Insurance Fraud Prevention: How It Works and How to Stop It

Insurance fraud prevention costs the US alone $308.6 billion annually, and as more insurers move their operations online, the attack surface for fraudsters has grown substantially. The costs can be felt across the entire industry: premiums rise, legitimate policyholders pay more and the operational burden of fighting fraud continues to drain resources that would be better spent elsewhere.

This article focuses on insurance fraud prevention: the strategies, signals and technologies that allow fraud and risk teams to stop fraudulent claims before they are ever paid out.

Key Takeaways

• Insurance fraud prevention is critical for online insurers, as digital channels increase exposure to identity fraud, false claims and multi-accounting schemes.
• Effective insurance fraud prevention strategies focus on stopping fraud before payouts occur: at onboarding, application and claims submission.
• Common types of online insurance fraud include application fraud, exaggerated claims, intentional damage claims and synthetic identity abuse.
• Modern insurance fraud detection and prevention tools rely on identity verification, device intelligence, digital footprint analysis and behavioral biometrics.
• Real-time risk scoring and dynamic verification help insurers reduce fraud losses while maintaining a seamless customer experience.

What Is Insurance Fraud?

Insurance fraud occurs when someone deliberately deceives an insurance company to obtain benefits or payments they’re not entitled to. A policyholder might lie on their application to get lower premiums, exaggerate to receive a larger payout or stage an accident to file a false claim. What distinguishes fraud from honest mistakes is intent — fraudsters knowingly misrepresent facts or fabricate events for financial gain.

What Is Insurance Fraud Prevention?

Insurance fraud prevention is the practice of stopping fraudulent insurance activity before a claim is paid out. Rather than investigating suspicious claims after the fact, prevention-focused strategies intervene earlier: at onboarding, at the point of policy application and at payment. In practice, this means verifying that applicants are who they claim to be, that the payment methods they use are legitimate and that their behavioural patterns are consistent with genuine customers.

Prevention works alongside detection, but it reduces the volume of fraud that detection ever has to manage. The further upstream a bad actor is caught, the less damage they can do.

Insurance Fraud Prevention vs Insurance Fraud Detection

These two terms are often used interchangeably, but they refer to distinct stages of the same problem. Fraud detection identifies suspicious activity during or after a claim has been made, making it reactive by nature.

Fraud prevention focuses on stopping fraud before it enters the system: verifying identities at onboarding, analyzing behavioral signals at the policy application stage and flagging anomalies before any payout is triggered. The most effective approach combines both. Detection catches what slips through. Prevention reduces how much slips through in the first place.

Hard vs Soft Insurance Fraud

Hard insurance fraud is premeditated. A policyholder deliberately stages an accident, destroys property or fabricates an event in order to file a claim. These schemes are often more elaborate, sometimes involving multiple parties or organised fraud rings.

Soft insurance fraud is more common and harder to prove. It occurs when a legitimate claim is exaggerated to obtain a larger payout — someone who genuinely had their phone stolen might add fictitious accessories to inflate the value or exaggerate injuries to sound worse than they are to secure a bigger settlement. Because soft fraud starts with a real event, it can be far more difficult to identify without detailed data analysis.

What Is the Impact of Insurance Fraud?

Insurance fraud is a serious issue and a punishable offense. Aside from the legal repercussions for the fraudsters, it also impacts the general public. Some of these consequences include:

• Lower margins for insurance companies: Every fraudulent payout eats directly into profitability. Fighting fraud is also expensive — investigations, legal costs and the technology required to detect suspicious activity all carry a price tag. Industry estimates suggest insurers spend billions annually on fraud-related operational costs.
• Higher premiums: According to the Association of British Insurers, insurers detected over 98,400 fraudulent claims worth £1.16 billion in 2024 alone. Insurers recover fraud losses by adjusting premiums across their customer base. The burden is effectively transferred to people who have done nothing wrong.
• Pressure on public resources: In health and car insurance contexts, fraudulent claims divert time and resources from hospitals, law enforcement and emergency services. In the United States, healthcare fraud is estimated to cost between $100 billion and $170 billion annually, accounting for 3% to 15% of total healthcare spending.

7 Types of Insurance Fraud

Insurance fraud often looks like business as usual. The claim is submitted with completed documentation and a story that aligns with the policy. On paper, everything seems legitimate until the payouts are made.

