Using AI and Alternative Data to Expand Access to Credit for Millions

According to recent research from LSU and Harvard University, access to credit could be significantly increased through the use of alternative data and artificial intelligence (AI), rather than just credit scores. The study found that smarter underwriting algorithms would be especially beneficial for recent college graduates and young people with short credit histories, as well as individuals with low or no credit scores. Traditional lenders, such as banks, who primarily rely on credit scores, are at a disadvantage compared to online lenders who use advanced technology and alternative data to estimate risk. The researchers examined outcomes for people who applied for more than three million Upstart personal loans between 2014 and 2021 and found that many people who were previously considered "invisible primes" were actually creditworthy.

The use of alternative data, including educational attainment and employment history, could enable lenders to approve almost twice as many borrowers, with fewer defaults. This would benefit both borrowers and lenders, leading to better outcomes for all involved. The research also showed that broader use of alternative data and AI in lending decisions could not only allow millions of Americans access to credit, but those approved for loans could also receive better interest rates. The financial health of invisible primes could improve significantly as a result of credit access, with those approved for Upstart loans becoming 20 percent less likely to default on credit cards and their credit scores increasing by 9 percent. Their ability to meet future obligations also increased.

Don Carmichael, manager of machine learning at Upstart, provided data for the LSU-Harvard study and argued that expanding access to credit means more business for lenders. He also noted that the use of alternative data and AI can enable lenders to isolate borrowers with different levels of risk, even among those with similar credit scores. The study showed that Upstart's model was able to identify high-risk borrowers even among applicants with high credit scores. This would have a significant impact on those currently shut out of the credit market, including young people, college-educated people, low-income people, Black and Hispanic people, and anyone who lives in an area where there are more minorities, renters, and foreign-born individuals.

In addition to benefiting borrowers, smarter underwriting algorithms and alternative data can also benefit lenders by reducing defaults and increasing profits. Lenders can use AI and alternative data to more accurately assess a borrower’s creditworthiness and risk of default, leading to more informed lending decisions. This can ultimately lead to higher loan approval rates and lower default rates, which can increase profitability for lenders.

However, the use of alternative data and AI in lending decisions is not without controversy. Critics argue that the use of alternative data could lead to discrimination, as certain types of data, such as education and employment history, could unfairly benefit some groups of people over others. Additionally, the use of AI in lending decisions raises concerns about transparency and accountability, as algorithms can sometimes be opaque and difficult to understand.

To address these concerns, some advocates have called for greater transparency and oversight in the use of alternative data and AI in lending decisions. This could include requirements for lenders to disclose the types of data they use and how they use it, as well as regulatory oversight to ensure that algorithms are not unfairly biased or discriminatory.

Despite these concerns, the potential benefits of using AI and alternative data in lending decisions are significant. By expanding access to credit and reducing defaults, these technologies can help millions of people achieve greater financial stability and security. With proper safeguards in place, AI and alternative data could be a powerful tool for promoting financial inclusion and improving economic outcomes for all.