Claims fraud detection
Assessing risk in order to reduce exposure by accurately identifying risks and automatically detect cases where further investigation is required at the claim stages of the insurance lifecycle.
What is insurance fraud
Insurance companies are exposed to organised and opportunistic fraud. There are 4 main categories of soft and hard insurance fraud:
- opportunistic fraud in general and retail insurance, which includes exaggerated and fabricated claims, and in commercial insurance where the focus is on organisations, rather than individuals, committing frauds.
- organised fraud involving gangs
- claims fraud is where an individual or organisation makes a fictitious or intentionally inflated insurance claim, for example someone claiming for non-existent jewellery or for a slip or trip which never took place
- application fraud is where an individual or organisation manipulates facts on their insurance application in order to lower their premium, for example someone falsely stating they have never made an insurance claim before.
Clearly, there is a significant difference between opportunistic fraud, where people encounter an opportunity within their everyday experiences to commit fraud and more organised planned frauds.
Fraud is also more common than people think, because we tend to refer to hard insurance fraud, which actually represents the minority of cases. Burning down a building or crashing a car on-purpose is what is called hard insurance fraud because the source of the claim was entirely manufactured. On the other hand, soft insurance fraud is far more common because it consists of inflating the value of a legitimate claim. This type of fraud takes up the majority of an insurance fraud investigators’ time.
A dynamic fraud detection approach
Reducing fraud losses is a high priority for all insurers, with the market recognising they must contain fraud as a ‘managed risk’. There is no room for underestimating the fraudsters targeting the industry, who continually evolve their methodologies in direct response to insurers’ counter fraud strategies. The opportunities afforded to fraudsters by new technologies are driving innovative techniques for perpetrating fraud over the internet. A dynamic counter fraud model is essential for insurers to protect their honest customers and bottom line.
Claims fraud indicators can be grouped into four main areas:
1. Expert Rules: drawn from the insurers’ claims expertise and based on the company’s internal data to identify typical fraud indicators eg. five or more people involved in an accident; a claim within 30 days of policy inception.
2. 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.
3. 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.
4. Analytics Rules: Data analysis using advanced statistics techniques and predictive models to identify representative behaviour of fraudulent claimants.
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