1. False or Exaggerated Claims 

The most prevalent form of fraud, accounting for £466 million in detected claims in the UK in 2024 alone. Policyholders either fabricate a claim entirely or inflate a legitimate one to receive a higher payout. Each insurance company has its own processes for handling claims and ensuring the correct amount is paid under the policy, but volume and complexity make it difficult to manually review every submission.

2. Application Fraud

Application fraud occurs when individuals misrepresent or falsify information during the insurance application process to obtain coverage they wouldn’t otherwise qualify for or to reduce their premiums. Applicants may lie about their health status, income, occupation or the value of their assets. Businesses might understate operational risks or misrepresent the nature of their operations.

3. Fake User Registration and Multi-Accounting

During a typical multi-accounting scheme, stolen IDs (sourced from data breaches or dark web markets) are used to register multiple accounts with an online insurer. Devices are insured under each account, then the fraudster reports them as lost or damaged, collects the payout, wipes the device and sells it.

AI-powered bots can now automate the entire account creation process, spinning up dozens of fake profiles with unique behavioral patterns to avoid detection. Because the identity check fails at registration rather than at the claims stage, catching this type of fraud requires intervention much earlier in the customer journey.

4, Ghost Brokers Scams

Ghost brokers pose as legitimate insurance agents, selling fake or altered policies to unsuspecting customers — often at a discount to appear credible. These scams are increasingly distributed through social media and target less tech-savvy users.

A ghost broker is essentially a fraudster posing as an insurance company. It is a scam that spreads on social media and targets vulnerable, less tech-savvy users. They may also be found offline, spreading through word of mouth or shady local businesses. 

5. Car Insurance Fronting

Fronting occurs when a more experienced driver is listed as the primary driver on a policy to obtain a lower premium, while the vehicle is actually driven by someone else, typically a younger driver who poses a higher risk for the insurer. Because proving who drove a vehicle most often is difficult, fronting is widespread and persistently hard to eliminate.

6. Crash for Cash

A form of car insurance fraud in which collisions are deliberately staged. There are three common variants:

• Staged accidents: A fraudster deliberately damages their own vehicle.
• Induced accidents: A fraudster forces an innocent driver into a collision.
• Ghost accidents: The accident exists entirely through fabricated paperwork.

Crash for cash schemes are sometimes run by organized groups and can involve multiple fraudulent claims across different insurers.

7. Intentional Damage Claim

Common in digital and gadget insurance. The fraudster insures a device, then deliberately damages or destroys it to file a claim for a replacement or payout. The challenge for insurers is distinguishing between genuine accidents and intentional damage — a cracked screen looks the same whether it was accidental or deliberate.

Insurance Fraud Prevention Strategies for Online Insurers

Effective fraud prevention starts with a single question: Is this person real? Everything that follows the initial identity check (claim verification, anomaly detection, investigation) becomes exponentially harder if a fraudster enters the system.

• Surfacing risk early with digital footprint analysis:A single data point rarely tells the full story, and fraudsters are skilled at blending in. Insurers gain critical context by layering real-time data enrichment, including device, phone and email intelligence such as reverse email lookup. A 10-minute-old email with no online presence signals far higher risk than an established digital identity, helping stop fraud before policies are bound or claims are paid.
  Building a risk profile: Multiple identity signals and behavioral biometrics form a complete risk profile, adding depth and clarity to every policyholder and claim interaction. This layered view helps insurers separate legitimate customers from fraudsters with greater confidence.
• Implementing dynamic friction: Instead of treating every interaction the same, insurers can adjust verification requirements based on real-time risk. Behavioral analysis determines when additional checks are necessary, allowing high-risk activity to be challenged while trusted users move forward without unnecessary disruption.

How SEON Helps With Online Insurance Fraud Prevention

SEON’s multilayered solution helps insurers stop fraudulent applications and claims before payouts occur. By combining AI-enhanced risk scoring with real-time analysis of digital footprint, device intelligence, IP data and behavioral signals, SEON builds a dynamic risk profile for every applicant and policyholder.

Built on fraud signals, SEON’s integrated IDV solution verifies who the person behind the document or selfie is, exposing stolen and synthetic identities that may otherwise pass standard controls.

Operating passively in the background, SEON reduces wasted investigative effort while maintaining a seamless customer experience. Low-risk users move forward without disruption, while higher-risk activity is flagged for deeper review or stepped-up verification.

The result is an insurance journey that filters out fraudulent identities at the entry point, turning identity verification and fraud prevention into a proactive operational advantage.

Frequently Asked Questions

Sources

• Insurance Information Institute: Facts + Statistics: Fraud