The most recent additions to the Federal Reserve’s Synthetic Identity Fraud Mitigation Toolkit offer new information about fraud detection technology, data sharing and the value of fraud information sharing within the industry to help fight synthetic identity fraud.
Organizations can enhance their ability to prevent and mitigate synthetic identity fraud using a variety of detection and prevention technologies and approaches. For example, performing a “link analysis” of data attributes across products and channels may help identify synthetics that reuse identity elements (e.g., a Social Security number) in multiple relationships. Machine learning can quickly process large amounts of data to evaluate risk.
“The nature of synthetic identity fraud makes it challenging to detect – which in turn, encourages criminals to leverage synthetics for their own financial gains. More accurate identification and reporting of synthetics with technology and information sharing could benefit financial services companies and the overall industry by ensuring greater visibility into fraud trends and more effective mitigation approaches.”
Mike Timoney, vice president, secure payments,
Federal Reserve Bank of Boston
Within an organization, improved data strategy approaches can increase accurate categorization of synthetic identity fraud losses, decrease fraud loss underreporting and offer insights into the magnitude of fraud, among other benefits. Furthermore, sharing information within the financial industry about known bad actors and new fraud insights may benefit institutions and make it harder for criminals to operate successfully.
Explore these topics and more in the online toolkit, including insights and downloadable resources covering:
- Synthetic Identity Fraud: The Basics – explains what synthetic identity fraud is, why you should care, and why fraudsters commit this type of fraud.
- How Synthetic Identities are Used – describes what is hiding in your portfolio and how fraudsters use synthetics to commit fraud and increase their payouts.
- When Synthetics Become a Reality – outlines examples of common synthetic use cases.
- Detecting a Synthetic Identity – provides tools to help colleagues and consumers identify and prevent synthetic identity fraud.
- Validating Identities – discusses ways to differentiate real customers versus synthetics using a suite of identity validation tools and alternative data.
- Identifying Synthetics – focuses on ways to identify synthetics at different stages of the relationship, including at the account opening, when already existing within a portfolio and during post-loss analyses.
- NEW: Technology Enhances Fraud Detection – presents technologies, approaches and real-life examples of ways to enhance cross-channel fraud intelligence using link analysis, and machine learning.
- NEW: Fraud Data Strategy and Information Sharing – describes how improved data strategy and information sharing can improve fraud detection and mitigation.
Stay tuned for more information and engagement opportunities from the Fed as we continue to collaborate with the payments industry to address synthetic identity fraud.
The synthetic identity fraud mitigation toolkit was developed by the Federal Reserve to help educate the industry about synthetic identity fraud and outline potential ways to help detect and mitigate this fraud type. Insights for this toolkit were provided through interviews with industry experts, publicly available research, and team member expertise. This toolkit is not intended to result in any regulatory or reporting requirements, imply any liabilities for fraud loss, or confer any legal status, legal definitions, or legal rights or responsibilities. While use of this toolkit throughout the industry is encouraged, utilization of the toolkit is voluntary at the discretion of each individual entity. Absent written consent, this toolkit may not be used in a manner that suggests the Federal Reserve endorses a third-party product or service.