The digitization of financial services, especially with insurance, is leading to large-scale and major transformations. While this process is creating new growth opportunities, it also signals new challenges and inherent risk. These are the headline messages from a new report from BioCatch, titled “Digital Transformation in the Insurance Sector.” BioCatch is a provider of behavioral authentication and threat detection for web and mobile applications.
The future of biometric data and insurance
One important example discussed in the report is behavioral biometrics. This digital approach can help insurance companies to reduce fraud and to reduce friction in the online experience. Taking fraud first, the use of behavioral biometrics can prevent applicants from using stolen or even synthetic identities to obtain new policies. The process can also lower the chance of account takeovers for filing false claims happening, as well as stopping a person from diverting funds from legitimate claims to fraudster accounts. The technique can also flag up the use of stolen identities for fraudulent policy applications.
What is behavioral biometrics? The term refers to analytics designed to uniquely identify and measure patterns in human activities. The term contrasts with physical biometrics, which involves innate human characteristics such as fingerprints or iris patterns.
Machine learning powerful insurance tool
Friction can also be reduced through the use of machine learning: the technology can be applied to stop false declines on new policies, as well as providing risk-based authentication, which is regarded as more robust than context-based step-up verification.
Both of these factors show the advantage of digitization for insurance companies. Leading insurance companies are now searching for effective ways to find out a uniquely identifying characteristic for each person doing business with the company: this is a case of “not of what you are, but of what you do”, as TechRadar puts it.
This is being undertaken with new software, artificial intelligence and machine learning, designed to detect a range of human and non-human — malware, remote access Trojans, robotic activity — cybersecurity threats. This helps, as the BioCatch report discusses, to reduce the risk of insurance fraud by detecting criminal behavior patterns along with genuine users.
