AML trends:
- The FinCrime Frontier 2025–26 report captured insights from 250 senior financial crime and compliance leaders across banking, insurance, and FinTech worldwide
- Nearly two-thirds of respondents pointed to data quality and integration as the biggest barrier to AML efficiency, alongside resourcing and legacy technology challenges
- The findings highlight that meaningful AML efficiency gains depend on strengthening data, workflows, and investigative processes rather than automation alone
The FinCrime Frontier 2025–26 report captured insights from 250 senior financial crime and compliance leaders across banking, insurance, and FinTech worldwide
The FinCrime Frontier 2025–26 report by SymphonyAI and AML Intelligence drew on insights from 250 senior financial crime and compliance professionals across banking, insurance, and FinTech worldwide.
Respondents included senior executives, AML leaders, compliance officers, and risk and technology specialists, providing a comprehensive health check of how institutions are managing financial crime risk.
The study was designed to surface the most pressing operational challenges holding back compliance effectiveness, as well as the structural changes shaping the future of AML programmes.
Nearly two-thirds of respondents pointed to data quality and integration as the biggest barrier to AML efficiency, alongside resourcing and legacy technology challenges
When asked what is holding back AML efficiency in 2025–26, respondents were permitted to select multiple answers, reflecting the interconnected nature of AML challenges.
Nearly two-thirds (66%) cited data quality and integration as the single biggest blocker, underscoring persistent issues with fragmented client, transaction, and alert data.
Resource constraints followed at 43%, while 40% pointed to outdated or inadequate technology solutions.
These findings highlight a clear pattern: AML inefficiency is driven less by regulatory uncertainty and more by foundational data and infrastructure weaknesses that limit scalability and analytical accuracy.
The findings highlight that meaningful AML efficiency gains depend on strengthening data, workflows, and investigative processes rather than automation alone
Beyond data and technology, respondents also highlighted workflow-related pressures that erode productivity.
Alert fatigue was cited by 31% of respondents as a significant drain on analyst capacity, while 16% pointed to slow case resolution as an ongoing bottleneck in investigations and escalation processes.
Together, these results suggest that meaningful efficiency gains will not come from automation alone, but from addressing core enablers such as data integrity, modernised platforms, and better-aligned teams—unlocking faster investigations, stronger detection outcomes, and greater regulatory confidence.
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