BioCatch prevents financial crime by recognizing patterns in human behavior. By analyzing as many as 3,000 unique behavioral indicators – mouse movements, typing speed, hesitation, disjointed typing, etc. BioCatch helps financial institutions determine whether a session is legitimate (matching the user’s historical behavior) or fraudulent (deviating from that user’s history and matching known patterns of criminal activity).

Grounded in advanced cognitive research and machine learning, BioCatch enables financial institutions to balance identity, trust, and ease in digital banking. Today, 34 of the world’s largest 100 banks and more than 250 financial institutions rely on BioCatch Connect™ to combat fraud, drive digital transformation, and strengthen customer relationships.

Powered by Microsoft Azure, BioCatch helps banks and enterprises stay ahead of emerging threats by analyzing real-time behavioral data to uncover fraud patterns. The company collaborates with industry leaders, including American Express, Barclays, Citi Ventures, HSBC, and National Australia Bank, through its Client Innovation Board, driving innovation in fraud detection and financial crime prevention.

How BioCatch helps financial institutions

Stop fraud before it happens

Prevent identity fraud at account opening by detecting stolen or synthetic identities based on behavioral patterns rather than static data.

Enhance security without friction

Authenticate users continuously throughout their session, ensuring security without adding unnecessary steps to the customer journey.

Detect evolving threats

Identify behavioral anomalies linked to RATs, malware, and social engineering scams—even when other fraud tools fail to detect them.

Combat social engineering scams

Recognize subtle behavioral changes that indicate a victim is being manipulated into authorizing fraudulent transactions.

BioCatchPrivateOfferBioCatch5.0(1 Bewertungen)

BioCatchPrivateOffer

BioCatch

BioCatchPrivateOffer

BioCatch

BioCatchPrivateOffer
BioCatch
5.0(1 Bewertungen)