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Artificial Intelligence Applications in Banking and Financial Services

Anti Money Laundering and Compliance

  • Book
  • © 2023

Overview

  • Includes AI studies that impact entire anti-money laundering and compliance process in banks and financial institutions
  • Covers entire AI journey from Data to decisioning in bringing AI-driven efficiency in AML compliance
  • Contains pointers for both starter and practitioners using multiple AI-driven use cases from field experience

Part of the book series: Future of Business and Finance (FBF)

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Table of contents (11 chapters)

Keywords

About this book

This book discusses all aspects of money laundering, starting from traditional approach to financial crimes to artificial intelligence-enabled solutions. It also discusses the regulators approach to curb financial crimes and how syndication among financial institutions can create a robust ecosystem for monitoring and managing financial crimes. It opens with an introduction to financial crimes for a financial institution, the context of financial crimes, and its various participants. Various types of money laundering, terrorist financing, and dealing with watch list entities are also part of the discussion. Through its twelve chapters, the book provides an overview of ways in which financial institutions deal with financial crimes; various IT solutions for monitoring and managing financial crimes; data organization and governance in the financial crimes context; machine learning and artificial intelligence (AI) in financial crimes; customer-level transaction monitoring system; machine learning-driven alert optimization; AML investigation; bias and ethical pitfalls in machine learning; and enterprise-level AI-driven Financial Crime Investigation (FCI) unit. There is also an Appendix which contains a detailed review of various data sciences approaches that are popular among practitioners.

The book discusses each topic through real-life experiences. It also leverages the experience of Chief Compliance Officers of some large organizations to showcase real challenges that heads of large organizations face while dealing with this sensitive topic. It thus delivers a hands-on guide for setting up, managing, and transforming into a best-in-class financial crimes management unit. It is thus an invaluable resource for researchers, students, corporates, and industry watchers alike.

Authors and Affiliations

  • Effiya Technologies Private Limited, Singapore, Singapore

    Abhishek Gupta

  • Department of Economics and Finance, Cracow University of Economics, Kraków, Poland

    Dwijendra Nath Dwivedi

  • Effiya Technologies, Ahmedabad, India

    Jigar Shah

About the authors

Abhishek Gupta possess over 18 years of experience in analytics driven advisory, with focus on enterprise-wide risk management, forensics for financial crimes and corporate strategy. Abhishek was also the risk management expert for McKinsey & Co. and then with Sutra Management Consultancies, where he has successfully worked with over 30 banks and financial institutions on Risk and Compliance offerings, South East Asia, North America and Europe. Abhishek has been working with his team on new emerging technologies like text analytics, voice and image analytics. Academically, he has also been one of the co-inventors of a provisional patent on fraud management technology in India, authored few research papers in reputed journals and has been a visiting faculty for MBA colleges.

 

Dwijendra Nath Dwivedi is having over 17 years of experience in applying Artificial Intelligence and Advanced Analytics across different industries, e.g.BFSI, Government, Telco, and utilities in various functional areas, e.g. Risk and marketing. He conducts AI Value seminars and workshops, for the executive audience and for power users. He is currently leading Analytics and AI practice for EMEA at SAS and helps to enable organizations in applications of AI. As a thought leader, he is bridging the gap between business needs and analytical enablers and to drive analytical thinking into successful business strategies. He completed his MPhil. from Indira Gandhi Institute of Development and research. He is currently pursuing his PhD in AI from the Department of Economics and Finance from Krakow University of Economics.

 

Jigar Shah is a techno-management professional with 12 years of work experience into BFSI domain in business and analytics, consulting, IT services, project management and private equity. He carries hands-on experience in executing challenging assignments and consulting clients in areas of financial risk, compliance, and business intelligence. He has a rich experience in working with teams and clients across geographies.

Bibliographic Information

  • Book Title: Artificial Intelligence Applications in Banking and Financial Services

  • Book Subtitle: Anti Money Laundering and Compliance

  • Authors: Abhishek Gupta, Dwijendra Nath Dwivedi, Jigar Shah

  • Series Title: Future of Business and Finance

  • DOI: https://doi.org/10.1007/978-981-99-2571-1

  • Publisher: Springer Singapore

  • eBook Packages: Business and Management, Business and Management (R0)

  • Copyright Information: The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023

  • Hardcover ISBN: 978-981-99-2570-4Published: 21 July 2023

  • Softcover ISBN: 978-981-99-2573-5Due: 20 August 2023

  • eBook ISBN: 978-981-99-2571-1Published: 19 July 2023

  • Series ISSN: 2662-2467

  • Series E-ISSN: 2662-2475

  • Edition Number: 1

  • Number of Pages: XVI, 140

  • Number of Illustrations: 47 b/w illustrations, 4 illustrations in colour

  • Topics: Financial Engineering, Artificial Intelligence, Optimization, Criminology and Criminal Justice, general

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