AI and Machine learning in Banking: Driving Efficiency and Innovation
Keywords:
Bank innovation, AI fraud detection, Risk management, Machine learning, AI-powered banking.Abstract
The banking industry is being radically transformed by artificial intelligence (AI) and machine learning (ML), which are spurring a move toward increased operational effectiveness, creativity, and customer-centricity. The revolutionary effects of AI/ML technology on banking procedures, client interaction, risk management, and regulatory compliance are methodically examined in this paper. Using a mixed-methods approach, the study combines quantitative assessment of AI/ML performance across three significant banking case studies, covering more than 1.2 million transactions, with thematic analysis of 85 peer-reviewed papers. With processing times reduced by 62% and loan approval error rates falling from 8.3% to 1.1%, the results show that AI-driven automation lowers manual processing errors and time. With an accuracy rate of 98.7%, machine learning (ML)-based fraud detection systems outperformed conventional rule-based systems and resulted in significant cost savings. AI-powered customer personalization projects raised satisfaction scores by 22% and product uptake rates by 34%. ML models increased the accuracy of credit default prediction in risk management (AUC-ROC: 0.78–0.93), allowing for more stable portfolio management. Notwithstanding these developments, issues with data quality, algorithmic bias, legacy system integration, and regulatory compliance still exist. The study emphasizes how crucial it is for banks to make strategic investments in personnel reskilling, ethical AI frameworks, and infrastructure modernization. As it identifies research gaps in ethical governance, cross-market generalizability, and the long-term societal impact of AI adoption in financial services, the study ends by describing future directions for AI/ML in banking, with a focus on hyper-personalization, advanced fraud prevention, and inclusive credit scoring.
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