KBBS

MODULES

Fraud Detection

 
insurance-fraud-detection-prediction.jpg
 
 

Fraudsters never stand still: their methods are constantly evolving. When trying to detect fraudulent behaviour it's important that insurers exploit all possible approaches before paying a claim. We've designed our fraud detection modules so that they continually improve your capacity to identify fraud risks and reduce wasteful false positives. 

We apply a formidable array of techniques in our automated fraud prediction process. Models trained on your data using the latest machine learning methodologies. Text mining. Fraud profiles. Anomaly detection. Geospatial enrichment. And, of course, any risks highlighted by our Fraud Intelligence and Link Analysis applications. 

But we know that it's not all about us. Our rules engine has the flexibility for you to incorporate your own model outputs and internal referrals. Or, if you prefer, just build rules based on your own knowledge and expertise.

Either way, we'll make sure you have all available information at your fingertips to make the best decisions with our visualisation and business intelligence modules. And at any stage our simulation module lets you compare current results with candidate rule sets to make sure you have the optimal set up for your needs.

Rules Engine: Build rule sets to predict fraud using your data, our model predictions and the outputs from other applications and data sources.

 Insurance Fraud Simulation

Simulation: Compare rule sets against each other in champion-challenger methodology by simulating historical performance.

 fraud detection triage

Triage: Present outstanding scored claims so users can prioritise investigations. 

 insurance fraud visualisation

Visualisations: Construct your own dashboards from a catalogue of data visualisations or build reports interactively.