Exaggerated Claims Fraud: The Investigation Workflow Problem Behind the UK’s Biggest Fraud Category

The ABI’s November 2025 fraud report had a headline figure that most people in the industry already expected: fraudulent claims above £1 billion for another year running. But there is a number inside that report that deserves far more attention from anyone running a counter-fraud operation. The category of exaggerated claims fraud accounted for £466 million of the total, making it the single largest fraud type by value across the UK insurance market, and it grew by 10% in a single year.

What makes that figure particularly frustrating is the combination it represents. The biggest fraud category by value also tends to produce the lowest investigation conversion rates, and the majority of SIU workflows were never designed with this fraud type specifically in mind. If your team is running the same investigation process for exaggerated loss that it runs for staged motor accidents or fabricated property claims, the result is that investigators are working harder than they need to and converting less than the referral volume justifies.

This article is about why that happens and what the practical fixes look like.

What Exaggerated Claims Fraud Is and Why It Behaves Differently

The simplest definition of exaggerated claims fraud is a case where a genuine loss has occurred but the claimant has inflated the value or scope of what they are claiming. This can involve adding items to an inventory that were not actually lost, overstating the value of goods that were damaged, or describing an injury in terms that go beyond what the medical evidence supports.

To get the investigation approach right, it helps to be clear about what sets this fraud type apart from everything else in the referral queue. With fabricated fraud, the underlying event simply did not happen. A staged accident, a burglary that never took place, a fire that was started deliberately: the investigator’s job in those cases is to build evidence that the claimed event did not occur in the way the claimant has described, and the entire workflow flows from that central task.

The challenge with exaggerated claims fraud is structurally different because the underlying event is real. Something was stolen, damaged, or destroyed, and the claimant has a legitimate basis for making a claim. The problem is that the amount being claimed does not reflect the actual value of what was lost. Items that were not present have been added to an inventory. Goods that were damaged have been valued above what the market would put on them. An injury has been described in terms that go beyond what the medical evidence actually supports. The claim has a foundation; it has just been built up beyond what the facts warrant.

That distinction carries significant consequences for how the investigation has to be conducted. You cannot simply repudiate the claim, because part of it is genuine. The investigator’s job is to establish what the loss was actually worth, document the gap between that figure and what has been submitted, and build a case for a settlement adjustment that would hold up under FOS scrutiny. That requires a different evidence-gathering sequence, a different decision point, and a different documented outcome compared to a standard fraud repudiation, and running both through the same workflow template is where conversion starts to suffer.

Why the Volume of This Fraud Type Keeps Growing

The figures are heading in one direction, and the industry understands reasonably well what is behind it. Allianz’s counter-fraud team has described the pattern as a shift from greed to need, with cost-of-living pressure nudging people who would not previously have considered inflating a claim towards treating it as a way of recouping some financial ground. The cultural framing of exaggeration as a victimless minor issue, rather than as insurance fraud, is doing a great deal of the heavy lifting.

Admiral’s research, published in 2026, found that one in eight people admitted having exaggerated a claim at some point. CIFAS data on first-party fraud points in the same direction. The people committing this fraud are largely ordinary claimants who have rationalised the behaviour as something that does not seriously affect anyone else, and that mindset is spreading as financial conditions stay tight.

For SIU teams, the practical result is that referral volumes for this fraud type are climbing while investigation capacity is broadly flat. The gap between incoming volume and investigation throughput is the real operational problem, and it is not going to resolve itself.

Why Exaggerated Claims Fraud Investigation Produces Weaker Conversion Rates

The investigation challenge has several connected layers, and understanding each of them is the starting point for any SIU looking to improve its performance on this fraud type. The difficulty begins before a case even reaches the investigation queue, at the referral stage itself.

Claims handlers are trained to spot the signals of organised and fabricated fraud: internal inconsistencies in the claimant’s account, connections to known fraud networks, the kind of patterns that detection systems are calibrated to flag. The indicators of exaggerated loss fraud tend to be quieter and harder to read in a busy claims environment. A valuation that runs a little above what the market would bear. An inventory list that extends slightly further than the circumstances would predict. An injury description that does not quite align with the mechanism of the accident. These signals require a different kind of attention, and referral rates for this fraud type are typically lower relative to actual fraud volume than for categories where the red flags are more obvious.

