Artificial Intelligence in the Malaysian Financial Sector
This discussion paper outlines Bank Negara Malaysia's proposed approach and views relating to the development and adoption of artificial intelligence in the Malaysian financial sector. It examines current adoption trends, benefits, and risks across financial institutions, while seeking stakeholder feedback on regulatory posture and industry-led guidelines.
Summary and content fields are drawn from the document text and are pending editorial review.
Who issued it
Who it governs
Financial service providers, industry associations, technology providers, and stakeholders in the Malaysian financial sector.
What the document contains
The paper covers AI adoption trends in Malaysia's financial sector, an analysis of the benefits and risks of traditional AI and Generative AI, BNM's regulatory and supervisory posture, model risk management expectations, and strategies for fostering responsible industry-led collaboration and development.
It does not establish binding rules, statutory penalties, or exposure drafts, serving purely as a non-binding consultative discussion paper.
- Bank Negara Malaysia published a discussion paper in August 2025 to outline its proposed approach to AI adoption in the financial sector.
- Financial service providers in Malaysia are increasingly adopting AI, with a strong focus on non-financial risk areas like customer analytics and internal operations.
- The paper highlights both benefits such as efficiency and financial inclusion, and risks including data leakage, bias, third-party dependency, and cybersecurity threats.
- BNM maintains a technology-agnostic, outcome-focused regulatory approach based on the principles of parity, proportionality, and neutrality.
- The document invites stakeholder feedback by 17 October 2025 on regulatory posture, guidelines, and future development approaches.
· Part A: Introduction 1 BNM’s Posture on Artificial Intelligence 2 Artificial Intelligence Adoption Trends in the Malaysian Financial Sector 3 Benefits and Risks of Artificial Intelligence Adoption · Part B: BNM’s Approach to Artificial Intelligence Adoption in the Financial Sector 4 Regulatory Approach 5 Development Approach
How it scores
Each score is backed by a quote verified against the document text. Editorial review has not yet confirmed them.
Accountability
4/5Clear responsibility for AI outcomes
Board and senior management are accountable for all AI strategies and outcomes.
Exhibit 11
screening score · 2026-10-23
Fairness
4/5Non-discrimination and equitable treatment
AI-driven decisions do not discriminate or create harmful bias against any individual or group of individuals.
Exhibit 11
screening score · 2026-10-23
Human Dignity
0/5Respect for the inherent worth of persons
screening score · 2026-10-23
Transparency
4/5Openness about how AI systems work and are used
Use of AI is sufficiently disclosed and communicated to those affected where appropriate, commensurate to level of materiality
Exhibit 11
screening score · 2026-10-23
Enforcement
1/5Consequences and compliance mechanisms with real force
an escalation in supervisory focus may be considered if AI-related risks become more material
Section 4.12
screening score · 2026-10-23
Impact Assessment
4/5Required assessment of an AI system's risks/impacts before or during use
FSPs are expected to develop holistic risk management and oversight practices across the lifecycle of AI models within their institutions.
Section 4.5
screening score · 2026-10-23