Claims fraud is an important topic, so we’ve written about it several times before. In this blog, I want to discuss how IBM big data capabilities can augment an existing fraud system at any insurer. By wrapping big data around your existing claims fraud system, you can capitalize on available data that isn’t included in your current fraud analysis and gain new insights. While IBM offers a comprehensive fraud solution, you do not have to replace an existing fraud solution in order to take advantage of the IBM big data platform.
As continues to be reported in recent headlines, fraud is on the rise as organized crime rings take advantage of regulation loopholes, overworked adjusters and investigators, easier access to information and a clogged court system. In addition to suffering losses due to fraudulent claims, insurance companies have to divert precious resources to identify, investigate and prosecute fraud at a time when they have little to spare.
With a turbulent economy, increasing financial pressures and rising fraud threat levels from ever-more sophisticated criminals, insurance fraud costs are on the rise.
Many insurers have recently implemented or are implementing advanced claims processing solutions to support interaction with policyholders, producers, adjusters and others in the claims process. Some are wondering if incremental fraud detection capabilities are needed. Others have implemented claims fraud solutions and have achieved a level of maturity in minimizing fraud exposure. In both cases, insurers are wondering if they have fully explored the range of potential fraud.
As insurers increasingly digitize their interaction processes with policyholders and agents, they are supporting emerging capabilities, including the ability to submit and update claims information through smart devices, GPS or telematic devices, laptops, voice and publicly sourced information. To fully benefit from the wealth of information contained in this structured and unstructured information—including free and for-purchase public information sources—insurers are developing big data capabilities to support deeper analysis of emerging fraud or claims overpayment patterns. These capabilities also address the growing demand for increased interactions with producers to support their book of business, including the claims process.
To optimize claims processing in this environment, insurers need to consider the four Vs of big data:
- Volume of available information about all parties related to a claim and an insured. This includes information available within an insurance company and from external sources.
- Variety of available information, including GPS and geospatial information, photographs and videos, social media and sentiment about an event (for example, CAT), as well as structured and unstructured information readily accessible online or submitted by the parties to the claim.
- Velocity to absorb both data in motion as well as changing data inputs from a range of digital, external and internal sources.
- Veracity of information; understanding when information is good enough and when it needs to be further governed and analyzed.
IBM big data capabilities—including IBM InfoSphere BigInsights, IBM InfoSphere Streams and IBM PureData System for Analytics—can deliver analyses that are completed on an ad hoc basis to spot emerging patterns or on a regular basis to monitor changes throughout the claims lifecycle. The findings can then be used to support a closed-loop process whereby findings are incorporated into predictive models for automated ongoing and right-time analysis. The figure below shows examples of how big data capabilities support the claims process.
Insurance companies can use a big data platform to address a variety of data-driven processes, improve efficiency and deliver deep, timely insights.
Stopping insurance fraud requires an aggressive, comprehensive approach that combats fraudsters at each stage of the claim lifecycle. Built from a broad range of industry-leading IBM software, the IBM claims fraud solution allows companies to go on the offensive with a robust set of capabilities. It gives underwriters, adjusters, investigators and managers the tools they need to stay ahead of fraudsters while enabling the company to reduce the tremendous financial impact that fraud can have on business results.
To learn more, read "Leverage big data to fight claims fraud."
See other posts, videos, podcasts and other resources about big data in the insurance industry