BioCatch Reviews

Name: BioCatch
Brand: BioCatch
Rating: 4.0 (1 reviews)

4.0 out of 5

1 review
100% willing to recommend

What is BioCatch?

BioCatch is a cybersecurity company that delivers behavioral biometrics, analyzing human-device interactions to protect users and data. Banks and other enterprises use BioCatch to significantly reduce online fraud and protect against a variety of cyber threats, without compromising the user experience.

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BioCatch is the #4 ranked solution in Fraud Detection and Prevention software. PeerSpot users give BioCatch an average rating of 8.0 out of 10. BioCatch is most commonly compared to ThreatMetrix: BioCatch vs ThreatMetrix. BioCatch is popular among the large enterprise segment, accounting for 80% of users researching this solution on PeerSpot. The top industry researching this solution are professionals from a financial services firm, accounting for 60% of all views.

Buyer's Guide

Fraud Detection and Prevention

October 2024

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Helped 816,406 peers since 2012

BioCatch mindshare

As of November 2024, the mindshare of BioCatch in the Fraud Detection and Prevention category stands at 8.9%, up from 6.8% compared to the previous year, according to calculations based on PeerSpot user engagement data.

Fraud Detection and Prevention

Key learnings from peers

Valuable Features

"It can track mouse movements as well as the actual oriental moments of such as the movement of devices, how they are held, and the angles which at they are held. All these are captured for customers and a behavioral profile is built for the customer over a period of time. This would be matched against any fraudulent behavior. If, for example, suddenly a customer account seems to be accessed by our profile, which is not one particular customer account, if the movements or habits are suspect, we can catch the fraud and shut it down."

Room for Improvement

"BioCatch is one of the fraud detection tools which also has machine learning capabilities and it has what is called a machine learning model feature. It is run in the background. The consequence of those machine models is it is complex to perform data functions and the activity and programming techniques. The decision-making for determining what's happening within those models is a little bit complex and not at all transparent. It's not easy for businesses to understand how the model is using the data of the bank customers in order to come to the assumption it does."

These insights are based on the in-depth reviews provided by peers to help you make a better buying decision.

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