By PAUL O’DONOGHUE, Senior Correspondent
JUST 4.7% of financial institutions continuously adapt their AML controls as financial crime risks change, the FinCrime Frontier 2026–27 Report has found.
The research from SymphonyAI and AML Intelligence surveyed more than 200 financial crime and compliance leaders.
It is available to download now [HERE].
More than half of respondents, 56.8%, have not adopted always-on compliance monitoring. They are either exploring the approach, or remain at an early pilot stage.
“The finding points to a structural gap,” the report said. “Financial crime typologies, payment ecosystems and regulatory expectations are evolving continuously, while most compliance programs are still built around scheduled review cycles.”
The report also found that 70.8% of respondents said 5% or fewer of the alerts they investigate result in an escalation or SAR/STR filing.
AI and automation is now the leading compliance investment priority. It was cited by 61.9% of respondents.
Fincrime Frontier 2026-27 findings
However, investment in AI has not yet transformed day-to-day compliance operations.
Some 76.3% of institutions still review alerts manually or with only partial automation. Fully manual alert review has fallen, however, from 21.3% to 16.5% year-on-year.
“Criminal typologies shift by the week, transaction volumes keep climbing, and regulatory expectations are tightening,” the report said.
It added that compliance functions are “still largely built to reassess risk on a schedule rather than as conditions change.”
The regulatory environment is also creating new pressures for financial institutions.
“Most financial institutions aren’t short on commitment to modernizing compliance,” said Stephen Rae, Co-Founder and Chair of AML Intelligence. “They’re short on operating tempo.”
John Edison, President of Financial Services at SymphonyAI, said: “The pace of change in financial crime compliance continues to outrun most compliance programs’ ability to adapt.
“The next phase will be defined by how effectively institutions use AI to connect risk intelligence with institutional judgment, transforming detection, investigation and governance.
“[This is] so that controls respond dynamically as risk changes, while maintaining appropriate human oversight and accountability.”
The full report is available to view [HERE].
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