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Artificial Intelligence for Risk Mitigation in the Financial Industry
Ambrish Kumar Mishra (Edited by), Mishra (Author), Shweta Anand (Edited by), Narayan C. Debnath (Edited by), Purvi Pokhariyal (Edited by), Archana Patel (Edited by)
9781394174713, Wiley
Hardback, published 6 June 2024
384 pages
22.9 x 15.2 x 2.4 cm, 0.862 kg
Artificial Intelligence for Risk Mitigation in the Financial Industry This book extensively explores the implementation of AI in the risk mitigation process and provides information for auditing, banking, and financial sectors on how to reduce risk and enhance effective reliability. The applications of the financial industry incorporate vast volumes of structured and unstructured data to gain insight into the financial and non-financial performance of companies. As a result of exponentially increasing data, auditors and management professionals need to enhance processing capabilities while maintaining the effectiveness and reliability of the risk mitigation process. The risk mitigation and audit procedures are processes involving the progression of activities to “transform inputs into output.” As AI systems continue to grow mainstream, it is difficult to imagine an aspect of risk mitigation in the financial industry that will not require AI-related assurance or AI-assisted advisory services. AI can be used as a strong tool in many ways, like the prevention of fraud, money laundering, and cybercrime, detection of risks and probability of NPAs at early stages, sound lending, etc. Audience This is an introductory book that provides insights into the advantages of risk mitigation by the adoption of AI in the financial industry. The subject is not only restricted to individuals like researchers, auditors, and management professionals, but also includes decision-making authorities like the government. This book is a valuable guide to the utilization of AI for risk mitigation and will serve as an important standalone reference for years to come.
Preface xvii 1 Artificial Intelligence in Risk Management 1 2 Application of Artificial Intelligence in Risk Assessment and Mitigation in Banks 27 3 Artificial Intelligence and Financial Risk Mitigation 53 4 Artificial Intelligence Adoption in the Indian Banking and Financial Industry: Current Status and Future Opportunities 81 5 Impact of AI Adoption in Current Trends of the Financial Industry 103 6 Artificial Intelligence Applications in the Indian Financial Ecosystem 133 7 The Extraction of Features That Characterize Financial Fraud Behavior by Machine Learning Algorithms 159 8 A New Surge of Interest in the Cybersecurity of VIP Clients is the First Step Toward the Return of the Previously Used Positioning Practice in Domestic Private Banking 187 9 Determinants of Financial Distress in Select Indian Asset Reconstruction Companies Using Artificial Neural Networks 209 10 The Framework of Feature Extraction for Financial Fraud Behavior and Applications 229 11 Real-Time Analysis of Banking Data with AI Technologies 261 12 Risks in Amalgamation of Artificial Intelligence with Other Recent Technologies 289 13 Exploring the Role of ChatGPT in the Law Enforcement and Banking Sectors 327 References 345 Index 349
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Subject Areas: Computer science [UY]
