How LASER is Changing the Game
Over the last 4 years, Finsphere has built and refined an analytics platform that is changing the way users' transactions and login events are authenticated. By unlocking the power of rich mobile network operator data, Finsphere has developed a non-invasive means of evaluating risk and enhancing security for banks, enterprises, and consumers. The LASER Platform (Location Assisted Statistical Engineered Response), powered by a neural net predictive analytics model, which uses rich mobile data and over 60 additional account and transaction data points, evaluates the relative risk of a user or event.
At the heart of the IAS Solution is a set of location-based, precision analytic models, which combine the power of predictive analytics with ‘current state’ information from multiple, independent data sources (e.g. financial account profile, telecommunications) to generate an identity risk score.
IAS analytic models include both expert, rule-based models as well as neural network models. A key input into these identity risk scoring algorithms is physical positioning data, which may take many forms, including latitude and longitude coordinates and location contexts, such as street addresses, postal codes, districts, cities, counties and councils, landmarks, and countries. The algorithms enable the comparative analysis of mobile location data with other location data, such as evaluating the distances between position coordinates or between location contexts, attenuating for maximum potential movement since the event occurred.
LASER is designed to produce an actionable risk score, which can be tuned to the incumbent fraud management system and risk strategies of each customer. The LASER model has a myriad of applications and is fully customizable for each client.