Visa introduces identity scores that uses AI to prevent new account fraud

Visa has launched a new digital tool to help U.S. financial institutions combat new account fraud – estimated at $10 billion a year.

U.S. cardholders currently spend an average of 15 hours to resolve new account fraud. Most financial institutions employ a layered fraud prevention strategy using multiple tools to combat identity-related fraud. However, many fraud prevention systems are rules-based, with gaps and limitations that may create customer friction or false positives.

“With more than 14.7 billion data records breached since 2013, many of which include sensitive data such as name, tax ID number, and address, new account fraud has been a consistently growing challenge for financial institutions,” said Julie Conroy, research director at Aite Group

Visa’s Advanced Identity Score helps financial institutions make more informed identity-related risk decisions by generating a two-digit Fair Credit Reporting Act (FCRA)-compliant identity fraud score in near real-time designed to help prevent fraud loss at the point of credit or loan application.

It uses artificial intelligence and predictive machine learning capabilities with application and identity-related data to generate a risk score for new account applications to help reduce fraud.

“As consumers, financial institutions and merchants focus on controlling expenses during uncertain times, the cost of new account fraud in terms of money and time lost can be significant. Advanced Identity Score offers financial institutions a powerful tool to use on top of existing systems and processes to prevent identity-related fraud,” said Melissa McSherry, global head of Data, Security and Identity Products and Solutions at Visa.

Visa’s artificial intelligence examines data points in areas including application velocity (the frequency of applications within a period of time), fraud and suspicious activity and bankruptcy data across consumer identity elements. It also incorporates data from government agencies, third-party data providers, law enforcement agencies and self-reported data from consumers.