Malaysia’s banking and development finance sector is adopting AI at a rapid pace, but many institutions remain cautious about using AI for high-impact business decisions, according to the AICB-Ecosystm AI in Practice report launched by the Asian Institute of Chartered Bankers (AICB), Ecosystm (Editor’s note: not a typo), and the AICB Chief Risk Officers’ Forum.
While the report found that while AI is increasingly used in areas such as Know Your Customer onboarding, fraud detection, Anti-Money Laundering and Counter Financing of Terrorism, and employee productivity, only 25% of respondents trust AI-generated outputs enough to act on them in key business decisions.
AICB-Ecosystm Study: Most Institutions Remain In Early Stages of AI Readiness
The study, launched on the sidelines of AICB’s 4th Malaysian Banking Conference and 2nd Bank Audit Conference, draws on responses from 87 senior leaders across Malaysian commercial banks, digital banks, Islamic banks, and development financial institutions, supported by executive roundtables and interviews.
Edward Ling, AICB Chief Executive, said Malaysian banks and DFIs are no longer questioning whether AI has a role in financial services, but whether institutions have the governance and capability to use it responsibly in decisions affecting customers, risk, and institutional performance.
The study found that 44% of Malaysian banks and DFIs are in the “Developing” stage of AI readiness, having moved beyond experimentation but still facing fragmented capabilities across data, skills, and operating models. Only 15% have reached an “Established” level of readiness, while 2% are categorized as “Advanced”, where AI is fully integrated into decision-making and contributes to competitive differentiation.
Only 26% of institutions have a defined strategy linking AI to business goals, while 44% are already developing custom AI solutions, a gap the report says increases the risk of fragmented initiatives that are difficult to scale. Separately, 79% of institutions report shortages in specialized AI technical skills, while only 20% actively promote AI-driven decision-making across their workforce.
AI governance was identified as a further constraint, with around 53% of organizations relying on fragmented or ad hoc governance rather than consistent, risk-based frameworks. Only 33% have established structured AI governance and model risk management, while 27% apply formal AI risk tiering to adjust oversight according to risk level.
Dr Chong Han Hwee, Chairman of the AICB Chief Risk Officers’ Forum and Group Chief Risk Officer at RHB Malaysia, said AI introduces complexity that extends beyond the model itself, spanning data quality, usage patterns, and the decisions informed by AI over time.
Sash Mukherjee, VP Industry Insights at Ecosystm, said financial institutions are seeking clarity on model risk management, explainability, third-party AI, and data governance, adding that collaboration between industry and regulators will be needed for governance frameworks to keep pace with AI development.
AICB said the findings provide a benchmark for the financial sector as institutions move from AI pilots toward responsible, enterprise-wide implementation.
Pokdepinion: As banks scale AI faster than they can govern it, the real risk isn’t adoption lagging behind ambition, but rather, it’s a matter of trust lagging behind deployment.
