Big Data in Lending has Ability to Confirm Biases and Extend Credit to Weaker Borrowers

After the financial crisis banks pulled back from lending to anyone they deemed a potential risk; this helped spur many of the fintech lenders you see today and a wave of new underwriting technology being used by banks; FT Alphaville asks how alternative data is playing a role in underwriting and what it means for borrowers; Moody’s explains some of the new data fields include education, academic scores and job history; the concern is that these new fields could enforce biases as top tier schools and high paying jobs would be viewed as less risky; they could also help lenders to extend credit to borrowers who are too risky as they try to use new forms of data to rationalize a loan; lenders need to be careful and remember the past to not find themselves repeating it. Source.

Todd is the Chief Product Officer of LendIt Fintech.

He is the host of PitchIt: the fintech startups podcast, a weekly interview show featuring emerging fintech founders and leading venture capitalists.

He is responsible for leading the content team which covers fintech through daily & weekly email newsletters, editorial, virtual events, and in-person conferences.

He has been covering fintech, banking, and venture capital for more than 15 years, including speaking regularly at industry events.

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Joseph Putman
Mar. 14, 2019 4:22 pm

Bias is good when it leads to good outcomes. If top tier schools and high paying jobs are indicative of less risk, than taking these into consideration isn’t an unfair bias, it is factual risk based lending and should be embraced as it leads to lower costs for credit for the entire group through lower default risk. Lending isn’t where social justice warriors should be looking to bridge inequality. When risk is priced correctly, everybody wins. Didn’t we all learn that from the mortgage debacle?