Agentic AI risk-aware credit decisioning sandbox : A framework for responsible financial innovation

Abstract

The rapid evolution of artificial intelligence (AI), particularly in the form of agentic systems, has introduced unprecedented capabilities for autonomous decision making in various sectors, including financial services.1 These agentic AI systems, characterised by their ability to act independently and learn from interactions, promise to revolutionise credit decisioning by enhancing efficiency, accuracy, and risk assessment. The autonomous nature of agentic AI, however, necessitates a robust framework for managing inherent risks, including issues of accountability, bias, and compliance, especially within the highly regulated financial industry. This paper proposes the development and implementation of agentic AI Risk-Aware Credit Decisioning Sandbox (RA-CDS) as a critical mechanism to foster responsible innovation while mitigating potential systemic risks. This controlled environment would allow for the rigorous evaluation of AI agents’ performance and adherence to ethical guidelines within credit decisioning processes.2 This article is also included in The Business & Management Collection which can be accessed at https://hstalks.com/business/.