risk assessment will result in unequal outcomes if the loans are aggregated at the community level. The average loan interest rate, loan amount, rejection rate will negatively impact disadvantaged communities. I don't see how, with this outcome, UPST can avoid negative regulatory actions in the longer term.

The only acceptable outcome is that everyone will need to pay higher, equal interest rates, which then negates the predictive value of the AI/ML that UPST employs. Or am I missing something? Or do we have a newly enlightened regulatory system. Or are the advocate groups not eating their own cooking?

I'm along for the UPST ride but I need to stay alert for the first crack in the narrative that UPST are the good guys, in contrast to the black hat banks.

KC
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