A credit card issuer uses a combination of internal fraud scores, a third party fraud score, 25 business rules and a 3rd party identity verification alert to rank every loan application they receive by fraud risk. They are considering purchasing a new email-based identity verification tool to add to their fraud detection strategy. Before they invest in this new tool they want to run a retrospective analysis to determine how much fraud this tool would have detected and what incremental fraud it would have helped prevent, if any.
The new vendor being evaluated agrees to support a free retro analysis on 6 months of historical applications. Outlier Analytics helps the credit card company prepare an application data file to send to the vendor. The file does not contain fraud tags or performance information. The vendor appends their alerts and risk scores and returns the file. The credit card company then appends the fraud tags and information on which rules were triggered for each application. The file is securely transferred to Outlier Analytics where it automatically is processed through the Optimization Engine. Within seconds performance results are provided showing fraud detection and false positive rates for every risk score segment, business rule and alert. The results provide individual performance metrics and rankings based on incremental performance.