Detect suspicious connections and fraud networks, protecting insurers' business. CRIF services enable special investigators and anti-fraud department users to undertake a real-time single entry search across the multiple databases, performing queries based on complex fuzzy matching principles.
Sherlock is a fraud prevention service which allows insurance companies to manage the identification and fraud prevention stages faster and more efficiently.
Multilingual and multiline (supporting motor, home, personal injury, health, marine, travel and pet insurance lines), Sherlock can integrate any internal and external information source, and analyze the results using innovative machine learning and analytics tools. A unique and intuitive interface enables claims and policies to be quickly classified on the basis of the actual risk of fraud, checking personal identity, reporting anomalies, and performing customer intelligence activities.
Using tools which allow users to configure their own expert rules and multidimensional anomaly identification functionality, it is now possible to move from a verification approach based on the characteristics of the individual claim and with a limited number of variables, to the analysis of a combination of multiple variables which are difficult to analyze manually and using traditional algorithms. Therefore, Sherlock enables potentially unknown or not previously identified fraud scenarios to be discovered and individual cases to be examined in more depth, carrying out additional checks on related subjects, third parties and associated addresses through the ntwork analysis function, showing the identified links graphically. Through a simple and comprehensive report, it is possible to quickly identify any anomalies and areas of risk which require further investigation and to analyze the searches carried out thanks to the traceability of all the activities performed on each subject under investigation.
Finally, users can carry out interactive searches in real time, and view on a single screen the aggregate results of all the links generated from a wide rage of variables relating to individuals, companies, addresses, vehicles, e-mail addresses, telephone numbers, etc. which could also be relevant across different claims.