Transforming Finance: The Dual Impact of AI on Operations and Equity

Artificial Intelligence (AI) in financial services, particularly in credit scoring, presents both opportunities and challenges for addressing socioeconomic inequalities. A Brookings Institution study revealed that existing credit scores like FICO are strongly correlated with race, favoring white homebuyers over Black and Hispanic applicants. Research by economists Laura Blattner and Scott Nelson further demonstrated that disparities in mortgage approvals stem not only from bias but also from the lack of comprehensive credit data for minority and low-income groups, leading to less precise predictions and contributing to inequality. While the integration of AI and Machine Learning in credit scoring offers potential for enhancing financial inclusion, particularly for underbanked communities through the use of alternative data sources, its implementation requires careful consideration. The ongoing efforts of banks and startups to leverage these technologies for economic growth must be balanced with responsible use, necessitating continued vigilance and collaboration between industry players and regulatory bodies to ensure that AI-based credit scoring systems promote fairness rather than exacerbate existing disparities.