When a referral does reach the SIU, the investigation has specific requirements that a standard workflow does not always address. Establishing the true value of the claimed items means pulling market valuation data, verifying purchase history against the claimant’s own records, sourcing comparator pricing for the relevant product type, and in injury cases reviewing the medical documentation in detail. All of that has to be assembled and recorded before the investigator can reach a determination, and in most SIU operations today that means logging into multiple data portals and building the evidence trail by hand across disconnected systems.

The good practice guidance from the Insurance Fraud Taskforce has long pointed to structured case documentation as a foundational requirement for fraud investigation across the UK. Structured documentation takes time, however, and when investigators are managing large case loads, exaggerated loss cases are often the ones where the effort-to-saving ratio feels least favourable. Cases end up sitting in the queue without resolution, or they settle at the claimed figure because building the counter-offer case properly would require time the team does not have. Neither outcome is sustainable at the volumes the ABI data is describing.

The MI issue makes things harder still. Most SIU dashboards report total fraud savings, organised fraud operations, and referral volumes in aggregate. The conversion rate specifically on exaggerated loss referrals is rarely broken out as its own metric, which means there is no clear visibility of how many of these cases are reaching a resolution, how long they are taking, or what the average saving per case looks like. A blind spot at that scale accumulates cost quietly.

SIU Investigation Best Practice in the UK for Exaggerated Loss Cases

The SIU teams that are getting better results on this fraud type have generally made a few specific operational changes, and the consistent thread running through those changes is building a workflow that treats exaggerated loss as its own investigation category rather than as a variant of the standard fraud path.

The first change is triage that actually differentiates fraud types. Once a referral is identified as probable exaggerated loss rather than fabricated fraud, it needs its own investigation route with appropriate cycle-time targets, evidence requirements, and an outcome structure designed for the mixed-claim situation it presents. Running it through a generic workflow adds effort without adding accuracy, because the generic workflow was built for a different problem.

The second change is making the right data lookups part of the case rather than a separate manual task. Effective investigation of how to handle inflated insurance claims means that market valuations, purchase history checks, and injury comparators should surface inside the case workbench, not across a set of disconnected browser windows. Every hour an investigator spends switching between systems to collect data that could be retrieved inside the workflow is an hour that is not being spent on the determination itself. This is the core principle behind post-alert insurance investigation management: the enrichment should happen as part of the investigation, not around it.

Documentation is the third area where most teams have room to improve. The basis for any settlement challenge needs to be recorded inside the case file, linked to the specific evidence that supports it, and written in terms clear enough to hold up if the customer escalates to the FOS. Consumer Duty requires that adverse claim decisions are explainable and defensible, and that obligation shapes how the case needs to be built from the moment the referral arrives, not as an additional step added at the end when the hard work is done.

These changes together address the conversion problem at each of its three layers: better routing from triage, faster and more complete evidence gathering during investigation, and cleaner documentation that makes the settlement outcome defensible.

How Purpose-Built Case Management Changes the Outcome

FraudOps was built specifically for the post-referral investigation layer in UK insurance fraud teams, and the way it handles the exaggerated loss investigation workflow reflects these requirements directly. Cases route by fraud type from intake, so a probable exaggerated loss referral follows the right investigation path from the outset rather than sitting in a generic queue. Data lookups from market data sources, and DVLA run from inside the case, which means investigators work from a single workbench rather than across a set of separate portals.

Every valuation decision is recorded against the evidence that supports it, and the outcomes feed into MI that gives the Head of Fraud a clear view of exaggerated loss conversion by line of business, cycle time by case type, and settlement reduction by evidence source. The referral moves through a structured investigation to a documented outcome, rather than cycling in a queue waiting for investigator capacity to free up.

The Bottom Line

The ABI’s £466 million figure for exaggerated claims fraud is not heading downwards on its own, and the conditions driving it, particularly the cost-of-living pressures pushing ordinary claimants into opportunistic inflation, are not easing. Referral volumes are climbing, investigation workflows at most SIU teams were not built to handle this fraud type at scale, and the result is a growing gap between what is being detected and what is actually being converted into a saving.

The practical fixes are specific and implementable without overhauling how a counter-fraud operation runs. