Combatting insurance fraud requires insurers and investigators to make intelligent use of reliable data sources.
So, what kind of data should businesses consult to positively identify cases of insurance fraud? Let’s examine the chinks in the armour of insurance and figure out how data can fill them.
If there’s one element that is foundational to the ideal of an insurance relationship, it’s trust.
Unfortunately, trust is in high demand and short supply.
Trust needs to go both ways in insurance. Customers need to trust that they’ll receive the requested support or compensation in line with their contract. Insurers need to be able to trust that their customers are who they say they are, and that any claims are legitimate.
It’s this last point that so often puts strain on the trust in an insurance relationship. With insurance fraud running rampant, trust is a luxury insurers cannot afford to give out blindly.
The motivations for fraudsters attempting to scam insurance companies vary. For organised fraudsters, exploiting and undermining insurer trust through any available opening is part of their day-to-day affairs.
Increasingly, insurance fraud is seen as a form of “soft fraud” by the public. Due to mounting economic pressure from the cost-of-living crisis, otherwise law-abiding individuals are more likely to risk making falsified claims.
This issue has been highlighted by various thought leaders in the insurance space. Adam Winslow, Aviva’s UK and Ireland general insurance chief executive, explains this behaviour as “short-term decisions as a consequence of the macroeconomic recessionary style environment” — motivating attempts to shore up personal finances using falsified claims as a method to gain access to a bit of sorely needed cash.
Aviva is well aware of the climate around insurance fraud — in 2021 they uncovered an estimated 11,000 fraudulent claims, which added up to more than £122 million. The true number is certainly even larger, due to claims which slipped through the net and those still under investigation.
This spike is evident across insurance as a whole, including motor, device, property and personal injury insurance.
Insurance company Zurich attributes a 25% rise in their fraudulent property claims to economic pressures in 2022 — adding up to over £40,000 per day fraudulently claimed, but prevented.
And this trend shows no signs of slowing down: financial crime is expected to become “even more prolific” in line with increasing living costs, according to the UK’s Financial Conduct Authority (FCA).
In order to weather this rise in insurance fraud, businesses need to implement robust and intelligent measures to ensure they are no longer seen as an easy target for opportunistic individuals.
Traditional counter-fraud measures were limited in their ability to take a preventative approach, largely focused on identifying and resolving incidents of fraud after the fact. At a time when insurance fraud was less of a universal constant, this would suffice.
Education played a large role in this — training employees to spot patterns and suspicious signs which may indicate fraud, as well as warning customers of the characteristics of certain scams, such as ghost broking. This is and has been an effective component of counter-fraud strategy, best taken as part of a broader approach.
Likewise, having proactive in-house or external investigations teams is a vital element in catching instances of fraud after they have occurred, however they are only as good as the data they have access to.
Insurance companies leave themselves vulnerable when they rely on weak data throughout their fraud prevention strategies, but especially during initial KYC and screening. It can be tempting to solely utilise credit history to verify that a potential customer is who they say they are, however credit history is less inclusive than alternative data sources.
All these practices are effective and play an important part in fraud prevention and investigations. However, what was previously sufficient is increasingly becoming a vulnerability in the age of constant insurance fraud. The FCA warns of this, explaining that fraudsters are a “complex and ever-evolving enemy. They will adapt to exploit new weaknesses in the financial system, and they will constantly vary their tactics when targeting the vulnerable for fraud.”
Insurers need to implement data which is just as adaptable and targeted as the approaches of the fraudsters they’re looking to repel.
In the face of these challenges, sophisticated new data points can provide a substantial uptick in positive identifications of fraud throughout the process.
Mobile Network Operator (MNO) data is particularly useful for this purpose. These data points contain useful pieces of information about a mobile phone contract, such as who it belongs to, and recent changes to the device and number. By querying this data, businesses are able to access authoritative insights about customers suspected of fraud simply from their phone number.
While MNO data has broad functionality across verification, authentication and validation, there are a few checks in particular which are especially useful for insurance fraud investigations:
This requires negotiating and contracting with mobile network providers to access their heavily guarded data — and from there, extracting and interpreting the data within your own processes.
However, at TMT ID, we have already done this for you. We have cultivated close relationships with the largest MNOs in the UK and France and built a customisable API which allows our clients to get the most from these insights with minimal hassle.
If you’re an insurance provider looking to keep up with the rising tide of fraud in your industry, we’re here to help. If you’re ready to explore the possibilities of MNO data, let’s organise an initial call or demo — we would be more than happy to discuss your requirements and provide any further information you might need.
Last updated on June 24, 2026
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