Is AI finally becoming a priority in Malaysia’s financial sector? According to Bank Negara Malaysia’s (BNM) latest discussion paper, the answer is a clear yes.

With 97% of Malaysian households connected to the internet and 98% carrying a smartphone, the stage is set for a technology leap. It’s also fuelled by a growing recognition among financial service providers (FSPs) that AI can deliver tangible business and consumer value.

The discussion paper, which covered an industry-wide BNM AI survey with 120 responses (BNM AI Survey 2024), found that 71% of banking institutions and development financial institutions (DFIs) had implemented at least one AI application in 2024, an increase of over 56% from 2023.

Much of the momentum comes from a growing curiosity about GenAI applications.

BNM notes that AI is now embedded across the entire financial value chain: from front to middle to back office. What’s more telling is that most applications are designed to augment rather than replace human decision-making. Full automation, though, remains a space to watch as the technology matures.

Where Exactly Is AI Used in Malaysia’s Financial Institutions?

The survey shows that AI is making inroads across multiple functions, from know-your-customer (KYC) and onboarding, to fraud detection and AML, human resources and more.

Customer analytics and marketing lead in overall AI projects, though most are still in the limited deployment phase. By contrast, internal operations take the lead in full deployment, with AI being used to streamline processes and boost automation.

In technology and cyber risk, adoption stands at up to 10%, driven by AI solutions that detect internal malware and respond to security threats.

At the other end of the spectrum, capital and liquidity management, along with claims review and processing, remain untouched in full deployment.

GenAI Has Big Potential, But Rollouts Steer on the Cautious End

Interestingly, while financial service providers see broad potential in generative AI, most are prioritising internal process improvements. Current use cases range from productivity tools like AI chatbots for staff queries to claim assessment systems, HR onboarding, and internal communications.

Only one in five financial service providers say their senior leaders or C-suite executives actively use internal or publicly available GenAI tools in their own work. Banks, in particular, view internal GenAI as carrying greater risks than traditional AI, prompting them to weigh stronger and more targeted risk management measures.

Admittedly, generative AI has created new cybersecurity challenges for financial service providers, as bad actors use it to develop malicious software, scripts, and more sophisticated threats like deepfakes, advanced phishing scams, and identity fraud.

These are harder to detect and defend against, prompting financial service providers to strengthen their internal controls.

In Malaysia, most financial service providers remain cautious with GenAI, especially in customer-facing and financial risk applications. While the technology has clear potential to improve customer outcomes and operational efficiency, progress will depend on balancing innovation with strong risk management.

From Pockets of Innovation to Institution-Wide AI Strategies

BNM’s findings suggest that Malaysia’s financial institutions will keep steering AI development toward non-financial risk areas like fraud detection, customer analytics, and other operational gains. Higher-stakes financial risk applications may see slower progress.

One big shift in 2024 was structural: more than a third of financial service providers now anchor AI adoption in institution-wide strategies. Over a quarter have built dedicated AI Centres of Excellence to drive execution. This centralisation signals a maturing approach, moving away from scattered pilots toward coordinated, scalable programs.

At the same time, many institutions are opting to develop AI solutions in-house. The aim is to tighten alignment with internal policies, meet regulatory expectations, customise to business needs, and sidestep transparency concerns with third-party models.

Building this internal muscle now could set the stage for more confident, large-scale deployment in the years ahead.

Looking ahead, BNM says it will continue engaging with FSPs to deepen its understanding of both the opportunities and challenges of AI adoption.

BNM is also seeking feedback from the industry to help shape its regulatory and developmental approach for AI in the financial sector. These include questions such as key actions organisations take to mitigate risks associated with AI deployment. Feedback can be emailed no later than 17 October 2025.

These ongoing conversations will be central to its broader goal of fostering responsible innovation across Malaysia’s financial sector.

Featured image: Edited by Fintech News Malaysia, based on images by sodawhiskey via Freepik