Artificial intelligence and bank credit analysis: A review

Abstract

This article teases out the ramifications of artificial intelligence (AI) use in the credit analysis process by banks and other financing institutions. The unique features of AI models, coupled with the expansion of computing power, make new sources of information (big data) available for creditworthiness assessments. Combined, the use of AI and big data can capture weak signals, whether in the form of interactions or non-linearities between explanatory variables that appear to yield prediction improvements over conventional measures of creditworthiness. At the macroeconomic level, this translates into positive estimates for economic growth. On a micro scale, instead, the use of AI in credit analysis improves financial inclusion and access to credit for traditionally underserved borrowers. However, AI-based credit analysis processes raise enduring concerns due to potential biases and ethical, legal, and regulatory problems. These limits call for the establishment of a new generation of financial regulation introducing the certification of AI algorithms and of data used by banks.