An Empirical Analysis of Challenges Faced by Rural Bank Customers in Health Sector Loans: Assessing the Impact of Emerging Technologies and AI Risks in Kolkata (West Bengal) and Mohanpur (Jharkhand)

Abstract

The integration of emerging technologies and artificial intelligence (AI) in the rural banking sector has revolutionized financial services, offering efficiency, automation, and enhanced decision-making capabilities. However, this rapid digital transformation has also posed significant challenges, particularly for rural customers seeking health sector loans in areas like Kolkata (West Bengal) and Mohanpur (Jharkhand). This study empirically analyzes the hurdles faced by rural borrowers due to the implementation of AI-driven credit assessments, digital banking barriers, cybersecurity risks, and financial literacy gaps. One of the primary concerns is the biased risk assessment by AI algorithms, which often disadvantage rural borrowers due to inadequate financial histories, limited digital footprints, and algorithmic opacity. Additionally, digital banking platforms, despite being promoted for their accessibility, often exclude individuals with low digital literacy, leading to difficulties in applying for and managing loans. This study also highlights the cybersecurity risks associated with AI-driven banking systems, where rural customers are more susceptible to fraud, phishing, and data breaches due to inadequate security awareness. From a legal standpoint, this paper examines the application of Indian laws such as the Reserve Bank of India (RBI) Guidelines on Digital Lending, 2022, which regulate AI-based credit disbursement and customer data protection. Furthermore, the Information Technology (IT) Act, 2000 plays a crucial role in addressing data security and privacy concerns in digital banking transactions. The Consumer Protection Act, 2019, is also relevant in cases where AI-driven loan decisions lead to unfair trade practices or financial discrimination. Moreover, the RBI's Fair Practices Code ensures transparency in lending practices, mandating that banks provide clear communication on loan terms and AI-based decision-making processes. This research employs an empirical methodology, combining field surveys and interviews with rural bank customers, financial institutions, and legal experts to assess the practical implications of AI integration in rural banking. The findings. reveal that while AI-driven credit assessment tools streamline loan processing, they often lack contextual awareness of rural socio-economic conditions, leading to loan denials or higher interest rates for rural borrowers. Moreover, financial illiteracy and the lack of regulatory awareness among customers further exacerbate challenges, creating a digital divide in financial accessibility.The study concludes by suggesting policy interventions, such as enhanced regulatory oversight on AI-powered financial systems, robust consumer awareness programs, and AI transparency mandates, to ensure equitable access to health sector loans in rural banking. Strengthening legal frameworks, improving AI accountability, and bridging the digital divide are crucial to achieving financial inclusion in India's rural banking sector.