The
increasing adoption of artificial intelligence (AI) in credit risk assessment
has significantly transformed lending operations within financial institutions.
AI-driven credit scoring systems enable faster processing of loan applications,
improved prediction of creditworthiness, and enhanced operational efficiency.
Despite these benefits, the increasing dependence on AI technologies has
generated concerns related to transparency, fairness, accountability, data
privacy, and regulatory compliance. In this context, effective corporate
governance plays a crucial role in ensuring the responsible and ethical use of
AI in financial decision-making.
This
study examines the corporate governance practices and accountability mechanisms
associated with AI-based credit risk assessment in financial institutions. It
explores the influence of governance structures, board oversight, risk
management policies, internal control systems, and ethical standards on the
design, implementation, and monitoring of AI models used in lending decisions.
The research also investigates key challenges such as algorithmic bias, lack of
explainability, data protection issues, and accountability for automated
decisions. By analysing evidence from financial institutions, the study
evaluates the effectiveness of existing governance frameworks in managing
AI-related risks and fostering stakeholder confidence. The findings aim to support
the development of robust governance strategies that balance technological
innovation, ethical responsibility, regulatory compliance, and sustainable
organizational performance.
