Regions Leading AI Adoption in Financial Crime & Compliance
AI adoption in financial crime and compliance is moving at different speeds across regions. Our latest research with Chartis highlights differences in maturity, with some regions running AI in production while others remain at the pilot and experimentation stages.
The report, AI in Financial Crime and Compliance: Charting the Path from Pilot to Maturity, also reveals how AI adoption is expected to evolve by region over the next two to three years.
→ Download the Banking Edition here
→ Download the Payment & FinTech Edition here
How North American Banks Are Using AI in Financial Crime and Compliance
North America shows the highest operational maturity, with significant numbers of banks running AI in production across different financial crime functions.
Fraud prevention is ahead. 8% of banks use AI at scale, 35% have it running in production, 34% are piloting, 16% are exploring, 3% use it individually, and 3% don't use it at all. That means 43% already have it fully operational.
AML transaction monitoring is catching up. 4% use AI at scale, 25% have it running in production, 39% are piloting, 15% are exploring, 13% use it individually, and 4% don't use it at all.
Sanctions screening sits in the middle. 4% use AI at scale, 18% have it running in production, 37% are piloting, 23% are exploring, 13% use it individually, and 5% don't use it at all.
Case management and investigations are moving slower. Only 3% use AI at scale, 9% have it running in production, 24% are piloting, 25% are exploring, 28% use it individually, and 12% don't use it at all.
Regulatory reporting is the slowest to adopt. Just 2% use AI at scale, 5% have it running in production, 20% are piloting, 27% are exploring, 28% use it individually, and 17% don't use it at all.
How European Banks Are Using AI in Anti-Financial Crime
Europe shows widespread adoption across all financial crime functions, with organizations piloting and operationally using AI throughout their FCC operations. European banks also show balanced adoption across functions, with particularly strong individual experimentation in case management and regulatory reporting.
Fraud prevention leads here too. 13% of banks use AI at scale, 22% have it running in production, 26% are piloting, 24% are exploring, 11% use it individually, and 5% don't use it at all. That means 35% already have it fully operational.
Sanctions screening shows strong interest. 5% use AI at scale, 7% have it running in production, 22% are piloting, but a significant 44% are still exploring. Another 19% use it individually, and only 3% don't use it at all.
AML transaction monitoring has positive pilot activity. 2% use AI at scale, 16% have it running in production, 32% are piloting, 23% are exploring, 20% use it individually, and 7% don't use it at all.
Case management and investigations remain experimental. Just 2% use AI at scale, 6% have it running in production, 14% are piloting, 31% are exploring, a notable 36% use it individually and 11% don't use it at all.
Regulatory reporting lags behind. Only 2% use AI at scale, 2% have it running in production, 14% are piloting, 28% are exploring, 32% use it individually, and 22% don't use it at all.
How Asia-Pacific Banks Are Using AI in FCC
APAC shows broad but uneven adoption, with activity focused on fraud, sanctions screening, and AML transaction monitoring. Banks in this region show particularly high rates of individual AI use for investigations and reporting, suggesting adoption that could scale as regulatory frameworks align.
Sanctions screening shows strong interest. 6% use AI at scale, 3% have it running in production, 20% are piloting, but a significant 37% are still exploring. Another 23% use it individually, and 11% don't use it at all.
Fraud is most advanced. 3% of banks use AI at scale, 11% have it running in production, 37% are piloting, 34% are exploring, 11% use it individually, and 3% don't use it at all. That means 14% already have it fully operational.
AML transaction monitoring has positive operational activity. None of the banks reported using AI at scale, while 17% have it running in production, 26% are piloting, 14% are exploring, 31% use it individually, and 11% don't use it at all.
Case management and investigations remain experimental. Again, none of the banks reported using AI at scale in this area, while 6% have it running in production, 14% are piloting, 29% are exploring, and 43% use it individually — the highest of any category in this region. 9% don't use it at all.
Regulatory reporting lags behind. Once more, no banks are using AI at scale in for this, while 3% have it running in production, 14% are piloting, 31% are exploring, 31% use it individually, and 20% don't use it at all.
Get the reports AI in Financial Crime and Compliance: Charting the Path from Pilot to Maturity:
→ Download the Banking Edition here
→ Download the Payment & FinTech Edition here
For more information on how Hawk can help your financial institution to scale AI for AML, fraud prevention, and screening, please contact us.