Two- day classroom program

AI for Financial Institutions: Governance, Risk and Practical Controls

A practical two-day course on assessing, approving and overseeing AI across financial services

Date27&28 April 2027
VenueKuala Lumpur

This practical two-day course helps participants translate those questions into effective oversight. It explains how predictive and generative AI work, examines their principal risks and explores how familiar governance, model risk and third-party controls can be adapted to manage them.

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Why this course?

Why this program?

AI is creating new opportunities across financial services, from fraud detection and customer analytics to operational efficiency and customer support. For risk, compliance, audit and governance teams, it also raises pressing questions: where is AI being used, who is accountable, what could go wrong and are existing controls sufficient?

This practical two-day course helps participants translate those questions into effective oversight. It explains how predictive and generative AI work, examines their principal risks and explores how familiar governance, model risk and third-party controls can be adapted to manage them.

Through demonstrations, case studies and guided workshops, participants will develop an AI inventory, a process for assessing and approving use cases, and an approach to evaluating AI vendors. The programme also covers human oversight, incident response, internal audit and board reporting, with discussion grounded in the Malaysian financial services environment.

No coding or specialist technical knowledge is required.

Learning objectives
  • By attending this course, participants will be able to:
    • Understand how predictive and generative AI work, their limitations and the implications for financial institutions.
    • Identify AI risks across model risk, operational risk, conduct, compliance, cybersecurity and data protection.
    • Develop an AI system inventory, including AI embedded in existing software and outsourced services.
    • Assess the materiality of AI use cases and determine appropriate controls, approval requirements and human oversight.
    • Apply model risk principles to AI validation, monitoring and change management.
    • Evaluate AI vendors, including data handling, contractual safeguards, model updates and exit arrangements.
    • Strengthen AI incident response, internal audit coverage and reporting to senior management and the board.
Practical takeaways
  • Participants will work with templates and exercises that can be adapted to their own organisations, including:
    • An AI system inventory and materiality assessment guide.
    • A use case intake form and approval matrix.
    • An AI vendor assessment questionnaire.
    • A generative AI acceptable use policy template.
    • Incident scenarios, an internal audit test plan and a board reporting template.
    • A practical 90-day action plan.
Who should attend?

This course is designed for professionals responsible for assessing, approving, monitoring or assuring the use of AI within banks, Islamic banks, regulators, insurers, Takaful operators, investment institutions and other financial services organisations.

It is particularly relevant to risk management, compliance, internal audit, model risk and validation, data protection, IT risk and security, procurement and vendor management teams. Governance and company secretariat professionals supporting board and committee oversight will also benefit.

Booking options

Fee

Fee per participant

RM6,500/US$1,750 Enquire about this course →

Please note that the Ringgit price is applicable to Malaysia-domiciled participants only. Discounts are available for group bookings. Please contact us for more details.

*Price is subject to 8% Service Tax

Agenda

27&28 April 2027 · 2 days

Day One: Understanding AI, Identifying Risks and Building the Inventory 27 April 2027

Understanding AI from a risk and governance perspective 2 topics
  • Understand how predictive and generative AI produce results, where their limitations arise and why these matter for control functions.
  • Explore AI assistants, connected tools and agents, and the implications of allowing systems to act with increasing autonomy.
AI in financial services: Applications and oversight 2 topics
  • Examine applications across customer analytics, fraud detection, AML, credit assessment and internal operations.
  • Discuss the Malaysian regulatory and governance context, with selected international approaches providing points of comparison.
Identifying and assessing AI risks 2 topics
  • Consider inaccurate outputs, bias, data leakage, limited explainability, third-party dependency and AI-enabled fraud.
  • Connect these exposures to existing risk categories and identify where additional controls may be needed.
Workshop: Building an AI system inventory 1 topic

Identify AI across business functions, including features within existing vendor software, and develop a practical register covering ownership, purpose, data use, decision-making authority, validation and review requirements.

Assessing materiality and setting control requirements 2 topics
  • Evaluate AI use cases according to customer impact, data sensitivity, autonomy and the consequences of error.
  • Use this assessment to establish proportionate oversight and approval requirements.
Case studies: What went wrong and what should have prevented it? 2 topics
  • Examine examples involving customer-facing AI, confidential information and automated decisions.
  • Identify the governance failures, missing controls and evidence an auditor would seek.

