INFORM has released outcomes from a survey of 88 financial crime experts, illustrating trends in AI utilization and increasing interest in behavioral biometrics.
INFORM, based in Germany, is a developer of AI-driven decision-making software for risk, fraud, and compliance. The ‘Artificial Intelligence & Anti-FinCrime Market Research Survey’ encompasses responses from 88 financial crime professionals within large financial institutions.
According to the survey findings, AI has transitioned from an experimental tool into a core component of anti-financial crime defense strategies, with most respondents already integrating AI in key compliance and detection roles.
Patterns of adoption and primary applications
The majority (56%) of survey participants are associated with banks, credit unions, or fintechs, while 50% work at organizations employing more than 1,000 individuals. Over half occupy executive or middle management positions, lending significant weight to the survey results.
AI is predominantly used for high-volume, continuous monitoring tasks. Transaction monitoring takes the lead with 82.5%, followed by AML (anti-money laundering) at 71.25% and anomaly detection at 61.25%. Identity verification (37.5%) and customer behavior analysis (33.75%) are less prevalent, indicating that real-time monitoring remains the primary AI application in financial crime management.
Survey respondents cited faster detection as the primary driver for AI adoption (80%), followed by reduced false positives (72.86%) and improved accuracy (61.43%). Cost reduction was mentioned by 30% of participants, while enhanced customer experience was noted by 20%, underscoring that operational efficiency is the key motivation rather than commercial objectives.
Behavioral biometrics as a supplementary tool
A significant finding pertains to the role of behavioral biometrics alongside AI. Over half (56.25%) of respondents consider it the most valuable supporting technology in their anti-financial crime toolkit. Behavioral biometrics monitor subtle changes in user interaction patterns, such as typing rhythm, mouse movement, and device handling, to detect account-takeover attempts, bot activity, and social engineering-driven transactions before fraudulent events occur.
There is moderate interest in expanding biometric capabilities over the next three to five years, with an average score of six out of ten for organizational intent. This indicates that while adoption is expected to grow, it has not yet reached full maturity.
Additionally, 56.79% of professionals highlighted AI’s effectiveness at pattern recognition in large datasets, emphasizing the core analytical capability institutions expect from this technology.
Platform positioning and product context
The survey was executed by INFORM, which markets RiskShield—a financial crime management platform based on a hybrid AI model combining rule-based logic with machine learning. The platform processes transactions in real time and integrates fraud prevention, AML compliance, and risk management into one environment.
As financial institutions grapple with increasingly stringent regulatory demands and sophisticated fraudulent tactics, the survey suggests that AI deployment strategies are maturing, moving from single-function implementations to integrated, multi-layered defense systems combining machine learning with behavioral analytics.
