Bank Negara Malaysia says more than 70% of Malaysian financial service providers have now implemented at least one AI application, and Governor Abdul Rasheed Ghaffour is pushing the industry to treat that shift as a governance question rather than a technology upgrade. Speaking at the inaugural AICB Nexus Conference in Kuala Lumpur, he said institutions must move beyond internal efficiency gains and ensure humans remain accountable for AI-driven outcomes across fraud detection, credit assessment, and compliance.
Key Facts At A Glance
- More than 70% of Malaysian financial service providers have implemented at least one AI application, per BNM
- Findings are based on industry responses to BNM’s Discussion Paper on Artificial Intelligence in the Malaysian Financial Sector
- AI use cases cited include fraud detection, credit and insurance risk assessment, compliance, risk management, and customer service
- BNM is coordinating with the Royal Malaysia Police, PayNet, and financial institutions to share intelligence on scams and fraud
- AICB’s Future Skills Framework is positioned to build AI literacy, ethical judgment, and governance capabilities among banking staff
- BNM’s Open Finance framework is set for phased implementation from 2027, developed with PayNet and industry partners
- BNM’s asset tokenisation roadmap is moving into pilots through the Digital Assets Innovation Hub
- BNM is developing its Financial Sector Blueprint 2027-2030 with industry, government, and other stakeholders
From Efficiency Gains To Governance
Abdul Rasheed told the AICB Nexus Conference that AI adoption in Malaysia’s financial sector has so far concentrated on internal gains such as efficiency, productivity, and risk management. He urged financial institutions to widen their focus to industry-level problems, including scams, fraud, and cyber threats, arguing that individual institutions cannot manage these risks alone. He pointed to the coordination already underway between BNM, the Royal Malaysia Police, PayNet, and financial institutions as a model for shared intelligence and stronger customer safeguards. As models used in financial decision-making grow more complex, he said institutions need to be able to explain outcomes, challenge automated decisions, and remain accountable for them, adding that responsibility for those decisions cannot be delegated to an algorithm. He called on boards and senior management to treat AI as a standing agenda item tied to measurable business outcomes and a defined risk appetite, and said risk, compliance, and internal audit functions will need to expand their role beyond confirming that controls exist to being able to explain and stand behind AI-driven outcomes.
Workforce And Wider Regulatory Agenda
Abdul Rasheed also called for greater investment in people as AI reshapes job roles and workflows across the sector, pointing to AICB’s Future Skills Framework as a mechanism for building AI literacy, ethical judgment, and governance capability among banking professionals. He framed BNM’s broader approach as one of encouraging innovation while preserving trust, through early industry engagement, clearer regulatory expectations, and shared infrastructure. The remarks come as BNM advances several parallel initiatives: an Open Finance framework for consent-based data sharing with supporting infrastructure being built alongside PayNet, with phased implementation starting in 2027; an asset tokenisation roadmap now moving into pilot stage through the Digital Assets Innovation Hub; and a new Financial Sector Blueprint for 2027 to 2030 being developed jointly with industry and government stakeholders. Abdul Rasheed described these initiatives as tools rather than end goals, saying their value would depend on whether they strengthen resilience and broaden opportunity rather than simply accelerate technology adoption.