How AI Loan Scoring Works (and Fails)

AI is transforming consumer lending, promising faster credit decisions and greater access. But the reality is more complicated. Many AI-based scoring systems rely on alternative data — utility payments, online behavior, even social media activity — to predict creditworthiness.

While this can help thin-file borrowers, it also raises concerns. These proxies can encode bias. For example, a 2023 study from the Brookings Institution found that AI credit models disproportionately rated Black and Latino applicants as higher risk, even when controlling for income.

Another problem is opacity. Because these algorithms are proprietary, denied applicants often have no clear way to understand or contest the decision.

Regulators are paying attention. The EU’s AI Act and U.S. proposals like the Algorithmic Accountability Act call for greater transparency in automated credit decisions. The goal: ensure AI lending tools expand opportunity without reinforcing old inequalities.