The rapid evolution of artificial intelligence (AI), particularly generative AI (Gen AI), promises transformative changes in the financial services sector.
CRISIL recognises the vast array of potential applications these technologies bring, reshaping banking functions and enhancing customer experiences.
While the opportunities presented by AI are significant, effective data governance remains a central concern for its successful integration.
Anshuman Prasad, Global Head of Risk Analytics, CRISIL, recently published an article highlighting governance challenges that financial institutions must overcome before AI adoption becomes commonplace. Key concerns include transparency in training models, maintaining high ethical standards, and specific and robust governance frameworks for AI's optimal use.
As banks strive to address these challenges while expanding their AI capabilities, it is crucial for them to align their business strategies with the inherent risks of new technologies and match their risk appetite with the AI use cases they want to develop.
Foundational governance pillars such as data quality, metadata management and taxonomy management will not only require more emphasis, but also need to adapt to support the underlying data that fuels these capabilities. This paper explores the paramount relationship between AI scaling and data governance, underscoring its transformative potential for the financial sector.
