Artificial Intelligence in Financial Inclusion: An Impact on Financial Accessibility and Efficiency in India

Abstract

This study explores the role of artificial intelligence (AI) in enhancing financial inclusion and bolstering government-led programs like the Pradhan Mantri Jan Dhan Yojana (PMJDY) and Direct Benefit Transfers (DBTs). Specifically, AI-driven technologies such as machine learning algorithms for credit scoring and automated transaction systems are instrumental in addressing challenges related to financial instability, fraud, and exclusion from formal financial services.Grounded in theoretical frameworks including the Technology Acceptance Model (TAM), Financial Inclusion Theory, Resource-Based View (RBV), and Fraud Triangle Theory, the research incorporates both primary data collected from 468 key stakeholders and secondary data obtained from authoritative sources like the Reserve Bank of India (RBI) and NITI Aayog. The findings reveal that AI significantly improves transparency and operational efficiency within these financial initiatives. However, its effectiveness in preventing fraudulent activities and enhancing financial literacy remains uncertain and warrants further investigation.Through Structural Equation Modeling (SEM), the study establishes a positive and meaningful relationship between AI adoption and increased financial inclusivity. To ensure sustainable economic development, future studies should prioritize the development of robust AI infrastructure, expansion of digital and financial literacy programs, and improved access to reliable internet services. These efforts are essential to fully leverage AI's potential in driving inclusive growth and long-term prosperity.This study explores the role of artificial intelligence (AI) in enhancing financial inclusion and bolstering government-led programs like the Pradhan Mantri Jan Dhan Yojana (PMJDY) and Direct Benefit Transfers (DBTs). Specifically, AI-driven technologies such as machine learning algorithms for credit scoring and automated transaction systems are instrumental in addressing challenges related to financial instability, fraud, and exclusion from formal financial services.Grounded in theoretical frameworks including the Technology Acceptance Model (TAM), Financial Inclusion Theory, Resource-Based View (RBV), and Fraud Triangle Theory, the research incorporates both primary data collected from 468 key stakeholders and secondary data obtained from authoritative sources like the Reserve Bank of India (RBI) and NITI Aayog. The findings reveal that AI significantly improves transparency and operational efficiency within these financial initiatives. However, its effectiveness in preventing fraudulent activities and enhancing financial literacy remains uncertain and warrants further investigation.Through Structural Equation Modeling (SEM), the study establishes a positive and meaningful relationship between AI adoption and increased financial inclusivity. To ensure sustainable economic development, future studies should prioritize the development of robust AI infrastructure, expansion of digital and financial literacy programs, and improved access to reliable internet services. These efforts are essential to fully leverage AI's potential in driving inclusive growth and long-term prosperity.