In the landscape of Asia-Pacific financial services, regulatory compliance teams are grappling with outdated methods even as artificial intelligence (AI) emerges as a potential game-changer. Recent research from Fenergo highlights a striking disconnect: while enthusiasm for AI is on the rise, the majority of operations in this region remain rooted in labor-intensive, hands-on processes.
This insight comes from a survey of 110 professionals in risk, financial crime, and compliance roles at banks and asset management firms across Singapore, Malaysia, and Australia.
The study reveals that two-thirds of these teams—precisely 66%—continue to rely heavily on manual workflows for their daily tasks.
This dependence contributes to significant inefficiencies, with more than half (54%) experiencing recurring delays in Know Your Customer (KYC) reviews.
Additionally, nearly half (45%) struggle with elevated rates of false positives during KYC, customer screening, and transaction monitoring.
These issues not only drain resources but also heighten the risk of errors in an environment where regulatory demands are intensifying.
Despite these challenges, there’s a clear shift toward technology-driven solutions.
Over half of the respondents (54%) are investigating potential applications for AI, signaling a growing intent to modernize.
However, actual progress is slower: only about one-third (34%) have started rolling out AI tools, and a smaller portion (13%) have yet to engage with the technology at all.
Familiarity with concepts like agentic AI—systems that can autonomously handle complex tasks—remains limited.
Just 6% of participants consider themselves highly knowledgeable, while over half (53%) have only moderate awareness, and nearly a third (29%) are unfamiliar altogether.
When it comes to implementation preferences, caution prevails.
A substantial 66% favor partial automation, where human oversight plays a central role, and 33% lean toward more extensive but still controlled integration.
Notably, no one advocates for complete automation, underscoring the need for “human-in-the-loop” models to ensure accountability and explainability, especially in sensitive areas like anti-money laundering (AML) and fraud prevention.
Interest in agentic AI is budding, with 44% of firms eyeing its use for key functions such as monitoring transactions, detecting fraud, and screening for sanctions.
Yet, barriers abound.
The APAC region’s diverse languages, fragmented regulations, and intricate data landscapes make achieving consistent data quality a formidable task.
This foundational issue, combined with difficulties integrating AI into aging legacy systems and concerns over meeting regulatory standards, is stalling widespread adoption.
Bryan Keasberry, Fenergo’s APAC Head of Strategy, emphasizes the unique hurdles:
“The manual nature of compliance here stems from linguistic diversity and varied regulatory frameworks, which complicate data standardization. Without solid data basics, advancing AI becomes tricky.”
He further notes that legacy setups demand a balanced approach, where innovation aligns with strict governance.
Regulators in markets like Singapore, Malaysia, and Australia insist on transparent AI systems, so firms must prioritize data enhancements and supervised automation before pursuing more sophisticated tools.
The report predicts increased funding for AI-enhanced compliance amid rising workloads and scrutiny.