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It's time to start winning the fight against insurance fraud

Author: Laura Ballam

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Insurance fraud represents a $308 billion cost to American consumers yearly, and this  continues to grow. Unfortunately, the underground data economy is vast and constantly evolving, making it extremely difficult for insurers to detect fraud - let alone stop it!

If you’re  reading this, chances are you see some form of fraud in your insurance business daily, and it's agonizingly frustrating. You always feel like you're fighting a losing battle because you begin recognizing the telltale signs of fraud only after losses pour in.

And then you do the only thing you can: patch the holes and implement a few more manual checks or processes, only to face a different flavor of fraud a month or two later. Worse yet, you can't be too strict with your anti-fraud measures. If you are, you’ll trigger a cascade of false positives on real customers, which can lead to massive customer service and brand reputation issues.

Because of these complexities and risks, many insurers often feel the cure is worse than the disease. So, they implement a whack-a-mole defensive strategy against the most egregious forms of insurance  fraud and pass on the cost of lost revenue, missed opportunities, and increased resource spending to their customers through higher premiums.

How FDPs are Revolutionizing the War against Insurance Fraud

If the above situation resonates painfully with you, there’s excellent news for you. Finally, the tide is turning! Machine learning, big data, predictive analytics, and artificial intelligence (AI) have been game-changers for the insurance fraud prevention industry. New tools are finally operating at scale with some of the largest insurers, and the results are a significant reversal in fraud losses across all categories of insurance fraud!

One of these leading tools in the war against insurance fraud is a Fraud Data Platform (FDP).

Think of an FDP like a Customer Data Platform (CDP) combined with a predictive analytics tool. Powered by AI and machine learning, an FDP can identify suspicious activity and trends in real-time and flag them for interception and investigation. It also captures critical technical data (such as device fingerprints, session details, network statistics, and even behavioral biometrics), establishes a contextually informed identity for the particular user and session, and interprets this data in a meaningful and actionable way. This data then informs rules that automate fraud detection, interception, and prevention logic.

But what does this look like in reality? Here are three types of fraud that a modern FDP solution can help insurers identify and prevent: 

1. Pay-per-click Fraud

PPC fraud typically occurs when a fraudster artificially inflates your ad traffic. For example, they create bots to auto-click your ads or even trick humans into clicking them. Have you ever been on a click-bait website where the page is so ad-saturated and the ads are so obtrusive it's almost impossible not to click an ad accidentally? These websites are notorious for PPC fraud, and the traffic they send your way has a near-100% bounce rate. The result? These website fraudsters end up making money from your ads—not you.

For example, one large insurer found that an average of 6% of their pay-per-click (PPC) ad traffic was fraudulent. Although 6% might not sound like a big problem at first, this represents a massive loss over time, both in lost opportunities and wasted marketing budgets.

In working with this client, Celebrus flagged an abnormal traffic pattern with a 100% bounce rate. The extensive individual-level details (such as the referring URL, campaign source, and session details) gave a detailed journey of each "visitor" in this traffic pattern. The data quickly corroborated that a "Click Bot" was creating the traffic. The team immediately pulled the targeted ads, redeployed their budget to different ads, and configured rules to counter similar situations in the future.

2. Commercial IP Fraud

Commercial IP fraud is when a fraudster gathers and uses another company's intellectual property (for example, pricing) to undercut that company or use it to its advantage.

One of the shocking realities we’ve found in working with our customers is how often some competitors use questionable (at best) and illegal (at worst) business tactics to gain a competitive advantage.

For example, in one instance, Celebrus FDP identified an unnatural data spike for one of our customers - a single IP address filled out nearly 5,000 quotes in a single day. The team quickly investigated and found the IP address was for a server owned by a competitor. Apparently, this competitor decided it was easier to script a bot to steal pricing than to offer a fair product at a competitive price. The team quickly blocked the bot and set up countermeasures to prevent future attempts.

One of the benefits of an FDP is it allows you to create rules to pass false data to bots trying to scrape your website for data. This functionality introduces unreliability into the data, discouraging competitors from using questionable data-gathering practices in the future. reliability

3. Quote Fraud

An FDP isn't limited to flagging and preventing large-scale fraud. It can also dive deep and intercept individual sessions where there’s suspicious behavior or activity.

This enables an FDP to be used to prevent quote fraud, sometimes called "friendly fraud." This type of fraud is an increasingly popular but negative consumer behavior where a visitor will manipulate the answers on an application form to obtain the lowest price.

For one client, Celebrus intercepted numerous sessions where visitors intentionally modified specific form fields that wouldn’t typically change (such as occupation status, vehicle valuations, and mileage). After each change, these visitors would resubmit the quote until they found the best price. Although it’s true everyone likes a good deal, these would-be customers were committing application fraud.

Our patented solution identified these sessions in real-time and triggered rules to flag these quotes for interception and review. The result was $10 million in savings in mitigated fraud!

These examples only scratch the surface of the potential applications for an FDP in preventing insurance fraud. The simple reality is that fraudsters have had the upper hand for far too long, and businesses and consumers have paid the price. Technology is finally here to level the playing field, and it's time to regain control. Are you ready?

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