The Moderating Role of Employee Expertise in the Relationship Between AI Adoption and Loan Management Performance in the Banking Sector

Abstract

The research examines the moderating effect of employee skill on the nexus between artificial intelligence (AI) adoption and loan management performance in the banking industry. With the increasing use of AI in financial processes like credit grading, fraud prevention, and loan disbursement, the human touch continues to play a critical role in ensuring the effective and ethical use of such technologies. This study takes a quantitative stance to establish the extent of employee knowledge that has an impact on the successful deployment of AI systems in loan management. Data were gathered from 400 bank professionals who were directly involved in digital loan processing and were analyzed through regression analysis. Employee competence is found to have a strong positive relationship with both AI integration (β = 0.800, p < 0.001) and loan approval performance (β = 0.823, p < 0.001), confirming that employees who have greater technical and analytical competence can utilize AI tools more efficiently. The research validates that worker competence positively moderates the impact between AI uptake and loan management performance, clearly reflecting the imperative for ongoing skill development and human–AI collaboration. The findings underscore that technological progress in itself is not adequate; good human capital development is equally important to attaining operational excellence in the digital banking environment.