AI-Powered Loan Recommendations for Self-Help Groups: Enhancing Financial Inclusion Through Machine Learning

This study aims to investigate the impact of artificial intelligence (AI) recommended loans on financial inclusion for self-help groups (SHGs) in Tamil Nadu. The research is grounded in the Financial Inclusion Framework and employs a hypothesis-driven approach. The null hypothesis posits that AI recommended loans have no significant impact on financial inclusion for SHGs, while the alternative hypothesis suggests a significant positive impact. The study's dependent variable is financial inclusion for SHGs in Tamil Nadu, measured through access to loans, savings, and other financial services. The primary independent variable is AI-recommended loans, specifically focusing on AI-powered loan recommendation systems. Additionally, digital literacy among SHG members is considered as a secondary independent variable, encompassing their ability to use digital devices and navigate online platforms. By examining the relationship between these variables, the research seeks to uncover the potential of AI-driven financial technologies in revolutionizing access to financial services for SHGs. This study's findings could have significant implications for policymakers, financial institutions, and technology developers in enhancing financial inclusion strategies for marginalized communities in Tamil Nadu and potentially other regions facing similar challenges. AI-powered loan recommendation systems use machine learning techniques, including decision trees and neural networks, to assess creditworthiness. These models analyze borrower history, financial behavior, and alternative credit data to ensure fair and optimized loan allocation.