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Full Description
The financial sector is at a pivotal juncture, grappling with unprecedented AI integration alongside mounting regulatory scrutiny.
Despite the abundance of technical resources, there remains a significant gap in accessible governance models tailored to the financial context. This book fills that void, providing practical guidelines and frameworks that align technological innovation with legal, ethical, and societal considerations. AI and ML Governance in Financial Services presents a comprehensive governance blueprint tailored specifically for financial institutions navigating the rapid evolution of artificial intelligence (AI) and machine learning (ML). As AI-driven tools become integral to decision-making, risk management, and customer engagement, the need for effective, ethical, and compliant governance frameworks has never been greater.
This book aims to empower financial leaders, compliance officers, data scientists, academia, and regulators to implement responsible AI practices that foster innovation while safeguarding against risks and promoting equity.
Contents
Overview of Book Structure and Key Themes. Chapter 1: Introduction—The Governance Imperative. Chapter 2: Frameworks for Governing AI and ML. Chapter 3: AI-Enabled Threat Actors and Systemic Risk. Chapter 4: AI Bias in Financial Services—Risks, Regulations, and Mitigation Strategies. Chapter 5: Model Risk Management (MRM) and Validation. Chapter 6: Data Privacy, Consent, and Consumer Protections. Chapter 7: AI Ethics and Internal Oversight Structures—Mitigating Bias in Financial AI. Chapter 8: Navigating the Regulatory Landscape of AI in Financial Services. Chapter 9: Designing Trustworthy AI Systems in Financial Services—A Comprehensive Framework. Chapter 10: AI Governance, AI Risk Evaluation, and Future Outlook and Case Studies.
