AI in Banking & Financial Services
Overview
Banks and financial institutions were among the first to use AI at scale, in credit decisions, fraud prevention, customer service and compliance. This course reviews the main applications, the regulatory expectations that come with them, and the practical steps institutions take to adopt AI safely.
Who should attend
Bank managers, risk and compliance professionals, product managers, and staff of financial regulators.
Training methodology
Facilitated discussion, practical frameworks, case studies from different sectors, group exercises, short demonstrations of AI tools, and an action plan for each participant's organisation.
Objectives
By the end of this course, participants will be able to:
- Review key AI applications across banking and financial services
- Understand AI in credit scoring and risk management
- Assess AI for customer experience and compliance
- Address model risk and regulatory expectations
- Plan responsible AI adoption in a financial institution
Course outline
Day 1AI Across Financial Services
- Landscape of AI use
- Banking, insurance and capital markets
- Value and risk drivers
- Industry examples
- Islamic finance and AI
- Data and infrastructure
Day 2Credit and Risk
- AI in credit scoring
- Early warning systems
- Fairness in lending decisions
- Case study
- Collections and recovery
- Stress testing support
Day 3Customers and Operations
- Personalised products and advice
- Virtual assistants
- Back-office automation
- Customer journey exercise
- Fraud prevention in digital channels
- Insurance claims automation
Day 4Compliance and Financial Crime
- AI in AML and sanctions screening
- Transaction monitoring
- Regulatory reporting
- Reducing false alerts
- Know-your-customer automation
- Case study
Day 5Model Risk and Adoption
- Model risk management
- Supervisory expectations
- Governance and validation
- Adoption roadmap
- Explainability for regulators
- Partnering with fintechs
