Transforming Financial Services with Generative AI: From Strategy and Design to Practical Applications
暫譯: 以生成式 AI 轉型金融服務：從策略與設計到實務應用

Godavarthi, Srinath, Nagvekar, Ravi

Transforming Financial Services with Generative AI: From Strategy and Design to Practical Applications
  • 出版商: Apress
  • 出版日期: 2025-12-15
  • 售價: $2,400
  • 貴賓價: 9.5 折 $2,280
  • 語言: 英文
  • 頁數: 325
  • 裝訂: Quality Paper - also called trade paper
  • ISBN: 9798868820526
  • ISBN-13: 9798868820526
  • 相關分類: ChatGPT

    • 海外代購書籍(需單獨結帳)

相關主題

商品描述

Generative AI (GenAI) is revolutionizing the financial services sector (FSS), offering new ways to enhance efficiency, improve customer experiences, and streamline operations. This book is your comprehensive guide to understanding and implementing GenAI within FSS.

Grounded in real-world use cases, this book moves from fundamentals to boardroom-ready execution. You'll start with the core concepts behind AI, machine learning, and GenAI, then pivot into the challenges of FSS: intense regulatory scrutiny, evolving fraud threats, operational complexity, and rising expectations for personalized, always-on service. You'll learn a practical blueprint for GenAI adoption, including strategy, governance, risk controls, data readiness, and culture--through the lens of executives tasked with delivering measurable value responsibly.

From there, you'll get hands-on experience building GenAI systems: prompt design, evaluation, Retrieval-Augmented Generation (RAG), fine-tuning, and agentic workflows. You'll see how these capabilities power mission-critical functions across the enterprise: Finally, you'll operationalize all of it with modern FMOps/LLMOps practices--security, privacy, performance, cost management, monitoring, and continuous improvement--so pilots become production systems that scale. The closing chapter distills emerging trends, from autonomous agents to domain-specialized models, and lays out next steps so your organization can adopt GenAI with confidence, compliance, and a clear return on investment.

Whether you're a CIO crafting a roadmap, a product leader shipping AI features, a data scientist building RAG pipelines, or a risk and compliance executive seeking control and clarity, this book is your end-to-end guide to deploying GenAI that is safe, explainable, and enterprise-grade.

What You Will Learn

    Develop a strategic blueprint for GenAI adoption, including implementation methodologies, risk mitigation, and best practices for financial institutions Master the core components of building GenAI applications, from prompt engineering and model evaluation to RAG and Agentic AI

    Discover how GenAI transforms risk and compliance management, including applications in Anti-Money Laundering (AML), trade surveillance, and regulatory reporting
    Explore practical GenAI use cases across retail banking, investment banking, and wealth management, and learn about successful operational deployment
Who This Book Is For

Data scientists, AI professionals, and financial services experts interested in leveraging generative AI within the financial sector.

商品描述(中文翻譯)

生成式人工智慧（Generative AI, 簡稱 GenAI）正在徹底改變金融服務業（Financial Services Sector, 簡稱 FSS），提供提升效率、改善客戶體驗和簡化操作的新方法。本書是您理解和實施 GenAI 在 FSS 中的全面指南。

本書以真實案例為基礎，從基本概念到高層執行，逐步深入。您將從人工智慧（AI）、機器學習（machine learning）和 GenAI 的核心概念開始，然後轉向 FSS 面臨的挑戰：嚴格的監管審查、不斷演變的詐騙威脅、操作複雜性以及對個性化、隨時可用服務的日益期望。您將學習到一個實用的 GenAI 採用藍圖，包括策略、治理、風險控制、數據準備和文化，這些都是從負責提供可衡量價值的高層管理者的視角出發。

