Facial recognition is not new, however the technology has evolved to the point where it is a serious contender in a number of very practical situations. The link to the article below using facial recognition as a tool to gather underwriting data is a case in point. Unlocking the vast amount of information in a face rather than filling out forms on health is a great improvement on data capture as well as customer service, though probably a bit freaky for some of the general population!
Digging a little deeper and running a cursory search on facial recognition on US patents identifies some big players showing an interest: Facial recognition with biometric pre-filters (IBM); Identifying consumers in a transaction via facial recognition (GOOGLE INC); and Facial recognition using social networking information (Facebook).
Retailers are getting in on the act with Amazon Technologies working on a patent that similarly uses live images to authenticate a buyer. The pressure on financial services in fraud reduction, and ensuring security of customer data, makes these developments a welcome addition to the identity verification approaches applicable in many digital processes.
As the old adage says, a picture is worth a thousand words. But for life insurers, the value may go beyond that.That's the objective of a new insurtech startup, Lapetus, which has developed facial analytics software that uses selfies to analyze body mass index, gender, and even physiological age to determine underwriting risk.The platform, Chronos, uses machine learning algorithms to extract human faces from images. Its AI engine then looks for intricate signals that give away information life carriers consider when issuing policies