Third-Party Risk Assessment with AI

A Comprehensive Guide for the Digital Age
1. Auflage 2027
ISBN: 978-1-041-37449-7
Verlag: CRC Press

Buch, Englisch, 272 Seiten, Format (B × H): 156 mm x 234 mm

Reports about major disruptions caused by third-party failures have made headlines globally. The CrowdStrike outage grounded airlines and shut down hospitals. The SolarWinds attack compromised thousands of organizations. The Ticketmaster breach exposed millions of customer records. These incidents demonstrate that third-party risks are not theoretical concerns - they are real, immediate threats that require systematic management.

Third-Party Risk Assessment with AI is a comprehensive, practitioner-oriented handbook to managing third-party risks in today’s digital economy. It explains how organizations can assess, monitor, and mitigate vendor, supplier, and ecosystem risks—especially as AI, cloud, and global supply chains reshape business models. The book features:

- Checklists, dashboards, risk scoring models, and governance playbooks ready for organizational use

- Tailored approaches for finance, healthcare, energy, retail, government, and education

- Practical applications of AI and ML in vendor intelligence, predictive risk modeling, and automated monitoring

The book takes readers from basic concepts to advanced implementation strategies. It starts with foundational knowledge, explores traditional and modern methodologies, examines regulatory requirements, and then dives deep into the transformative potential of AI in third-party risk management. With a focus on practical application and real-world relevance, the book is the professional’s guide for understanding how to use AI to manage more effectively and efficiently the risks posed by third-party vendors.

Zielgruppe

Professional Practice & Development and Professional Reference

Autoren/Hrsg.

Afzal, Hameed

Khan, Dan "Sage"

Khan, Haq Nawaz

Fachgebiete

• Mathematik | Informatik EDV | Informatik Technische Informatik Computersicherheit
• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz
• Wirtschaftswissenschaften Betriebswirtschaft Unternehmensfinanzen Controlling, Wirtschaftsprüfung, Revision

Inhaltsverzeichnis

1. Introduction to Third-Party Risk Assessment 2. The Critical Importance of TPRM in Modern Business 3. Understanding the Third-Party Risk Landscape 4. The Third-Party Risk Management Lifecycle 5. Traditional vs. Modern TPRM Methodologies 6. Industry-Specific TPRM Approaches 7. Global Regulatory Landscape for TPRM 8. International Standards and Frameworks 9. Vendor Classification and Criticality Frameworks 10. Building a Comprehensive TPRM Framework 11. The AI Revolution and Third-Party Risk 12. AI-Specific Risk Assessment Methodologies 13. Transforming the TPRM Lifecycle with AI 14. AI-Enhanced Due Diligence and Onboarding 15. Continuous Monitoring and Predictive Analytics 16. AI-Powered Contract Management and Compliance 17. TPRM Program Implementation Strategies 18. Organizational Change Management and Training 19. Measuring TPRM Program Effectiveness 20. Emerging Risks and Future Challenges 21. Quantum Computing Implications for TPRM 22. Future Trends and Strategic Recommendations 23. TPRM Tools, Templates, and Checklists 24. Excel Dashboards and Reporting Solutions 25. Industry-Specific Assessment Tools 26. Financial Services Case Studies 27. Technology and Manufacturing Case Studies 28. The Future of Third-Party Risk Management 29. Strategic Recommendations and Conclusion Appendix A: TPRM Assessment Templates and Checklists Appendix B: Regulatory Framework Summary Appendix C: Technology Implementation Guide Appendix D: Glossary of Terms Appendix E: Additional Resources and References Appendix F: Quick Start Guide and TPRM Maturity Self-Assessment Appendix G: Sample RFP/RFI Language for Vendor Security and Resilience

Über Autor(innen)

Hameed Afzal has more than seven years of specialized experience in operational technology (OT) cybersecurity and critical infrastructure protection, with a focus on energy, utility, and smart grid environments. He is an expert-level certified professional holding CISSP, CISM, PMP, CompTIA Security X (CASP+), and multiple ISO Lead Auditor credentials (ISO 27001, 27701, 22301, 20000, and 42001 for AI governance).

Muhammad Danyal (“Sage”) Khan is a Marie Sklodowska-Curie PhD Scholar at the University of Granada, specializing in secure and autonomous windfarms at the intersection of AI, blockchain, IoT, and critical infrastructure. He is the author of Open for Business: Harnessing the Power of Open-Source to Build Corporate IT Infrastructure (Taylor & Francis, USA) and Project Lead for the Linux Foundation’s DataOps initiative.

Haq Nawaz Khan is a technology consultant and cybersecurity professional with over 6 years of experience in information security, AI systems, and governance, risk, and compliance (GRC). He has worked across diverse domains including smart city initiatives, AI chatbot development, penetration testing, forensic analysis, and compliance consulting.