Insurers rely on service providers to deliver quality services at a reasonable cost. If claims become too expensive, both policyholders and shareholders will bear the brunt.

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Use case: Provider pricing

Insurers have long suspected that some providers overcharge or exaggerate the cost of services. This might include a claimant who is injured and treated for minor injuries, but the GP or allied health professionals bill the insurance company at a higher rate. Another example is a smash repairer over-quoting and doing larger, unnecessary repairs.

The challenge

The insurance industry currently lacks the necessary information to identify systemic issues with costly providers. To do so means insurers would have to share confidential data with each other. But competitive pressures and the risk of data breach of the personal details of policyholders prevent this option.


The solution

We have partnered with IXUP to facilitate secure data collaboration so that insurers can combine data without breaching privacy or jeopardising competitive intelligence. By combining their data, insurers can develop a more complete picture of how certain providers operate. Using the IXUP platform, we gain visibility into the cost of claims by service provider, enabling it to pinpoint expensive service providers in similar locations.


The outcome

Large datasets drawn from multiple insurers means we can rate providers on their value-for-money, as well as the quality and timeliness of services delivered. We can also create industry benchmarks to guide insurers on selecting providers who fall within desired pricing and service-level parameters.


The benefits

For insurance companies, it means significantly enhancing their ability to choose the best value-for-money providers. The industry will be better equipped to identify price anomalies. Policyholders will benefit from no longer having to pay for inflated provider pricing.


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

Use case: Fraud detection

Use case: fraud detection

Insurance fraud costs insurers more than $2.2 billion every year in Australia.


Use case: Insurance regulation

Use case: insurance regulation

Regulators overseeing the insurance industry frequently ask insurers for information.