The banking and development finance institutions are accelerating the adoption of artificial intelligence (AI) across their operations, but most remain reluctant to rely on the technology for critical business decisions, according to a new industry study.
The “AICB-Ecosystm AI in Practice: How Malaysia’s Banks & DFIs are Adopting and Governing AI” report found that although AI is increasingly being deployed in customer onboarding, fraud detection, anti-money laundering (AML), counter financing of terrorism (CFT) compliance and workforce productivity, only 25% of financial institutions trust AI-generated outputs sufficiently to make high-impact business decisions.
The report was jointly produced by the Asian Institute of Chartered Bankers (AICB), research and advisory firm Ecosystm, and the AICB Chief Risk Officers’ Forum. It was launched alongside the 4th Malaysian Banking Conference and 2nd Bank Audit Conference.
The study surveyed 87 senior executives from commercial banks, digital banks, Islamic banks and development financial institutions, supplemented by executive roundtables and in-depth interviews.
AI adoption gathering pace
AICB Chief Executive Edward Ling said the conversation within Malaysia’s financial sector has evolved beyond whether AI should be adopted.
“Malaysia’s banks and DFIs are no longer asking whether AI has a role in financial services. The question now is whether institutions have the judgement, ethics, governance and professional capability to use AI responsibly in decisions that affect customers, risk and institutional performance,” he said.
According to the report, 44% of financial institutions are currently in the “Developing” stage of AI maturity, having progressed beyond pilot projects but still lacking fully integrated capabilities across data, talent and operational models.
Only 15% have reached an “Established” level of AI readiness, while just 2% are classified as “Advanced”, where AI is deeply embedded into strategic decision-making and delivers clear competitive advantages.
Skills and governance remain key challenges
Despite growing investment in AI technologies, the report highlights significant gaps in organisational readiness.
Only 26% of respondents said their institutions have a clearly defined AI strategy aligned with business objectives. At the same time, 44% are already developing proprietary AI solutions, raising concerns about fragmented initiatives that may prove difficult to scale across the organisation.
Talent shortages continue to be another major hurdle.
Nearly 79% of respondents reported a shortage of specialised AI expertise, while only 20% said their organisations actively encourage AI-driven decision-making across the workforce, pointing to broader capability gaps beyond technical implementation.
Governance frameworks also remain underdeveloped.
More than half (53%) of surveyed institutions continue to rely on fragmented or ad hoc governance arrangements instead of comprehensive risk-based frameworks for AI deployment.
Only 33% have established structured AI governance and model risk management processes, while just 27% formally classify AI applications according to risk levels to determine the appropriate oversight and controls.
Managing emerging risks
Chairman of the AICB Chief Risk Officers’ Forum and RHB Banking Group Chief Risk Officer Dr Chong Han Hwee said AI introduces new categories of risk that extend beyond the technology itself.
“AI introduces a new dimension of complexity because its risks do not reside solely within the model. They emerge across the entire ecosystem, from data quality and human usage patterns to the decisions informed by AI and how these factors evolve over time,” he said.
Meanwhile, Ecosystm Vice President of Industry Insights Sash Mukherjee noted that financial institutions are increasingly seeking greater regulatory clarity as AI applications become more sophisticated.
“As AI expands into higher-risk use cases, financial institutions want greater clarity on model risk management, explainability, third-party AI and data governance. But regulation alone will not keep pace with the technology. Ongoing collaboration between industry and regulators will be equally critical to ensure governance frameworks evolve alongside AI innovation,” he said.
Industry benchmark
AICB said the findings provide an important benchmark for Malaysia’s banking sector as institutions transition from experimental AI projects to enterprise-wide implementation.
The institute added that the report reinforces its commitment to helping build the professional capabilities, governance standards and risk management practices needed to support the responsible adoption of AI across the financial services industry.
