New Version of ID Analytics’ Fraud Score Uses Machine Learning to Improve Fraud Detection and Offers Rescoring Feature to Provide Alerts for Increased Risk on Approved Applications

ID Analytics LLC, a leader in consumer risk management, has launched ID Score® 9.5, the latest version of the company’s advanced fraud score for new account applications. ID Score 9.5 leverages machine learning technology to better identify fraud trends, and offers updated modeling to better align with fraud tendencies and the proliferation of compromised identities. Additionally, ID Score 9.5 includes an innovative Rescoring feature that notifies companies if there are significant changes in fraud risk 24 hours after they approve an application.

ID Score 9.5 includes two significant new features, increased fraud detection and Rescore, and is designed to help enterprises meet their compliance and regulatory review needs.

  • Increased Fraud Detection– ID Score 9.5 can help reduce operational costs by remediating fewer accounts while stopping more fraud and improving the customer experience by reducing friction. By updating the core algorithms for identifying fraud, leveraging machine learning technology and new rules that account for changes in fraud attacks since the wide deployment of EMV cards, ID Score 9.5 delivers a best-in-class assessment for application fraud risk. Beta users reported an increase of up to 20 percent in fraud detection.
  • Supplementary Screens – In addition to the core ID Score service, customers can subscribe to a number of supplementary fraud screens to further reduce the potential for fraud risk.
    • Rescore – An innovative solution to look for significant increases in fraud risk in the 24 hours after a new account application is submitted, providing protection to enterprises targeted at the beginning of fraud sprees when less information is available to indicate fraud risk. This can improve fraud detection by 10-15 percent.
    • Signals – Provides companies with insight to support remediation efforts for fraud examiners. Such as whether it is likely first party or third party fraud, and which element of an application is most trustworthy for follow up verification purposes.

Source: ID Analytics Press Release