Day Two: Governance, Approval, Vendors and Assurance 28 April 2027

Establishing accountability and governance 2 topics
  • Define the responsibilities of the board, senior management, business owners and control functions.
  • Explore how the three lines model can support clear ownership, effective challenge and timely escalation.
Designing the AI approval process 2 topics
  • Develop a practical route from initial proposal to deployment, covering risk assessment, data use, validation, human oversight and approval.
  • Consider how requirements differ between predictive models and generative AI applications.
Workshop: Testing the approval workflow 1 topic

Apply an intake form and approval matrix to two financial services use cases, and identify who should review and approve each application, what evidence is required and how subsequent changes should be managed.

Model risk management for AI 2 topics
  • Explore validation, explainability, bias and fairness testing, performance monitoring and model drift.
  • Consider the additional challenges of evaluating generative AI, including testing outputs and challenging systems under adverse conditions.
Assessing AI vendors and third-party services 2 topics
  • Examine data flows, confidentiality, use of institutional data for training, subcontractors, model updates, logging and incident arrangements.
  • Assess whether contractual terms support the assurances made by vendors.
Workshop: Reviewing an AI vendor 1 topic

Evaluate a sample vendor information pack, identify gaps and inconsistencies, and develop conditions for approval using a structured assessment questionnaire.

Responding to AI incidents 2 topics
  • Work through scenarios involving a deepfake payment request and hidden instructions designed to manipulate an AI agent.
  • Discuss detection, containment, escalation and remediation, and identify opportunities to strengthen existing controls.
Internal audit, board reporting and the first 90 days 2 topics
  • Determine what internal audit should test and what senior management and the board need to know.
  • Develop a practical action plan for improving AI oversight, prioritising inventories, approvals, vendor reviews and assurance.

Course methodology

The course combines clear explanations, live demonstrations, financial services case studies and guided group exercises. A fictional Malaysian bank provides a running example, enabling participants from different institutions to explore common challenges and apply the lessons to their own roles.

Participants should bring a laptop for the practical workshops.

Expert Course Director

Junaid Aziz

Junaid Aziz

AI and Digital Transformation Specialist

Junaid Aziz is an AI and digital transformation specialist with more than eight years’ experience designing and delivering AI, data and digital upskilling programmes across the UAE and GCC. He has trained more than 7,000 executives in artificial intelligence, machine learning, Fintech, Blockchain and digital transformation, and developed upskilling curricula for more than 48,000 professionals. Previously a full-time faculty member at the Majid Al Futtaim Leadership Institute’s School of Analytics and Technology, Junaid supported the group’s digital transformation programme and worked on AI applications spanning customer analytics, operational automation and financial efficiency. He has also designed and delivered programmes through PwC Digital Academy, Pearson Education, Higher Colleges of Technology and NobleProg. His financial sector experience includes six years in investments and portfolio management at the Abu Dhabi Investment Office, working across an AI investment portfolio exceeding US$1.5 billion. He has contributed to policy research at the Center for AI and Digital Policy and holds the Artificial Intelligence Governance Professional qualification from the International Association of Privacy Professionals. Alongside his teaching and advisory work, Junaid brings hands-on software development and AI implementation experience. His work includes sentiment analysis for hedge funds, applications using large language models, automated workflows and public-sector platforms. This combination of executive education, governance knowledge and technical delivery enables him to connect how AI systems operate with the practical questions facing financial institutions and their control functions.

Registration

*Please note there is a fee for attending this program. Please contact us for more details.

Approving Manager

Verification

Before completing this registration form please read and understand our booking and cancellation policy. Thank you.

Booking, Payment and Cancellation Policy – important, please read carefully

By completing, signing and revised, sent separately us this registration form you are confirming participants on the program. You are also confirming your understanding of our Booking, Payment and Cancellation Policy.

Cancellation Policy: If participants cannot attend the program, replacement participants are always welcome. Otherwise, participants must notify us any of cancellations or requests to transfer to a different program at least 14 days before the program date to be eligible for a refund, less a 5% administration on fee. Participants who cancel within 14 days of the program start date are liable to pay the full program fee and no refunds will be given. Instead fees will be converted to a REDmoney Seminars voucher equivalent to the original fee, less a 10% administration charge. This voucher is transferable within your organization and must be redeemed within one year of issue or become void. If a program is postponed for whatever reason registrations and fees will be automatically transferred to the new program date. Participants who wish to transfer to a different program will be subject to the same terms as above and charged any difference in fees. No refunds or program vouchers will be issued for a no-show.
Payment Terms: All program fees are payable upon invoice. REDmoney shall receive the full program fee with no deductions of any description. All telegraphic transfer fees, taxes and levies (domestic or otherwise) shall be borne by the sponsoring organization.
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