Regulators and boards across the Asia-Pacific have stopped asking whether firms use artificial intelligence (AI). Instead, they started asking about the reasoning behind the AI-made decisions.
According to ComplyAdvantage, in November 2025, the Monetary Authority of Singapore (MAS) issued its consultation on Guidelines on AI Risk Management for financial institutions, setting expectations on transparency and explainability.
ComplyAdvantage recently discussed the case for defensible AI in APAC compliance.
Yet the gap between adoption and assurance is wide: ComplyAdvantage’s State of Financial Crime 2026 survey found that 59% of firms globally have a fully established AI assurance programme in place, with only half of firms (54%) in the Asia-Pacific region doing the same. Appetite is running ahead of production too: in the region, 73% of firms are using, piloting, or evaluating agentic AI for customer screening, while only 31% have it in production.
That gap set the agenda for the third and final session of ComplyAdvantage’s Future of Compliance Asia-Pacific summit in Singapore, hosted by Heather Tan, managing director and head of APAC at ComplyAdvantage, alongside DCS group general counsel Kok Chun Hou, Accenture responsible AI managing director Kush Mukherjee, BIT chief compliance officer Christopher Liu, and Chocolate Finance CTO Thomas Chia.
DCS Group General Counsel Kok Chun Hou said, “If we deploy this model, how can we ensure that it’s deployed in a sensible, justifiable, and defensible manner?”
Panellists agreed opacity costs a firm at three stages: when a case is escalated without explanation, when drift cannot be distinguished from a versioning change, and when a decision must be defended to an auditor.
DCS Group General Counsel Kok Chun Hou said, “The last stage, and arguably the most impactful stage at which an institution can be impacted by opacity, is when your regulatory liability actually crystallizes.”
Panellists stressed that outsourcing a model to a vendor does not outsource accountability for it.
Chocolate Finance CTO Thomas Chia said, “Accountability in general can’t be outsourced – that’s not a new problem, that’s not an AI problem.”
Speakers also called for a phased approach, keeping humans reviewing level-two decisions while AI handles repetitive work.
BIT Chief Compliance Officer Christopher Liu said, “All of us here are in the business of risk management. We are not in the business of eliminating risk.”
Data quality underpinned the entire discussion.
Accenture Responsible AI Managing Director Kush Mukherjee said, “Your AI is only as good as your data.”
The panel’s takeaway: build governance and explainability in from the start, and get metadata and entity resolution right, because no AI decision is defensible without sound inputs behind it.
Copyright © 2026 RegTech Analyst
Copyright © 2026 RegTech Analyst
