Top 5 Technologies Improving Insurance Fraud Detection in 2023

Advanced analytics, chatbots, computer vision, IoT sensors, and blockchain are the top 5 technologies making waves in insurance fraud detection today. Insurers are leveraging these technologies in innovative ways to uncover fraudulent patterns and prevent different types of fraud. Read on as we analyze the fraud-fighting abilities of each.

Insurance fraud costs the industry over $40 billion per year in the U.S. alone, according to FBI statistics. Frustratingly, the bulk of these costs end up being passed on to customers in the form of higher premiums. So policyholders also feel the sting of rampant insurance fraud.

Fortunately, insurers now have cutting-edge technologies in their anti-fraud arsenal. Let‘s examine the top 5 and see real-world examples of how insurers are deploying them against fraudsters.

1. Discover Behavioral Patterns with Advanced Analytics

Advanced analytics refers to sophisticated statistical modeling and machine learning techniques that uncover meaningful insights. Insurers use both supervised and unsupervised learning models to pinpoint potential fraud.

Supervised models classify claims as fraudulent or not based on identifiable patterns learned from past fraud examples. This technique is effective at detecting common types of fraud already seen before.

Unsupervised models instead look for anomalies and claims that behave differently than the norm. This allows insurers to stay a step ahead of new fraud schemes they haven‘t encountered yet.

Type of Learning ModelHow It Detects Fraud
SupervisedSpots common markers of fraud from past examples
UnsupervisedHighlights abnormal claims deviating from norm

Behavioral analytics is an emerging technique applying advanced analytics specifically to policyholder actions. By evaluating browsing patterns, clicks, location history, and more, behavioral models identify suspicious gaps between claims and typical customer actions.

For example, USAA uses behavioral analytics as part of its fraud prevention strategy. These insights help USAA recognize shifts in customer behavior that may indicate fraudulent activity across any touchpoint.

Advanced analytics enables insurers to flag exaggerated claims trying to tack on damages from prior incidents. It also detects potentially false claims where customers misreport details assuming certain scenarios won‘t be covered.

2. Speed Claims Processing with Chatbots

Artificial intelligence is powering the rise of chatbots – conversational interfaces that engage with customers through text or voice. Leading insurers now offer chatbot tools to start the claims process through automated natural-language dialogues.

By filing the initial notice of loss (FNOL) through a chatbot, policyholders can provide essential details immediately after damage occurs. This drastically shrinks the window fraudsters have to manipulate claims in their favor.

BenefitHow It Prevents Fraud
Accelerated FNOLLess time for fraudsters to distort data
Prompt photo/videoReduces false or exaggerated claims

For example, Lemonade insurance allows customers to file claims via chatbot for near-instant processing. Their AI Jim is able to settle 25% of claims fully automatically, with payouts deposited as fast as 3 seconds!

The quick claims handling limits opportunities for fraud right from the start. And the chatbot can request photos or videos of damage on the spot – further reducing chances of inflated costs down the road.

3. Assess Damage Cost with Computer Vision

Computer vision is a type of artificial intelligence that can analyze and interpret visual data including photos and videos. Insurers leverage computer vision to estimate repair costs and detect potential fraud early on.

By feeding images and footage of vehicle or property damage into computer vision models, insurers can rapidly generate an approximate cost assessment. This provides an initial impression of required repairs that fraudsters can‘t easily inflate later on.

Computer vision has also shown promising results in identifying manipulated images. For example, models can flag inconsistencies in photos that may indicate staged accident scenes or edited damage. This allows insurers to watch for doctored evidence from the very start of the claims process.

Research indicates computer vision techniques can assess vehicle damage costs with over 90% accuracy when compared to human appraisers. As the technology improves, its ability to detect subtle signs of fraud in submitted imagery will also increase.

4. Receive Real-Time Claims Notices with IoT

The Internet of Things (IoT) is already transforming various insurance segments, especially auto and home. Interconnected smart home devices and vehicle sensors provide insurers with near real-time status updates.

This means insurers can receive automated notices as soon as accidents or property damage occur. For example, OnStar vehicle sensors will contact insurers immediately if airbags deploy in a collision.

By removing reporting delays, IoT shrinks the window for fraudsters to stage accidents or alter details. Insurers also gain additional data from sensors to cross-check claims against.

IoT Data SourceValidates Claim Details
Smart vehicle telemetryAccident time, location, speed, etc
Home sensor activity logsWhen/where damage occurred

In fact, some insurers even offer policy discounts for customers using smart home monitoring systems. This incentivizes tech adoption while giving insurers more eyes on potential fraud-related activity.

5. Stop Double-Dipping Fraud with Blockchain

Blockchain refers to distributed ledger technology that acts as a shared record of transactions. The decentralized structure makes it nearly impossible to change past records or add fraudulent ones.

This provides a mechanism to trace claims through the entire insurance ecosystem. Each stakeholder adds their approval to the permanent blockchain record in sequence.

Because the ledger is immutable and dispersed across networks, fraudsters cannot tamper with it or "double-dip" by filing the same claim with multiple insurers. Only the claim record showing all proper sequential approvals will be considered valid.

By maintaining a complete claims lifecycle record, blockchain also deters staged or exaggerated incidents. Every detail of an accident and corresponding payout is permanently added to the ledger by stakeholders. Fraudsters cannot hide behind informational silos.

So far, insurers like Allianz have already built blockchain solutions to simplify cross-border claims and prevent double-dipping fraud across jurisdictions.

The Bottom Line

Insurance fraud drains over $40 billion annually from the industry, but new technologies are turning the tables. Advanced analytics uncover behavioral patterns while computer vision identifies doctored damage evidence.

Meanwhile, IoT sensors provide real-time loss notices and blockchain ledger networks prevent double-dipping of claims. By combining accelerating technologies like chatbots with transparency from blockchain, insurers have new ways to combat fraud.

While no single solution is a silver bullet, this mix of top technologies arms insurers with sophisticated fraud detection and prevention. As insurers continue to implement them, we can expect the business impact of insurance fraud to decrease over time. Honest customers stand to benefit from these efforts through more accurate claims processes and lower costs.

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