ARTIFICIAL INTELLIGENCE AND CAPITAL SOLVENCY RATIOS: THEORETICAL FOUNDATIONS, EMPIRICAL EVIDENCE, AND SYSTEMIC IMPLICATIONS

Abstract

This paper investigates the interplay between artificial intelligence (AI) integration and capital solvency ratios within financial institutions, combining theoretical frameworks with empirical evidence to assess systemic implications. It explores how AI-driven decision-making and algorithmic trading influence capital adequacy, risk management, and market stability, highlighting potential feedback loops and regulatory challenges. The study underscores the necessity of harmonizing AI governance with prudential capital requirements to mitigate emerging systemic risks and enhance financial resilience in evolving market ecosystems.