Paper Title
ARTIFICIAL INTELLIGENCE IN BANKING AND FINANCIAL SERVICES: IMPACT ON CUSTOMER EXPERIENCE, EMPLOYEE PERFORMANCE, FRAUD DETECTION, AND OPERATIONAL EFFICIENCY
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Registration ID: IJNRD_327466
Published ID: IJNRD2607419
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Abstract
The global banking and financial services sector is undergoing a profound paradigm shift driven by the rapid deployment of Artificial Intelligence (AI), Machine Learning (ML), Natural Language Processing (NLP), and Generative AI technologies. This research paper offers an exhaustive, empirical, and multi-dimensional analysis of AI’s transformational impact across four vital pillars of banking: Customer Experience (CX), Employee Performance and HR Transformation, Fraud Detection and Risk Management, and Back-Office Operational Efficiency. Utilizing a comprehensive methodology combining qualitative thematic analysis, quantitative performance metrics, and industry case studies from leading international and Indian financial institutions (including JPMorgan Chase, DBS Bank, HDFC Bank, and State Bank of India), this study evaluates how AI integration enhances operational capabilities while addressing strategic and ethical challenges. Our findings indicate that AI-driven hyper-personalization, conversational bots, and automated omnichannel management increase customer satisfaction scores (CSAT) by 28% to 35% and reduce service churn significantly. Concurrently, AI assistance in HR and workforce analytics optimizes talent acquisition, boosts employee productivity through automated workflows, and reshapes workplace dynamics, though it requires extensive workforce reskilling. In risk management, real-time ML anomaly detection and predictive analytics achieve fraud detection accuracy exceeding 94%, sharply reducing false positives compared to legacy rule-based systems. Furthermore, robotic process automation (RPA) combined with Intelligent Document Processing (IDP) curtails back-office processing costs by 30–50% and accelerates loan origination timelines from days to minutes. Despite these vast advantages, financial institutions face formidable implementation hurdles, including algorithmic bias, data privacy compliance (GDPR, India's DPDP Act), systemic cybersecurity threats, and model explainability issues (Black-Box dilemma). This paper presents a strategic governance roadmap, ethical guidelines, and future technology outlooks (including Quantum AI and Central Bank Digital Currencies) to help financial leaders navigate the AI-driven future responsibly.
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How To Cite (APA)
Puint Dhurve, Vishal Nikure, & Pradip Hedau (July-2026). ARTIFICIAL INTELLIGENCE IN BANKING AND FINANCIAL SERVICES: IMPACT ON CUSTOMER EXPERIENCE, EMPLOYEE PERFORMANCE, FRAUD DETECTION, AND OPERATIONAL EFFICIENCY. INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT, 11(7), e192-e201. https://ijnrd.org/papers/IJNRD2607419.pdf
Issue
Volume 11 Issue 7, July-2026
Pages : e192-e201
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Paper Reg. ID: IJNRD_327466
Published Paper Id: IJNRD2607419
Research Area: Other area not in list
Author Type: Indian Author
Country: Pandurna, MADHYA PRADESH, India
Published Paper PDF: https://ijnrd.org/papers/IJNRD2607419.pdf
Published Paper URL: https://ijnrd.org/viewpaperforall?paper=IJNRD2607419
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