Aside from those technological patterns, many traditional fraud indicators that are present at the time of a claim are also present at the time of application. Make use of this information to help identify policies that may be purchased simply to commit fraud.

No single indicator suffices to deny coverage, but applications that raise suspicion should be taken off of the direct-channel conveyor belt and placed in front of an underwriter, who will ask additional questions to verify information prior to granting coverage. In many instances, a dishonest applicant will not continue with the submission process when required to be in direct contact with an underwriter.

Claims Segmentation
Another proven fraud-fighting technique is to start by segmenting the legitimate claims. Doing that serves two purposes: First, the sooner a legitimate claim gets paid, the greater a customer's satisfaction with the company. Second, quickly identifying claims to fast track reduces the total number of claims that require adjuster or SIU scrutiny. This allows limited claim and investigative resources to focus on claims with some degree of suspicion—saving time and money by putting resources where they are needed most. 

Step one in the segmentation process is identifying "contra-indicators" in the claim file. Contra-indicators are claim characteristics that indicate a claim is likely legitimate and may be paid as expeditiously as possible. For example, a police report, confirmation of transportation by an ambulance, or tests and images verifying an injury may all indicate a claim's legitimacy. 

Cutting-Edge Detection Technology
Once legitimate claims are paid, remaining claims call for efficient fraud detection tools. Fortunately over the past decade, the reduced cost of data storage and the exponential increase in computing power have yielded the ability to leverage more information than ever. 

Text mining has become more accessible because of increased computing. Among the most common applications of this technology is the mining of claims adjusters' diaries. Ideally, an adjuster should recognize and escalate the same suspicious indicators that text mining uncovers. Unfortunately, lack of training or time constraints can prevent an adjuster from picking up on those red flags. Text mining applies a consistent level of scrutiny to every diary entry, ensuring that even subtle indicators will not go undetected. 

A second powerful technique that is rarely used is anomaly, or outlier, detection. The algorithms involved are computationally intensive yet extremely powerful for identifying behavior that does not fit the norm. Adopted from artificial intelligence, the algorithms learn new patterns to detect unusual characteristics even if the anomalous behavior does not include hallmark SIU red flags. This allows potentially problematic patterns to be identified earlier and put into the SIU pipeline for investigation.

The last decade also has witnessed a growth in the identification and analysis of networks, which has resulted in a broad area of research known as social network analysis. Harnessing that research for use in the P&C insurance industry provides the ability to identify fraud rings running various scams, including the following:

• Staged accidents
• Medical provider collusion
• Attorney collusion

Network technology allows insurers to construct holistic claim networks proactively without the need for a known suspect starting point. Once constructed, the networks are scored using advanced predictive analytics that identify those that have unusual or suspicious characteristics. This technology will highlight networks before they fully metastasize by tracking various network velocity measures, such as changes in claim volume. This allows carriers to intervene much earlier in the process and avoid millions of dollars of fraudulent payouts. 

Next Generation
Finally, claims executives need to keep abreast of tools and techniques used in other industries or disciplines. Often, best practices developed by others can be easily adapted quickly and effectively to the P&C industry.

Next-generation detection systems will help predict geographic migration patterns of fraud activity and identify false medical clinics attempting to mask their identity. They will include more and wider-ranging data sources, such as analysis of vehicle and medical images, automated use of social media, voice analysis, and GPS and cell phone data. To make the claims team as efficient as possible, always consider adopting the latest available technology from multiple disciplines. 

The fight against fraud is a constant struggle to thwart ever-changing crooks. In order for carriers to adapt faster than criminals, they must adopt a multipronged approach to fighting fraud that relies upon vigilant detection at every stage of the insurance life cycle.