Credit data company FICO has secured five new patents related to fraud, artificial intelligence and analytics technologies, according to StreetInsider reports on Monday (Jan. 7). That brings the total patents now owned by FICO to 192, with 93 additional patents pending, reports said.
“This is an exciting time for analytics and decision management, and FICO’s inventions are propelling change in this field,” stated FICO Chief Product and Technology Officer Dr. Stuart Wells. “Our data scientists continue to be at the forefront of the AI revolution and the progress in intelligent decision automation.”
Two patents, “Detection of Compromise of Merchants, ATMs and Networks” and “Card Fraud Detection Utilizing Real-Time Identification of Merchant Test Sites,” apply to payments fraud. The first outlines a mechanism to create profiles for financial accounts to more easily identify instances of fraud based on existing fraud data. The second describes a tool to detect when fraudsters are “testing” stolen card data via the use of real-time data.
The other three, “Efficiently Representing Complex Score Models,” “Automatic Modeling Farmer” and “Systems and Methods to Improve Decision Management Project Testing,” describe ways to deploy advanced analytics technology in various scenarios.
The first wields predictive analytics to aid IT departments in “operationalizing analytics.” The second outlines an artificial intelligence solution to automate the development of predictive models, and the third focuses on project testing.
FICO is slated to introduce its UltraFICO Score, a new credit score that adds more data to the scoring model, including how borrowers manage their checking, savings and money market accounts. Announced in October, the UltraFICO Score aims to help more consumers get approved for loans, especially borrowers with limited credit histories.
Last month, Experian announced the launch of Experian Boost, which provides real-time FICO scores to customers that connects their online bank accounts with the Experian platform. That solution, too, aims to support borrowers by adding more data into the assessment of borrowers’ credit health.