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Regulatory Compliance Checklist: AI Implementation in Financial Services
Executive Summary
This comprehensive checklist ensures UK financial services firms comply with all relevant regulations when implementing AI technologies. Based on the latest guidance from the FCA, PRA, Bank of England, and applicable UK/EU legislation as of August 2025.
Key Regulatory Framework
FCA AI Update (April 2024) and 5-Year Strategy (March 2025)
PRA/Bank of England Strategic Approach to AI (April 2024)
UK Government AI White Paper and 5 Principles
Consumer Duty (July 2023)
GDPR and UK Data Protection Act 2018
Financial Services and Markets Act 2023
Section 1: FCA Regulatory Requirements
1.1 Consumer Duty Compliance - HIGH PRIORITY
Consumer Outcomes Focus
Price and Value: AI implementation delivers fair value to consumers
Products and Services: AI-enhanced products meet consumer needs
Consumer Understanding: Clear communication about AI use to clients
Consumer Support: AI systems enable, not hinder, customer support
Evidence Required:
  • Consumer outcome testing results
  • AI impact assessment on customer journeys
  • Communication materials explaining AI use
  • Monitoring dashboard for consumer outcomes
1.2 Senior Managers & Certification Regime (SMCR) - HIGH PRIORITY
Accountability Framework
Senior Manager responsibility assigned for AI governance
Prescribed Responsibility (PR) clearly allocated for AI systems
Management Information includes AI risk reporting
Certification Regime covers AI-related roles where applicable
Documentation:
  • SMCR mapping document updated to include AI responsibilities
  • Senior Manager attestation on AI governance effectiveness
  • Management information pack includes AI metrics
  • Job descriptions updated for AI-related certified functions
  • 1.3 Treating Customers Fairly (TCF) & Market Conduct - MEDIUM PRIORITY
Fair Treatment Principles
  • AI systems support fair customer treatment outcomes
  • No discriminatory bias in AI decision-making
  • Vulnerable customer protections maintained
  • Clear redress mechanisms for AI-driven decisions
Market Conduct:
  • AI systems cannot manipulate market prices
  • Front-running prevention controls in place
  • Best execution maintained with AI-assisted trading
  • Market abuse detection enhanced, not compromised
1.4 FCA's Technology Approach & Innovation - ONGOING
FCA's 5-Year Strategy Alignment
  • AI implementation supports "tech-positive approach"
  • Innovation contributes to market competition
  • Technology enhances financial inclusion
  • AI use builds market confidence
Regulatory Technology (RegTech) Opportunities:
  • AI enhances regulatory reporting accuracy
  • Automated compliance monitoring implemented
  • Real-time risk management capabilities
  • Transaction monitoring improvements
Section 2: PRA & Bank of England Requirements
2.1 Prudential Regulation & Safety/Soundness - HIGH PRIORITY
Fundamental Requirements
  • Capital adequacy not compromised by AI investments
  • Liquidity management enhanced by AI capabilities
  • Credit risk management improved through AI
  • Market risk controls strengthened, not weakened
Three Lines of Defence:
First line: Business units understand AI risks
Second line: Risk function oversees AI governance
Third line: Internal audit reviews AI implementation
2.2 Operational Resilience - MEDIUM PRIORITY
Business Service Continuity
  • Important Business Services identified that use AI
  • Impact tolerances set for AI system failures
  • Mapping and testing of AI system dependencies
  • Response and recovery procedures for AI disruptions
Resilience Framework:
  • AI systems included in operational resilience self-assessment
  • Scenario testing includes AI system failures
  • Communication plans for AI-related service disruptions
  • Lessons learned process for AI incidents
2.3 Financial Stability Considerations - ONGOING
Systemic Risk Assessment
  • AI adoption doesn't increase systemic risk
  • Third-party AI dependencies mapped and managed
  • Concentration risk from AI providers assessed
  • Cross-sector AI risk coordination considered
Bank of England Reporting:
  • AI use disclosed in regulatory returns
  • Participation in BoE AI surveys and data collection
  • Financial stability impact assessment completed
  • Critical third-party relationships identified
Section 3: Data Protection & Privacy
3.1 GDPR & UK Data Protection Act 2018 - HIGH PRIORITY
Data Processing Fundamentals
  • Lawful basis established for AI data processing
  • Data minimisation principles applied to AI models
  • Purpose limitation respected in AI applications
  • Storage limitation enforced for AI training data
Individual Rights:
  • Right to explanation provided for automated decisions
  • Right to rectification mechanisms in place
  • Right to erasure procedures for AI systems
  • Data portability maintained despite AI processing
3.2 Data Protection Impact Assessments (DPIA) - HIGH PRIORITY
DPIA Requirements
  • Systematic monitoring DPIA completed for AI surveillance
  • Automated decision-making DPIA for AI-driven processes
  • Large-scale processing DPIA for extensive AI data use
  • High-risk processing DPIA for sensitive AI applications
DPIA Documentation:
  • Risk assessment methodology documented
  • Mitigation measures implemented and tested
  • Consultation with Data Protection Officer completed
  • ICO consultation undertaken if required
3.3 Cross-Border Data Transfers - MEDIUM PRIORITY
International AI Services
Adequacy Decisions
Confirmed for AI provider locations
Standard Contractual Clauses
In place where needed
Transfer Impact Assessments
Completed for third countries
Data Localisation
