Artificial Intelligence Applications in Banking and Financial Services: Anti Money Laundering and Compliance
Gupta, Abhishek, Dwivedi, Dwijendra Nath, Shah, Jigar
相關主題
商品描述
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.
商品描述(中文翻譯)
本書探討洗錢的各個面向，從傳統的金融犯罪方法到人工智慧驅動的解決方案。它還討論了監管機構如何應對金融犯罪，以及金融機構之間的聯合如何創造一個強健的生態系統，以監控和管理金融犯罪。書中首先介紹了金融機構的金融犯罪背景、金融犯罪的情境及其各種參與者。各類型的洗錢、恐怖主義融資以及處理監控名單實體的議題也在討論之中。透過十二章的內容，本書提供了金融機構如何應對金融犯罪的概述；各種監控和管理金融犯罪的IT解決方案；在金融犯罪背景下的數據組織和治理；機器學習和人工智慧（AI）在金融犯罪中的應用；客戶層級的交易監控系統；基於機器學習的警報優化；反洗錢調查；機器學習中的偏見和倫理陷阱；以及企業級的AI驅動金融犯罪調查（FCI）單位。此外，還附有一個附錄，詳細回顧了在實務中受歡迎的各種數據科學方法。
本書通過真實的案例經驗來討論每個主題。它還利用一些大型組織的首席合規官的經驗，展示大型組織在處理這一敏感主題時所面臨的真實挑戰。因此，本書提供了一個實用的指南，幫助設立、管理和轉型為最佳金融犯罪管理單位。對於研究人員、學生、企業和行業觀察者而言，這都是一個無價的資源。
作者簡介
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.
作者簡介(中文翻譯)
Abhishek Gupta 擁有超過 18 年的分析驅動顧問經驗，專注於企業範圍的風險管理、金融犯罪的取證以及企業策略。Abhishek 曾擔任麥肯錫公司的風險管理專家，之後在 Sutra Management Consultancies 工作，成功與超過 30 家銀行和金融機構合作，提供風險與合規服務，涵蓋東南亞、北美和歐洲。Abhishek 與他的團隊一直在研究新興技術，如文本分析、語音和影像分析。在學術方面，他也是印度一項關於詐騙管理技術的臨時專利的共同發明人，並在知名期刊上發表過幾篇研究論文，還曾擔任 MBA 學院的客座教授。
Dwijendra Nath Dwivedi 擁有超過 17 年的經驗，專注於在不同產業（如 BFSI、政府、電信和公用事業）中應用人工智慧和高級分析，涵蓋風險和行銷等多個功能領域。他為高層管理人員和專業用戶舉辦 AI 價值研討會和工作坊。目前，他在 SAS 負責 EMEA 的分析和 AI 實踐，幫助組織應用 AI。作為一位思想領袖，他在商業需求與分析驅動因素之間架起橋樑，推動分析思維融入成功的商業策略。他在印度甘地學院完成了碩士研究，並目前在克拉科夫經濟大學的經濟與金融系攻讀人工智慧的博士學位。
Jigar Shah 是一位技術管理專業人士，在 BFSI 領域擁有 12 年的工作經驗，涵蓋商業與分析、顧問、IT 服務、專案管理和私募股權。他在執行挑戰性任務和為客戶提供金融風險、合規和商業智慧等領域的諮詢方面擁有豐富的實務經驗。他在與不同地區的團隊和客戶合作方面也有著豐富的經驗。
