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Consider Tackling Insurance Fraud Detection Before Claims Automation

Arnaud Grapinet | January 30, 2018

As insurers consider using AI based claim-handling bots to handle straightforward low-cost claims, a natural concern would be the resulting increased possibilities of fraud. Given the potential impact claims automation could reap on fraud rates, insurers might consider first getting their arms around fraud detection technologies and processes.

What STP tells us about the relationship between fraud and automation

Many P&C insurance companies have started implementing Straight Through Processing (STP), also known as “One-touch” or “Fast-track” processing to streamline a significant portion of claim volume and as the first step towards claims automation. Such processes usually consist of handlers paying claims directly without the involvement of loss adjusters and sometimes without requiring invoices and quotations. Typically, insurers would apply STP logic to claims falling under a monetary threshold, where the pay-out would be less expensive than costs associated with expert analysis. Concrete examples include baggage claims under $500 within travel policies and water damage under $1,500 for homeowners’ insurance.

Despite still requiring a human touch, STP is viewed as an important first step toward broader claims automation. The manner in which STP expedites the payment process sheds light on the ways claim automation will heighten temptation for some consumers to behave fraudulently.

STP has already given birth to new fraud trends

With the development of STP the industry has seen evidence of two emerging fraud trends. Firstly, some policyholders have been filing multiple similar, and fake claims, just under the STP monetary threshold set by their policies. One travel insurer I’ve worked with has experienced a significant spike in policyholders filing claims for approximately $400 in the months following the implementation of STP. Similarly, a surge of policyholders faking multiple small water damages across several policies was discovered, with each occurrence providing nearly identical descriptions within the claim.

Secondly, policyholders with meritorious damages have been discovered exaggerating the costs for reimbursement up to the threshold amount. This has been especially rampant where repair shops are aware of the number and may be deliberately encouraging customers to fabricate the gravity of damages. A leakage normally quoted at $500 might change to $1,500 following collusion between the parties. Generally, the repairer will offer services for free or at a reduced cost if the policyholder agrees to the scheme.

Both groups have figured out that if they keep claims under $X, compensation will come without question.

The allure to commit fraud is compounded by the relatively low risk for legal repercussions. If an insurer decides to investigate a claim further, the policyholder simply drops the claim, while the insurer generally will not take legal action for such low financial stakes.

To combat this phenomenon some insurers have decided to incorporate basic rules to limit exposure to risk, such as a maximum of two STP claims per policyholder per year. Unfortunately, this type of rule is easy for fraudsters to circumvent as they often communicate the method to friends and family who can do the same on their own policies. Clearly, insurers cannot afford two fraudulent claims per policyholder per year, but this is a legitimate, albeit bleak forecast for insurers that do not remain vigilant as they turn more and more towards automation.

Analyzing the data uncovers that when fraudsters understand the rules behind STP, such as the thresholds or maximum number of claims per year, the fraud scheme usually spreads quickly among policyholders eager to make an extra buck. For example, a European insurance company implemented STP for glass breakage claims under 900€, and in just four months experienced sudden spikes in the rate of glass breakage claims concentrated in pockets of communities across the insurers’ geographical coverage zone.

Fraud schemes are also more likely to spread during natural catastrophes when associated claims are often treated using STP. Policyholders trying to game the system will capitalize on the insurer’s limited loss adjuster resources. During a recent flood in France a large numbers of policyholders, who lived outside of the impact zone, used friends’ flooded basement pictures to make fraudulent claims.

Expectations with the rise of claims automation

With claims automation, the potential for fraud becomes even more dangerous. Without a proactive effort we can expect instances of fraud to drastically increase.  Insurers are typically putting more safeguards in place as they turn to bots to handle claims. In an attempt to outsmart the bot, a policyholder might feel more at ease testing several different versions of the claim statement, until they find the circumstances that warrant coverage.

Insurers should be cautious as they apply deterministic sets of rules to claim-handling bots. If the claim-handling bot is programmed to process claims individually and does not have the capacity to detect trends, once a fraudster succeeds in cracking the system, they’ll know they can repeat the process. The fraudster will inevitably share information with their network, encouraging them to file a claim with similar circumstances and documents, knowing the bot will pay.

For these reasons, it is crucial for a claim-handling bot to integrate a powerful and comprehensive fraud detection solution with the intelligence to compare multiple seemingly unrelated claims to detect unusual similarity in circumstances or invoices, and detect statistically unlikely trends of claims to raise the red flag for human investigation.

Claim automation faces several complex challenges, such as:

  • reaching a precise estimate of the amount of the claim,
  • maintaining a good customer relationship, and
  • understanding the context and the damage with enough precision to propose an appropriate settlement method (payment on estimate, payment on invoice, sending a loss adjuster…)

While bots will always have the recourse to redirect claims back to a human handler at the customer’s request, customers are unlikely to voluntarily notify insurers of fraud detection deficiencies, allowing the potential for fraud schemes to run rampant and millions lost before the insurer catches on.

Thus, the biggest challenge facing insurers wishing to automate claims is not producing a bot capable of going through steps as one might expect. Insurers must first and foremost protect themselves from their increased vulnerabilities through integrating an adequately robust combination of fraud detection tools to safeguard the bottom line.

About the Author

Arnaud Grapinet is Chief Data Scientist at Shift Technology, a solution provider with a focus on enabling insurance organizations to successfully tackle the ongoing and growing claims fraud challenge.  Arnaud can be reached at arnaud.grapinet@shift-technology.com

 

 

 


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