We leverage more than a decade of behavioral data. BioCatch has created the world’s largest behavioral insights database, from trillions of behavioral interactions per month and billions of sessions across geographies, entities and use cases across our customer network.
Only BioCatch Collects data and analyzed continuously, providing full visibility into the user activity throughout account lifecycle. From login to logout we are reviewing all activity and inactivity, providing fraud teams with a risk score, risk indicators (genuine and fraudulent), and visualization tools that provide step by step session reconstruction. Using the Analyst Station, fraud analysts analyze risky sessions and identify patterns to be able to take action quickly to stop fraud before it happens.
We partner with our customers to develop solutions to the most advanced MOs, our operational model is designed to identify, learn, and incorporate into AI models quickly and effectively. Our experienced team of fraud analysts works closely with customers to identify emerging modes of operation performed by cybercriminals. The BioCatch Data Sciences team continually identifies new tends in data to identify new threats and enhance models with protection capabilities. The BioCatch innovation lab continues to push the envelope on new ways to leverage physical and cognitive digital behavior analysis to drive new insights. BioCatch has over 60 patents to support the innovate, cutting edge technology and proven results with most behavioral biometrics customers in the financial space.
Every users pattern of behavior is unique because they have a unique set of physical traits such as the way they move and click the mouse or hold their phone. And a unique set of cognitive traits such as the way they navigate through fields. When an account is accessed by a cybercriminal (fraudster), our algorithms detect the change in a users behavior that tells us that it is not the usual customer accessing the account.
When we look at the session flow during account activity, we analyze activity against the familiarity of the data being entered. Most fraudsters will input data quickly using advanced computer skills rarely seen among genuine customers. Data that is common for a genuine account holder is often times entered manually or using autofil. Fraudsters will use bots or function keys taking data of spreadsheets or other applications and applying them to the session. Their goal is to get in, perform the transaction, and get out before detection. With BioCatch, their speed works to their disadvantage.
Again, speed is a common denomiator for fraudsters. They often use compromised or synthetic identities to repeatedly attack a site. The fraudsters will be familiar with the banking site, navigate quickly to fill out the mandatory fields only and not pause to make choices genuine users would. They will skip optional fields, like notes or memos and complete the transaction quickly. While genuine users may perform a quick transaction, it is rare for them to move through the process quickly in instances where a new payee is set up. Only BioCatch looks at these behaviors in context.