2021: The Year in Which AI Credit Engines Surpassed Banking’s Traditional Methodologies

Recently, UPSTART went from being a private entity to becoming one of the most wanted companies in the New York Stock Exchange (NYSE), with a P/E ratio higher than 1,760.

Investors bet that UPSTART is going to be the next Artificial Intelligence (AI) Credit Engine that most banks in the US will end up using to power their underwriting and leverage upon the learnings of who will be a good or a bad borrower, something that can only be achieved by the use of a predictive software, like UPSTART, that aggregate all of these learnings.

These aggregate learnings create a Network Effect, in which, the more repayments get registered, the better the predictions are, and more banks benefit from it. Today, UPSTART has 12 banks feeding data to their software, therefore it still may not have better predictive ability than leading Financial Institutions such a Bank of America. However, adding the recent $15 billion valuation that UPSTART reached only a few days ago, it will be only a matter of time for these institutions to jump into enriching their credit decisions with UPSTART; similar to what happened when we turned from searching in Encarta to Wikipedia.

In addition to UPSTART, there is another AI Credit Engine positioning itself as a leader in LATAM: QUASH.ai, in which with more than 40 Financial Institutions are feeding today its engine and with their most recent valuation of $15M, is positioned to become the leading AI Credit Engine in this region.

Unlike the USA, the lack of credit access in LATAM is due to the few data that’s available for Financial Institutions’ credit models. Nonetheless, since our society has generated more data in the last two years than ever in human history, these new data points are enabling credit access like never before.

After processing 30 million loans in the last 12 months, QUASH’s software has learned that 80% latinos have never failed to repay their loans. However, less than half qualify for credit access according to the traditional credit models, and very few end up accessing the best offerings regarding interest rates and conditions. With smarter credit models, lenders can approve almost twice the applications with fewer defaults.

The arrival of AI represents a paradigm shift in how banks have been evaluating their credit applicants. There are more than 500 million latinos who anxielly wait to be evaluated through these new models, so they can reach a higher quality of life with more financial inclusion.

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