American Journal of Advanced Multidisciplinary Research and Innovation

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A Widely Indexed Open Access Peer Reviewed Multidisciplinary Bi-monthly Scholarly International Journal

Call for Paper Volume 8, Issue 5 (September-October 2026) Submit your research before last 3 days of October to publish your research paper in the issue of September-October.

AI-Enabled Financial Services: Transforming Risk Management, Fraud Detection and Customer-Centric Banking

Author(s) Dennis Wall
Country United States
Abstract Artificial Intelligence (AI) is fundamentally transforming the financial-services industry by enabling institutions to process large volumes of structured and unstructured data, identify complex patterns, automate decision-making, and deliver increasingly personalised financial services. Traditional banking systems often rely on predefined rules, historical information, and manual processes, which can be insufficient for detecting sophisticated fraud, assessing dynamic financial risks, and responding to rapidly changing customer expectations. AI technologies, including machine learning, deep learning, natural language processing, anomaly detection, and predictive analytics, provide new capabilities for risk management, fraud detection, credit assessment, customer segmentation, personalised financial products, and intelligent customer service. This study examines the role of AI in transforming financial services, with particular emphasis on risk management, fraud detection, and customer-centric banking. A qualitative and conceptual research methodology is adopted through an examination of academic literature and emerging technological applications. The study analyses AI applications in credit risk assessment, market and operational risk, anti-money-laundering systems, transaction monitoring, fraud detection, customer experience, chatbots, personalised recommendations, and financial inclusion. The findings indicate that AI can improve the speed, accuracy, scalability, and adaptability of financial decision-making. However, significant challenges remain, including algorithmic bias, lack of explainability, data privacy, cybersecurity, regulatory compliance, model risk, and overdependence on automated systems. The study concludes that responsible AI governance, human oversight, transparent models, high-quality data, and continuous monitoring are essential for ensuring that AI-enabled financial services remain secure, fair, trustworthy, and customer-centric.
Keywords Artificial Intelligence, Financial Services, Banking, Risk Management, Fraud Detection, Machine Learning, Credit Risk, Customer Experience, Financial Technology, Digital Banking.
Field Engineering
Published In Volume 5, Issue 2, March-April 2023
Published On 2023-03-15

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