接下來，您將獲得構建 GenAI 系統的實踐經驗：提示設計、評估、檢索增強生成（Retrieval-Augmented Generation, RAG）、微調和代理工作流程。您將看到這些能力如何推動企業內的關鍵任務功能：最後，您將通過現代的 FMOps/LLMOps 實踐來運營這一切——安全性、隱私、性能、成本管理、監控和持續改進——使試點項目轉變為可擴展的生產系統。結尾章節提煉出新興趨勢，從自主代理到專業領域模型，並列出下一步行動，以便您的組織能夠自信、合規地採用 GenAI，並獲得明確的投資回報。

無論您是制定路線圖的首席資訊官（CIO）、推出 AI 功能的產品負責人、構建 RAG 管道的數據科學家，還是尋求控制和清晰度的風險與合規高管，本書都是您部署安全、可解釋且企業級的 GenAI 的全方位指南。

您將學到的內容：

- 制定 GenAI 採用的戰略藍圖，包括實施方法、風險緩解和金融機構的最佳實踐
- 掌握構建 GenAI 應用的核心組件，從提示工程和模型評估到 RAG 和代理 AI

- 探索 GenAI 如何轉變風險和合規管理，包括在反洗錢（Anti-Money Laundering, AML）、交易監控和監管報告中的應用

- 探索零售銀行、投資銀行和財富管理中的實用 GenAI 用例，並了解成功的操作部署

本書適合對在金融領域利用生成式人工智慧感興趣的數據科學家、AI 專業人士和金融服務專家。

作者簡介

Srinath Godavarthi has over 20 years of experience in the IT industry serving both public sector and commercial customers. He held leadership positions with global technology and consulting companies including Amazon and Accenture. In his previous roles, Srinath led digital transformation for a number of customers across multiple industry verticals including Financial Services, Healthcare and Telecommunications. Srinath is an accomplished author, specializes in GenAI, AI/ML technologies and published over a dozen white papers and blogs. He has been a speaker at various industry conferences including Generative AI summits, AWS Public sector summit, AWS re: Invent, American public Human Services association among others. He holds a Master's degree in Computer Science from Temple University and a Chief Technology Officer program from the University of California, Berkeley. Srinath is deeply passionate about causes that impact Veterans and kids. In his spare time, he volunteers to help Veterans and enables the next generation by teaching AI/ML technologies to high school students and assisting them with research projects.

Dr Ravi Nagvekar is a seasoned technology professional with more than 20 years of experience in the IT and finance domains, having worked with some of the world's leading financial institutions, including JP Morgan Chase, ABN Amro, ICICI Bank, HDFC Bank, and Bank of Baroda. His extensive expertise spans across multiple areas, such as generative AI, machine learning, data engineering, and cloud solutions. Currently, Ravi is part of Amazon Web Services (AWS), where he supports some of the largest financial clients in the Americas, focusing on generative AI and machine learning implementations. Prior to his role at AWS, he led the Analytics and Machine Learning Platform Engineering team at JP Morgan Chase, driving innovation and enabling advanced analytics capabilities for the bank's strategic initiatives. Ravi has presented at numerous AWS Summits, Latin American summits, and client events, sharing his insights on AI/ML and generative AI, and is recognized for his thought leadership in the field. He is also the inventor of a patented cloud-agnostic data mesh, demonstrating his ability to create cutting-edge solutions that address complex data challenges. Academically, Ravi holds a aster's degree in Technology Management from the University of Arizona and a master's degree in Computer Management from the University of Pune. He also completed a Postgraduate Diploma from the Columbia Technical Institute. Currently, Ravi is pursuing a Doctorate, with his research focusing on the impact of generative AI on the financial industry. With a passion for continuous learning, Ravi stays at the forefront of emerging technologies, constantly exploring new developments in AI and cloud computing. In his spare time, he enjoys spending quality time with his family and exploring new places around the world.

