FutureCentral > AI in Banking: The Guide for Banking Professionals
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Banking & Financial Services · Working Professionals

AI in Banking

The Guide for Banking Professionals

Austin PM · FutureCentral Press

AI in banking for working banking professionals.

Working ProfessionalsManuscript chapters available
Explore the bookInquire about this bookView contents
AudienceWorking Professionals
Structure28 chapters listed
StatusManuscript chapters available

About the book

For working banking professionals, AI raises practical questions about credit, customer channels, treasury, trade finance, and financial crime. The book examines application choices alongside data architecture, engineering, operational controls, and the consequences of automated customer-facing decisions.

What you will learn

  • Evaluate banking AI use cases
  • Connect data foundations with banking decisions
  • Design controlled agentic workflows
  • Assess customer, operational and model risks
Read before you decide

Explore the book

Chapter overview

Inside Chapter 1

Chapter topics, summarized from “The Rise of AI in Banking”:

  • Explain how successive waves of AI build on earlier banking systems.
  • Use the three-wave framework to interpret banking applications.
  • Trace changes in Indian banking from computerization to generative and agentic AI.

Preview and inspection

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Frameworks and decision tools

The Three-Wave Banking Architecture

Introduced in Chapter 1.

The Banking ML Decision Stack

Introduced in Chapter 2.

The Indian Banking Data Fabric, five layers and their owners

Introduced in Chapter 3.

The AI Investment Thesis Architecture

Introduced in Chapter 4.

The Retail Credit Underwriting Architecture

Introduced in Chapter 5.

The Corporate and MSME Credit Architecture

Introduced in Chapter 6.

Table of contents

View all 28 chapters

Contents reflect available source documents. Final publication details remain unconfirmed.

  1. The Rise of AI in Banking
  2. Machine Learning and Deep Learning in Banking
  3. Data, Digital Signals, and the AI Infrastructure of Banking
  4. The Strategic Logic of AI Adoption in Banking
  5. AI in Retail Lending and Credit Underwriting
  6. AI in Corporate, MSME, and Working Capital Credit
  7. AI in Branch and Channel Operations
  8. AI in Treasury, ALM, and Bank-Internal Markets Operations
  9. AI in Trade Finance, Transaction Banking, and Payments
  10. AI in Agricultural, Rural, and Cooperative Banking
  11. Credit Risk Models in the AI Era
  12. Fraud, AML, and Financial Crime Analytics
  13. KYC, Customer Due Diligence, and Onboarding
  14. Operational Risk, Cybersecurity, and AI-Driven Threats in Banking
  15. What Generative AI Means for the Bank
  16. LLMs in the Banking Workflow
  17. Limits and Risks of Generative AI in Banking
  18. From Banking Assistants to Banking Agents
  19. Agent Engineering: Tools, Identity, Memory and the Multi-Agent Bank
  20. Agentic Risk, Security and Containment
  21. Agentic Workflows in Practice
  22. Customer-Facing and Revenue-Side Agents
  23. Governance, Model Risk, and Responsible AI in Banking
  24. Regulation, Compliance, and the FREE-AI Architecture
  25. Cybersecurity, Privacy, and AI in Banking
  26. The Role-by-Role Transformation
  27. Skills, Credentials, and the Career Architecture of the AI-First Bank
  28. The Future of the Indian Bank, Strategy and Transformation
Student and faculty companions

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