SAS and TransUnion partner to develop fraudster predictive model

SAS Canada and TransUnion, a credit and information management firm, have teamed to develop a predictive model aimed at tracking down fraudsters more effectively.
The model will leverage credit file information, in addition to fraud data from a consortium of financial institutions, to enhance fraud detection, a SAS release says.
Participating institutions will have access to a service that leverages TransUnion’s database, which contains more than 20-million consumer credit bureau files and employs SAS’s fraud detection technology – including business rules, social network analysis, predictive modelling and anomaly detection.
The solution will incorporate historical data from participating financial institutions, including approved and declined application data, as well as information on incidences of known fraud. This information, along with TransUnion’s credit bureau information and other TransUnion fraud data, will be incorporated into a predictive fraud identification model. SAS’s advanced analytics will drive the modelling process.
The combination of existing credit bureau data, credit and loan application data and advanced software framework is intended to help financial institutions spot fraudulent activity, especially undetected connections that exist between members of fraud rings.