Requirements met where applicable
Section 4: Model Risk Management
4.1 AI Model Governance - HIGH PRIORITY
Model Development
  • Model development follows established governance
  • Independent validation of AI models completed
  • Model risk appetite clearly defined and monitored
  • Documentation standards applied to AI models
Ongoing Monitoring:
  • Performance monitoring of AI models in production
  • Model drift detection and remediation procedures
  • Back-testing results reviewed and acted upon
  • Model inventory maintained and regularly updated
4.2 Algorithm Transparency & Explainability - MEDIUM PRIORITY
Decision Transparency
For customer-facing AI
Algorithm Auditing
Capabilities implemented
Bias Detection
And mitigation procedures
Human Oversight
Maintained over AI decisions
Documentation:
  • Model cards or similar documentation created
  • Algorithm explanation procedures documented
  • Staff training on AI explainability completed
  • Customer communication materials prepared
Section 5: Third-Party Risk Management
5.1 AI Vendor Management - HIGH PRIORITY
Due Diligence
Financial stability of AI vendors assessed
Regulatory compliance of AI providers verified
Data security standards of vendors confirmed
Business continuity plans of AI providers reviewed
Contractual Controls:
  • Service level agreements for AI performance defined
  • Data processing agreements comply with GDPR
  • Liability and indemnity clauses for AI failures
  • Termination and data return procedures specified
5.2 Critical Third Parties (CTP) - MEDIUM PRIORITY
CTP Assessment
AI providers assessed for critical third-party status
Systemic importance of AI services evaluated
Alternative providers identified where feasible
Concentration risk from AI vendors managed
Section 6: Cyber Security & Information Security
6.1 AI-Specific Security Risks - HIGH PRIORITY
AI Attack Vectors
Adversarial attacks on AI models prevented
Data poisoning protection measures implemented
Model extraction attacks mitigated
Prompt injection vulnerabilities addressed (for GenAI)
Security Controls:
  • AI model access controls implemented
  • Training data security measures in place
  • AI infrastructure security hardening completed
  • Incident response procedures include AI-specific threats
6.2 Traditional Security Requirements - MEDIUM PRIORITY
Standard Security Measures
Encryption
Of AI data in transit and at rest
Multi-factor Authentication
For AI system access
Network Segregation
For AI infrastructure
Vulnerability Management
For AI platforms
Section 7: Financial Crime Prevention
7.1 Anti-Money Laundering (AML) - ONGOING
AI in AML Systems
  • AI enhances, not replaces, AML controls
  • False positive rates monitored and managed
  • Suspicious activity detection improved
  • Compliance with MLRs 2017 maintained
Enhanced Due Diligence:
  • AI supports enhanced customer due diligence
  • PEP screening improved through AI
  • Sanctions screening accuracy enhanced
  • Transaction monitoring effectiveness increased
7.2 Fraud Prevention - ONGOING
AI-Enabled Fraud Detection
Real-time Scoring
Fraud detection implemented
Authentication
Customer verification enhanced
Behavioural Analytics
Pattern recognition deployed
False Positive Management
Alert filtering optimised
Section 8: Client Communication
& Transparency
8.1 Customer Disclosure Requirements - HIGH PRIORITY
Transparency Obligations
  • Clear disclosure of AI use in client-facing processes
  • Plain English explanations of AI impact
  • Opt-out mechanisms where legally required
  • Regular updates on AI system changes
Communication Materials:
  • Website privacy notices updated for AI use
  • Client agreements include AI disclosure clauses
  • Marketing materials accurately represent AI capabilities
  • Complaint procedures address AI-related issues
8.2 Professional Indemnity & Insurance - MEDIUM PRIORITY
Insurance Coverage
Professional indemnity covers AI-related errors
Cyber insurance includes AI-specific risks
Errors and omissions coverage reviewed
for AI
Coverage limits adequate for AI-related claims
Section 9: Training & Competence
9.1 Staff Training Requirements - ONGOING
Core Training Modules
AI Literacy
Training for all relevant staff
Regulatory Obligations
Specific to AI implementation
Ethical AI Use
And bias awareness training
Incident Reporting
Procedures for AI issues
Specialist Training:
  • Compliance teams understand AI regulatory requirements
  • Technical teams receive advanced governance training
  • Customer-facing staff can explain AI use to clients
  • Senior management briefed on AI strategic risks
IMPORTANT DISCLAIMER
This checklist is for general guidance purposes only and does not constitute legal, regulatory, or professional advice. AI regulation in financial services is rapidly evolving and varies significantly based on individual firm circumstances.
Key Limitations:
  • Each firm has unique regulatory obligations based on their permissions, business model, and risk profile
  • Requirements may have changed since publication
  • This guidance cannot replace tailored professional advice
Firms must:
  • Consult qualified legal and compliance professionals
  • Verify all requirements against current regulatory guidance
  • Customise this checklist for their specific circumstances
  • Engage with regulators where appropriate
No liability is accepted for losses or regulatory consequences arising from use of this checklist. Professional advice is essential before implementation.
This checklist should be customised based on specific firm requirements and regulatory obligations. Professional legal and compliance advice should be sought before implementation. Regular updates are essential as the regulatory landscape continues to evolve.