Current Situation
Legacy scoring models are ineffective at identifying fraudulent applications. Many institutions use rules based scoring methods and third party data to make decisions. Misclassified bad debt is charged off as a credit loss rather than fraud. Bad debt charge-offs due to first-party fraud may be as high as 20% consumer, non-mortgage losses.
Goals and Objectives
Financial institutions will invest in fraud prevention technology that will provide a complete view of the applicant. FIs will seek out platforms or best-of-breed solutions that collect and analyze numerous data elements about the applicant. The outcome will be a score that indicates probable level of trust.
Technology Deployed
Alternative data services, AI/machine learning, Analytics, Big Data, Cloud, Managed services
Use Case Summary
FIs will use advanced identity analytic offerings to identify likely first-party fraud to prevent early-pay defaults and bust-out schemes.