Insurance fraud costs insurers more than $2.2 billion every year in Australia. The Insurance Fraud Bureau of Australia believes that one in every ten claims is dishonest.

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Use case: Fraud detection

Fraud can range from individual policyholders yielding to temptation and filing a single dodgy claim, through to organised crime where multiple parties collude to repeatedly inflate or fabricate claims.

The challenge

Consumers and service providers typically have multiple relationships with insurers. This makes it almost impossible for insurance companies to verify all the information provided by the policyholder or to get an industry view of service providers because of competitive issues and data privacy requirements.

Challenge

The solution

We have teamed up with IXUP, which facilitates secure data collaboration, to enable the creation of an industry dataset to check detailed transaction level claims information across insurance products. This solution obtains detailed claims profiles from multiple insurers and insurance products to look for anomalous behaviour. Our advanced analytics surfaces unusual patterns of claiming that are not visible via simpler techniques using more limited data.

Solution

The outcome

Our analytics can uncover the extent of fraud or estimate the likelihood that a claim is dishonest. We look at industry data in a way that ensures commercial and confidential requirements of the participating insurers and respects the privacy of policyholders. Organisations don’t have to share details with competitors and policyholders don’t have to worry about sensitive information being shared.

More than that, additional data sets can be added to the platform – credit scores, banking information or hospital data – to flesh out specific trends that warrant further investigation. An example would be unearthing a spike in compulsory third party claims for certain combinations of accident type, claimant attributes and health or legal service providers.

Outcome

The benefits

Insurers’ business models are premised on extracting the most complete picture possible in order to pay legitimate claims efficiently and investigate, detect and reject fraudulent claims. This collaboration will give insurers a new level of decision making while maintaining absolute control over their own data.

The outcome would be reduced fraud and simpler processes – in both cases this would mean lower costs that would ultimately be passed on to consumers via lower insurance premiums.

Benefits

Talk to us about big data & analytics

The Finity big data team are available to help clients to fully embrace the substantial opportunities big data technology presents and decide – where to from here?

Aaron Cutter

Ph +61 2 8252 3321
Mobile +61 417 527 204
aaron.cutter@finity.com.au

Use case: Insurance regulation

Use case: insurance regulation

Regulators overseeing the insurance industry frequently ask insurers for information.

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Use case: Provider pricing

Use case: provider pricing

Insurers rely on service providers to deliver quality services at a reasonable cost.

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