AI and Generative AI Governance in Banking Course

Name: AI and Generative AI Governance in Banking Training Course
Availability: InStock

Equip banking leaders to prioritize AI use cases, apply human oversight, control model dependencies, and measure portfolio value.

AI and Generative AI Governance in Banking Course

At a glance

Duration: 5 days
Format: Classroom
Cities: Amsterdam, Istanbul, Kuala Lumpur, Abu Dhabi, Cairo, Dubai and more
Next session: 5 – 9 October 2026, Amsterdam
Average fee: 5,800 €

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AI and Generative AI Governance in Banking Training Course

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Overview

AI and Generative AI Governance in Banking Training Course is a five-day advanced course for banking executives, business-line leaders, risk managers, operations heads, product owners, and transformation leaders, who leave with a Governed Banking AI Portfolio Roadmap. Participants classify generative AI use cases, evaluate data and model dependency risks, define human oversight controls, prioritize a banking AI portfolio, plan workforce adoption, and establish banking value indicators. Agile Leaders Training Center delivers training in governed artificial intelligence for banking.

Who Should Attend

Banking leadership personnel responsible for strategy, investment, and accountable AI adoption
Retail and corporate banking personnel responsible for customer, credit, and product decisions
Risk and compliance personnel responsible for model, conduct, privacy, and financial-crime controls
Operations personnel responsible for service workflows, resilience, and third-party dependencies
Transformation and product personnel responsible for use-case portfolios, adoption, and value evidence

The course assumes participants can assess banking processes, risks, and investment proposals at work, and it leaves out coding, model building, prompt engineering, and vendor-platform configuration.

Departments and Industries

The course supports banking, finance, risk, operations, technology, and transformation functions across retail banking, corporate banking, payments, lending, and financial services.

Retail and corporate banking
Credit, lending, and product management
Risk, compliance, and financial-crime control
Operations, customer service, and payment services
Data, technology, and digital transformation

Learning Objectives

By the end of this course, participants will be able to:

Analyze banking AI use cases and decision boundaries
Evaluate data, model, and third-party dependency risks
Prioritize a governed AI use-case portfolio
Apply human oversight and escalation controls
Build adoption and operating-resilience actions
Use benefit and risk indicators for portfolio review

Course Agenda

Day 1: Banking AI Use Cases and Value

Banking AI Use-Case Classification Map
Customer Service and Product Opportunity Canvas
Credit and Risk Decision-Support Boundary
Operations and Financial-Crime Application Matrix
Banking Outcome and Value Hypothesis Register

Day 2: Data, Models, and Dependencies

Banking Data Readiness Scorecard
Generative AI Information-Flow Map
Model Limitation and Hallucination Register
Bias, Privacy, and Explainability Risk Grid
Third-Party Model Dependency Assessment

Day 3: Governance and Human Oversight

Banking AI Inventory and Ownership Register
Use-Case Risk Classification Matrix
Human Oversight and Decision-Rights Framework
Three Lines of Defense Accountability Map
Incident Escalation and Control-Evidence Checklist

Day 4: Portfolio, Adoption, and Measurement

AI Use-Case Value and Feasibility Matrix
Governed Banking AI Portfolio Board
Workforce Role and Adoption Impact Map
Operational Resilience Dependency Checklist
Benefit, Risk, and Adoption Indicator Tree

Day 5: Banking AI Governance Practice and Capstone

Suggested Exercise: Classify a Customer-Service Use Case
Suggested Exercise: Challenge a Credit Decision-Support Boundary
Suggested Exercise: Test Human Oversight and Escalation
Suggested Exercise: Reprioritize the AI Portfolio Under Constraints
Capstone Exercise: Governed Banking AI Portfolio Roadmap

Practical Exercises

The course uses suggested activities that turn banking AI proposals into reviewable governance and investment evidence.

Suggested activity: compare customer, credit, operations, and financial-crime use cases by value and decision sensitivity
Suggested activity: trace data, model, vendor, and operational dependencies for a generative AI application
Suggested activity: assign ownership, human review, control evidence, and escalation paths
Suggested activity: construct a portfolio review pack with adoption, benefit, risk, and resilience indicators

FAQs

Who suits the AI and Generative AI Governance in Banking Training Course, and what does it assume?

