In order to maximize the detection capabilities of fraud indicators, insurers can enrich the data sources using their internal data with external data sources. There are numerous data sources available to integrate with the solution, both open source and via industry bodies and commercial data providers. These can cover, but are not limited to, insurance customer history, socio-demographic, geographic, vehicle, and credit information.
Claims fraud indicators can be grouped into four main areas:
- Expert Rules: drawn from the insurers’ claims expertise and based on the company’s internal data to identify typical fraud indicators e.g. five or more people involved in an accident; a claim within 30 days of policy inception.
- Geographical Rules: localising the individuals, the place and the entities involved in the claim and where possible integrating external geographical data to assess environmental risk.
- Relational Rules & Link Analysis: risk assessment based on the relationships between the people involved in the claim and any links to previous suspicious claims history.
- Analytics Rules: Data analysis using advanced statistics techniques and predictive models to identify representative behaviour of fraudulent claimants.