Synthetic identity fraud is one of the most challenging frauds that enterprises face, with an estimated cost of nearly $5 billion by 2024. Attackers create synthetic identities by gathering personal data and using them for account creation. Synthetic identity fraud is difficult to detect, and fraud prevention models often miss 85% to 95% of potential synthetic identities. To combat this fraud, enterprises are turning to AI and machine learning. The most advanced AI platforms combine supervised and unsupervised machine learning to detect anomalies and patterns in transaction data in real-time. Splunk, Amazon Fraud Detector, and Telesign are among the AI and machine learning-based platforms and tools that can identify and thwart synthetic identity fraud. To improve fraud detection efficacy, enterprises should use a layered fraud mitigation approach and an integrated tech stack. Additionally, a balance between friction and experience is necessary for fraud prevention models to be effective without alienating legitimate customers.
Sontiq is a TransUnion company that analyzed publicly available data on fraudulent activity, including synthetic identity fraud, to identify trends and solutions for fraud prevention.
Joe Burton is the CEO of Telesign, a company that specializes in risk assessment and identification verification platforms using structured and unstructured machine learning.