Mandy Kinne is a Technical Editor, who has been an integral part of our team. Mandy has a passion for language and technology. She loves connecting with people from diverse backgrounds and working with people across cultures, which taught her the power of sharing knowledge through words and illustrations. Mandy has been working with AI and its precursors, in some form, since 1994, when she was employed by the Center for Machine Translation at Carnegie Mellon University. Mandy has been a technical writer in a variety of industries--health insurance, telecom and computer networking and hardware--and before becoming a freelancer, she worked at a fintech company. She holds BAs in Rhetoric and French from Carnegie Mellon University and is active in the Write the Docs technical writing community. Mandy volunteers with the NOVA Roller Derby, serves as the Communications Chair for her fiber art guild, and is always knitting or spinning something.

作者簡介(中文翻譯)

Srinath Godavarthi 在資訊科技產業擁有超過 20 年的經驗，服務於公共部門和商業客戶。他曾在包括 Amazon 和 Accenture 在內的全球科技和諮詢公司擔任領導職位。在之前的職位中，Srinath 為多個行業的客戶（包括金融服務、醫療保健和電信）主導數位轉型。Srinath 是一位成就卓越的作者，專注於生成式人工智慧（GenAI）、人工智慧/機器學習（AI/ML）技術，並發表了十多篇白皮書和部落格文章。他曾在各種行業會議上演講，包括生成式 AI 峰會、AWS 公共部門峰會、AWS re:Invent、美國公共人力服務協會等。他擁有天普大學的計算機科學碩士學位，以及加州大學伯克利分校的首席技術官課程。Srinath 對影響退伍軍人和兒童的事業充滿熱情。在空閒時間，他志願幫助退伍軍人，並通過教授 AI/ML 技術來啟發下一代，協助高中生進行研究項目。

Dr Ravi Nagvekar 是一位經驗豐富的技術專業人士，在資訊科技和金融領域擁有超過 20 年的經驗，曾與一些全球領先的金融機構合作，包括 JP Morgan Chase、ABN Amro、ICICI Bank、HDFC Bank 和 Bank of Baroda。他的專業知識涵蓋多個領域，如生成式 AI、機器學習、數據工程和雲端解決方案。目前，Ravi 是 Amazon Web Services (AWS) 的一員，支持美洲一些最大的金融客戶，專注於生成式 AI 和機器學習的實施。在加入 AWS 之前，他在 JP Morgan Chase 領導分析和機器學習平台工程團隊，推動創新並為銀行的戰略計劃提供先進的分析能力。Ravi 曾在多個 AWS 峰會、拉丁美洲峰會和客戶活動中發表演講，分享他對 AI/ML 和生成式 AI 的見解，並因其在該領域的思想領導力而受到認可。他還是專利雲中立數據網格的發明者，展示了他創造尖端解決方案以應對複雜數據挑戰的能力。在學術上，Ravi 擁有亞利桑那大學的技術管理碩士學位和普納大學的計算機管理碩士學位。他還完成了哥倫比亞技術學院的研究生文憑。目前，Ravi 正在攻讀博士學位，研究重點是生成式 AI 對金融行業的影響。Ravi 對持續學習充滿熱情，始終站在新興技術的最前沿，不斷探索 AI 和雲計算的新發展。在空閒時間，他喜歡與家人共度美好時光，並探索世界各地的新地方。

Mandy Kinne 是一位技術編輯，對我們的團隊至關重要。Mandy 對語言和技術充滿熱情。她喜歡與來自不同背景的人交流，並與不同文化的人合作，這讓她體會到通過文字和插圖分享知識的力量。自 1994 年以來，Mandy 就以某種形式與 AI 及其前身合作，當時她在卡內基梅隆大學的機器翻譯中心工作。Mandy 曾在多個行業擔任技術作家，包括健康保險、電信和計算機網絡及硬體，並在成為自由工作者之前，曾在一家金融科技公司工作。她擁有卡內基梅隆大學的修辭學和法語學士學位，並活躍於 Write the Docs 技術寫作社群。Mandy 參與 NOVA 滾輪壘球，擔任她的纖維藝術公會的通訊主席，並總是忙於編織或紡紗。

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