AI IMPLEMENTATION IN DIGITAL PAYMENT: AN EMPIRICAL ANALYSIS ON BANKING SECTOR IN INDIA

Abstract

To study AI Implementation in Digital Payment, as an empirical analysis on Banking Sector in India. Questionnaires comprised of closed-ended questions were given out in order to accomplish these objectives. The elements of the proposed model were evaluated using the validity, correlation, and reliability analyses. Regression analysis was used to confirm the proposed model and test the hypothesis further. Findings shows Thus, with a R square of 0.813, all variables account for 90% of the digital payment system. The regression model's ANOVA values show validation with a 95% confidence level. In the coefficient summary, the beta values of every factor are 0.902, which is a fair depiction of their impact on Digital Payment system. Practitioners and marketers in the Indian banking industry might benefit from the insights this research offers. We encourage banking professionals to think about improving their usage of AI in the credit scoring, analysis, and granting processes in order to decrease risk, save costs, and enhance customer experience. This will help with the deployment of AI-based decision-making. In addition to enabling banks to automate their knowledge workers, artificial intelligence (AI) will make automation more intelligent overall, eliminating competitiveness and security dangers. Banks will be able to provide individualized services and increase operational and financial savings by making the most use of human and machine capabilities thanks to AI. As AI is used more widely in banking, authorities working to maintain financial stability while improving consumer protection and fostering innovation will face both new opportunities and difficulties. It offers the banking industry fantastic chances to improve customer experience democratize financial services, bolster risk management, and better cyber-security and consumer protection.