One challenge that firms with legacy systems face is trying to reconcile the need to innovate with being accountable to regulators.

A survey finds that the APAC financial services industry has a long way to go in harnessing AI and other technologies to modernise compliance processes.

The Asia-Pacific financial services industry, which has been hit by a number of money laundering and other scandals in recent years (such as here and here), still relies heavily on manual processes to handle compliance, a survey finds.

A report from Fenergo and Risk.net has surveyed 110 risk, financial crime and compliance professionals at banks and asset managers in Singapore, Malaysia and Australia. 

Dublin-headquartered Fenergo, provides digital solutions for client lifecycle management (CLM), know your customer (KYC) and transaction monitoring. Risk.net is a specialist financial publication.

While it's unsurprising that a fintech, which focuses on areas such as KYC compliance, would laud the benefits of tech, the findings do indicate that for all the talk about change in recent years, compliance remains a labour-intensive business. One sticking pain point has been long onboarding times, as explored here.

Some 66 per cent of survey respondents report heavy manual workloads, with more than half (54 per cent) facing periodic know-your client (KYC) review backlogs; 45 per cent cite high false-positive rates across KYC, screening and transaction-monitoring processes.

These pressures persist despite 54 per cent saying that they are actively exploring AI use cases, while only one third (34 per cent) have begun implementation, and 13 per cent say they are not using AI at all.

There is a widening gap between the scale of compliance workloads, institutional intent to adopt AI and the readiness to execute automation at scale, the survey found.

In other findings, there is limited familiarity with advanced compliance technologies. Only 6 per cent of respondents state that they are “very familiar” with agentic AI in compliance, while 53 per cent report being only “somewhat familiar” and 29 per cent say that they are “not familiar at all.”

“The challenges faced by firms today reflect the realities of legacy operating models and the need to balance innovation with regulatory accountability,” Keasberry said. 

“For organisations at earlier stages of AI adoption, keeping human oversight in the loop remains essential. Regulators expect AI systems to be explainable and well governed. The findings suggest institutions want to demonstrate control over how AI models operate and how decisions are reached, particularly in high-risk areas such as KYC, AML and fraud,” he added.