Southeast Asia currently find themselves in the midst of a serious challenge in financial crime (fincrime).

Countries like the Philippines, Singapore, Malaysia, Thailand, and Vietnam are witnessing an escalation in illicit activities, driven partly by their banks’ limited use of artificial intelligence (AI) in combating threats such as money laundering and also fraud.

A recent report by SymphonyAI, in corporation with Regulation Asia uncovered the challenges and opportunities in addressing these vulnerabilities, spotlighting the urgent need for AI adoption in the region’s financial systems.

Rising Financial Crime Is A Regional Concern

Financial crime in Southeast Asia is growing more complex and widespread. According to the report, incidents of money laundering in the region surged by 64% from 2018 to 2023 with criminal organisations tend to exploit outdated compliance systems, leveraging sophisticated tactics to bypass traditional safeguards.

Thailand and Singapore for starters have emerged as key targets due to their robust financial hubs, while emerging economies nations such as the Philippines and Vietnam who are grappling with increasing regulatory gaps are also facing the same issue.

The recent high-profile cases in Singapore, the Philippines and Malaysia illustrate the urgency of reform.

In 2023, Singaporean authorities uncovered a money laundering operation involving assets worth USD$ 2.3 billion.

What could be arguably be the latest and biggest news surrounding the Philippines is the Alice Guo case where the Anti-Money Laundering Council (AMLC) filed a case against Alice Guo and her family corporations for using their businesses to facilitate financial crimes.

Similarly, can be said to Malaysia as the Malaysian authorities raided 12 premises linked to XFOX Market Sdn. Bhd. and froze 92 bank accounts totalling USD$ 5.59 million over suspected financial offences, including breaches of anti-money laundering and anti-pyramid scheme laws.

AI’s Untapped Potential in Financial Crime Compliance

AI’s transformative potential in businesses is widely acknowledged and it’s unfair to say that financial institutions (FIs) in this region are not utilising AI within their organisations especially when AI is said to be able to uplift ASEAN’s GDP by 10 to 18 percent, with a value up to USD$ 1 trillion by 2030.

Interestingly, despite the adoption, the report finds an apparent result among emerging markets like Vietnam and the Philippines financial organisations are at the nascent stages of AI deployment and mainly uses AI on front-office applications such as customer experience rather than compliance functions like transaction monitoring or Know Your Customer (KYC) processes.

The SymphonyAI-Regulation Asia report indicates that only 24.6% of financial institutions in the region actively use AI for anti-money laundering (AML), while 41% are in planning stages. In Vietnam, many banks lack dedicated AI development teams, with only one from nine have their own AI team.

AI has the ability to process vast datasets, hence, when being used for financial crime purposes, it can help in detecting suspicious patterns all while reducing false positives which can be a game-changer plus make life easier for FIs.

Barriers to AI Adoption in Southeast Asia

With this in mind, many of us are left wondering, what are the main causes of financial institutions refusal to turn to the trusty-ol artificial intelligence for help?

According to the report, AI adoption in Southeast Asia’s financial institutions faces significant hurdles, primarily due to integration challenges with outdated legacy systems and poor data quality.

Nearly 60% of institutions report struggles with aligning AI to their existing infrastructure, while fragmented datasets and the lack of robust data governance further impede progress. Effective AI relies on high-quality data, but many banks are starting from scratch to create usable frameworks, often requiring years of effort.

Regulatory uncertainty across the region adds complexity, with inconsistent frameworks and strict data privacy rules making compliance difficult. Model explainability also poses challenges, as stakeholders demand transparency in AI decision-making, slowing approvals and adoption.

Cost concerns, particularly for smaller institutions, further hinder AI deployment.

However, AI itself can address some of these barriers by automating data cleansing and structuring, enabling faster deployment.

Incremental implementation, focusing on scalable, low-disruption solutions, offers institutions a pathway to overcoming these challenges and leveraging AI effectively to combat financial crime.

RCBC Shows How AI Can Help

Rizal Commercial Banking Corporation (RCBC) offers a compelling example of how FIs in Southeast Asia can navigate these challenges all while utilising AI into their systems.

Brent Estrella, Group Chief Compliance Officer at Rizal Commercial Banking Corporation (RCBC) described how the bank is leveraging AI to transition from traditional compliance methods to a more dynamic, much more data-driven approaches.

One of RCBC’s most significant initiatives involves using AI to trigger Customer Due Diligence (CDD) reviews based on specific events and risk factors.

“The periodic review system tends to produce the same results repeatedly. AI allows us to focus on meaningful changes in customer behaviour or risk profiles,” Brent said.

By training models on historical Suspicious Transaction Reports (STR) data, the bank can identify high-risk accounts more efficiently and of course, accurately.

Brent also emphasised the importance of leadership support in driving AI adoption. At RCBC, the board and senior management have shown strong alignment with the bank’s compliance objectives.

“One of our independent directors is the head of the Center for AI Research in the Philippines, which provides invaluable guidance and ensures that compliance remains a priority,” he noted.

However, he still acknowledged that focusing AI for compliance functions can be tricky, as business-related AI applications often take precedence.

To address this, RCBC is working to build specialised technical skill sets within its compliance teams, reducing reliance on shared resources and accelerating the implementation of AI initiatives.

Southeast Asia’s FIs Are Pushing for AI Governance

Despite the lack of AI use for fincrime prevention, the regulatory environment for artificial intelligence in Southeast Asia is rapidly evolving as governments are now seriously taking proactive steps to define how AI should be deployed, particularly within financial services.

While the transformative potential of AI is widely recognised, the fragmented regulatory landscape across Southeast Asia presents both challenges and opportunities for financial institutions (FIs) looking to adopt the technology. Let’s have a look at what other countries across Southeast Asia is doing.

Unlike its counterparts, the Philippines is still in the early stages of AI adoption, with efforts primarily concentrated on pilot projects in fraud detection and compliance within financial services.

The country’s central bank, Bangko Sentral ng Pilipinas (BSP), is playing a crucial role by drafting AI guidelines for the banking sector and facilitating regulatory sandboxes for experimentation.

Additionally, the Philippines as a government, is pushing for a comprehensive AI regulatory framework for the ASEAN region by 2026, with a focus on cybersecurity, generative AI, and ethical use.

While the Philippines faces significant challenges in scaling AI adoption across industries, its commitment to building regulatory and technological capabilities signals a promising future for responsible AI integration.

The Way Forward

The rise of financial crime in Southeast Asia demands an urgent shift from reactive to proactive measures in compliance systems.

AI offers a unique opportunity to strengthen the region’s defences against evolving threats. By addressing integration challenges, improving data governance, and fostering regulatory alignment, banks in Southeast Asia can harness AI’s full potential.

As Southeast Asia advances its regulatory frameworks, collaboration among countries will be key to overcoming fragmentation and fostering a unified approach.

Countries like Singapore and its neighbour Malaysia are setting examples with their robust governance models, while nations like the Philippines and Vietnam are actively developing their regulatory landscapes to support emerging technologies.

For financial institutions in the region, navigating these varied regulatory environments will require strategic planning, but the potential rewards which includes increased efficiency, improved compliance, and enhanced financial crime prevention are well worth the effort.

Featured image credit: Edited from Freepik