Machine Learning and Consumer Banking: An Appropriate Role for Regulation

Machine learning has the potential to democratize access to credit. It can expand the pool of people qualified to obtain credit -- most notably low- and moderate-income (LMI) borrowers -- and decrease the cost of that credit. It also can increase access to credit and reduce systemic risk by allowing different banks to analyze different factors, and thereby generate different results in a way that the existing, FICO-based system discourages. The greatest current obstacle to this development is pressure from the banking regulators to continue adhering to the status quo system, lest machine learning produce an unfortunate outcome. Perversely, that system already contains the very flaws that regulators have expressed about machine learning.