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AI Governance & Responsible Use in Financial Services
A practical guide to AI governance in financial services, covering FCA guidance, EU AI Act implications, responsible AI principles, and the regulatory framework for AI model risk management. Designed for compliance professionals and business users adopting AI tools.
3 modules, 9 lessons~30 minutes80% pass mark36 flipcards, 9 scenarios
CPD AlignedCertificate of Completion
This course content has been generated using AI and is based on publicly available regulatory guidance, including FCA discussion papers, the EU AI Act, and Bank of England publications. It is provided for educational purposes only. Your organisation's compliance team is responsible for verifying the accuracy and completeness of this material before it is used as part of your firm's official training programme. ComplySkills accepts no liability for regulatory decisions made based on this content.
What you will learn
- Understand the regulatory landscape for AI in your industry
- Identify key risks of AI including bias, transparency, and accountability
- Apply governance frameworks for responsible AI deployment
- Know your obligations around AI-generated decisions affecting customers
- Recognise when human oversight is required for AI systems
Who is this for?
All staff involved in AI adoption or oversight
Course details
Duration~30 min
Modules3
Lessons9
Pass mark80%
CertificateYes
CPD Hours0.5
Jurisdiction
UK and EU (EU AI Act). Principles applicable to any jurisdiction deploying AI systems.
Course Modules
1
AI in Financial Services
~10 minUnderstanding the regulatory landscape for AI in financial services, including FCA guidance, the EU AI Act, and AI risk categories.
FCA Guidance on AI/ML in Financial Services
AudioVisualFlipcardsScenario
EU AI Act Implications for UK Firms
AudioVisualFlipcardsScenario
AI Risk Categories and Use Cases in Finance
AudioVisualFlipcardsScenario
Assessment - 5 questions
2
Responsible AI Principles
~10 minCore principles of responsible AI including fairness, transparency, explainability, and data quality governance.
Fairness and Bias in AI Decision-Making
AudioVisualFlipcardsScenario
Transparency and Explainability Requirements
AudioVisualFlipcardsScenario
Data Quality and Governance for AI Systems
AudioVisualFlipcardsScenario
Assessment - 5 questions
3
Compliance & Governance
~10 minPractical governance frameworks for AI including model risk management, human oversight, and regulatory expectations.
AI Model Risk Management Framework
AudioVisualFlipcardsScenario
Human Oversight and Accountability
AudioVisualFlipcardsScenario
Regulatory Expectations: FCA, PRA, and Bank of England
AudioVisualFlipcardsScenario
Assessment - 5 questions
Total Questions
15
Pass Mark
80%
Audio
9/9
Certificate
Yes
v1.2.0 | Updated 2026-07-01 | Sources verified 2026-06-27
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