The course suits banking leaders who assess use cases, risks, operations, products, and investments and who can interpret business and control evidence without building models or configuring platforms.

How does AI governance in banking training differ from prompt-engineering training?

AI governance in banking training focuses on use-case decisions, banking risks, ownership, oversight, dependencies, adoption, and value measurement rather than prompt construction, software development, or model implementation.

How should banks prioritize generative AI use cases?

Banks should compare outcome value, decision sensitivity, data readiness, model limitations, customer impact, control effort, third-party dependencies, operational resilience, reversibility, and the evidence required before wider adoption.

What human oversight belongs in banking AI governance?

Human oversight should define accountable owners, review points, decision limits, challenge roles, exception handling, escalation paths, evidence retention, and authority to pause or change a use case.

How should banking AI value and risk be reviewed?

Banking AI portfolios should be reviewed against benefit hypotheses, adoption evidence, customer and operational outcomes, model performance signals, control exceptions, resilience dependencies, and documented decisions to continue, adjust, scale, or stop.

Conclusion

Participants take back a Governed Banking AI Portfolio Roadmap linking use cases, data readiness, model dependencies, human oversight, adoption, and indicators. It changes how banking teams compare proposals and document accountable deployment decisions. The roadmap supports staged investment, visible ownership, control evidence, resilience planning, and portfolio review based on value and risk.

credits: 5 credit per day

Course Mode: full-time

Provider: Agile Leaders Training Center

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Showing 1-20 of 76 events

Location	Dates	Duration	Mode	Price
Amsterdam	Week 41, 2026 5 – 9 October 2026	5 Days	Onsite	€5,700
Istanbul	Week 42, 2026 12 – 16 October 2026	5 Days	Onsite	€4,500
Kuala Lumpur	Week 43, 2026 19 – 23 October 2026	5 Days	Onsite	€5,200
Abu Dhabi	Week 43, 2026 19 – 23 October 2026	5 Days	Onsite	€4,700
Cairo	Week 44, 2026 26 – 30 October 2026	5 Days	Onsite	€4,100
Dubai	Week 45, 2026 2 – 6 November 2026	5 Days	Onsite	€4,500
Toronto	Week 45, 2026 8 – 12 November 2026	5 Days	Onsite	€12,000
Sharm El-Sheikh	Week 46, 2026 9 – 13 November 2026	5 Days	Onsite	€4,100
Barcelona	Week 47, 2026 16 – 20 November 2026	5 Days	Onsite	€5,700
New York	Week 47, 2026 16 – 20 November 2026	5 Days	Onsite	€12,000
Manama	Week 47, 2026 22 – 26 November 2026	5 Days	Onsite	€4,700
Amsterdam	Week 49, 2026 30 November – 4 December 2026	5 Days	Onsite	€5,700
Singapore	Week 49, 2026 30 November – 4 December 2026	5 Days	Onsite	€5,700
London	Week 50, 2026 7 – 11 December 2026	5 Days	Onsite	€5,700
Tbilisi	Week 51, 2026 14 – 18 December 2026	5 Days	Onsite	€5,000
Vienna	Week 52, 2026 21 – 25 December 2026	5 Days	Onsite	€5,700
Zoom	Week 53, 2026 28 December 2026 – 1 January 2027	5 Days	Online	€1,500
Nice	Week 53, 2026 28 December 2026 – 1 January 2027	5 Days	Onsite	€5,700
Nairobi	Week 53, 2027 3 – 7 January 2027	5 Days	Onsite	€4,500
Rome	Week 01, 2027 4 – 8 January 2027	5 Days	Onsite	€5,700

Frequently asked questions

What does this course cover?

OverviewAI and Generative AI Governance in Banking Training Course is a five-day advanced course for banking executives, business-line leaders, risk managers, operations heads, product owners, and transformation leaders, who leave with a Governed Banking AI Portfolio Roadmap. Participants classify generative AI use cases, evaluate data and model dependenc…

Are training dates available?

Yes. Available dates and destinations are listed in the course dates section on this page.

How can I register?

Choose an available date on this page and complete the registration form, or send a programme enquiry.

Can I download the course brochure?

Yes. Use the brochure download link provided on this page.

AI and Generative AI Governance in Banking Course