The RAISE Framework

Description

When AI Touches the Numbers, Governance Is No Longer Optional.

 

Most organizations know AI is changing financial reporting but very few have governance structures that keep pace with it. The RAISE Framework closes that gap with a structured, practical governance model built on five integrated principles – Responsible, Auditable, Interpretable, Secure, and Ethical – purpose-built for the financial reporting and audit environment.

 

The book moves through six parts covering governance misalignment, regulatory context, control failure, operational risk, and governance design. Real-world case studies from Zillow, Wirecard, and the Post Office Horizon system show how governance failures develop, how financial risk accumulates, and how organizations recover control.

 

What you will learn

● Identify governance misalignment when AI executes financial decisions, while boards and executives retain accountability.

● Apply the RAISE Framework to embed AI governance within financial reporting and audit control structures.

● Evaluate AI control failure patterns including automation bias, model drift, vendor dependency, and judgment override.\

 

Table of Contents

1. Governance Misalignment

2. Restoring Control and Accountability

3. AI Decision Ownership and Accountability

4. AI Governance Frameworks and Control Standards

5. AI Impact on Financial Reporting Processes

6. AI in Audit Practice and Governance

7. AI Control Failure and Governance Breakdown

8. Evidence, Risk, and Assurance of AI Control

9. Financial AI Systems in Practice

10. AI Assurance: Redefining Audit Processes

11. Vendor Control in AI Governance

12. Judgment Overrides in AI Systems

13. Governance Patterns and Control Integration

14. Case Studies in AI Governance Failure and Control Recovery

15. Audit Readiness, Evidence Quality, and Governance Effectiveness

16. The RAISE Governance Model

17. RAISE Lifecycle Governance

18. First 90 Days of AI Governance