Application fraud costs the insurance industry millions every year and the shape of the problem is shifting. Cifas’s latest Fraudscape report found that while false application fraud cases fell 24% nationally in 2025 (following an unusually high 2024), insurance identity fraud specifically rose 26%, over 16,000 cases. Fraudsters are moving away from simple non-disclosure toward identity and document fraud, exactly the kind of fraud that’s hardest to catch manually.
Unlike fraudulent claims, application fraud happens at the start of the insurance lifecycle, applicants misrepresenting or failing to disclose details material to their quote and policy, to save money or secure cover they wouldn’t otherwise get.
Some lines suffer more than others. Life insurance can be lucrative for fraudsters given the complexity of applications and the size of payouts and the cost of motor insurance means car insurers have to stay especially vigilant, the Insurance Fraud Bureau found over a third of drivers aged 18 to 24 think it’s acceptable to lie on an insurance application to save money.
The cost-of-living squeeze and rising premiums have both been blamed for growth in application fraud and the shift to fast, online applications has made it easier for applicants to input fraudulent details. Fraudsters’ techniques keep diversifying too, making it harder for insurers and MGAs to keep pace.
The main types of application fraud are:
- Misrepresentation or non-disclosure: An applicant enters inaccurate information or withholds material details to secure cover they wouldn’t otherwise get, or to cut their premium. “Fronting” on motor insurance, listing the main driver as a named additional driver, is a classic example. In health insurance, it might mean not disclosing a pre-existing condition.
- Falsified documents: Fake documents are a growing problem, particularly no-claims authentication on motor insurance, where AI tools have made it easier to produce convincing fakes. Cifas recorded fake no-claims documents in 9% of false application cases in 2023, more than double the 4% recorded in 2022 and the identity-fraud rise noted above suggests that trend has kept building since.
- Ghost broking: Applicants are conned by fake brokers who complete fraudulent, inaccurate applications on their behalf. The applicant ends up paying for cover that doesn’t meet their needs, the insurer misses out on the premium it should have charged and it can cause serious problems if the applicant later tries to claim.
How insurers and MGAs can identify and prevent application fraud
Advanced analytics and machine learning
Data analytics and machine learning can spot application patterns and anomalies based on historical data, an unusual spike in applications from one region sharing similar high-risk characteristics is a red flag worth investigating. Given the right data, machine learning can also link fraudulent claims back to the original application.
Identity verification processes
Fraud is much harder to commit where strong identity checks are in place: document scanning, facial recognition, SMS-based codes, biometric checks and device fingerprinting, which spots multiple fraudulent applications coming from the same phone or computer.
Cross-reference data
Public records and shared insurance data help verify what an applicant tells you. Credit bureaus and licensing agencies can confirm addresses, credit history and employment, making inconsistencies easier to spot and email intelligence tools can score an address’s fraud risk based on its history.
Robust application review processes
Manual background checks on every application aren’t realistic, they slow down quote and bind and drain resources. Automated checks close that gap: velocity checks assess how fast an application was completed and behaviour monitoring flags unusual patterns.
Share knowledge across your team and with the wider industry
Fraudsters keep evolving, so staying current means participating in industry fraud-prevention networks, training staff regularly on the latest techniques and giving them a straightforward, confidential way to report anything suspicious.
Reducing fraud risk with Insly
Stamping out application fraud is central to reducing losses and protecting profitability and it’s exactly the kind of risk that low-risk insurance software is built to manage. Insly collates and streamlines application data, flags inconsistencies automatically and integrates with third-party fraud solutions, so fraud detection isn’t left to chance or manual review alone. Nora, Insly’s AI layer, adds to that by automatically extracting and structuring submission data from emails, PDFs and other documents at intake, so those checks are working with cleaner data from the start rather than whatever a manual re-key happened to capture.
Insly’s system is also highly customisable, with no technical limit on adding further layers or tools for fraud detection, so it can flex to whatever specific fraud risks your book of business faces.
We work with 70+ MGAs and insurers and on average our customers handle double the gross written premium they managed on their previous systems.
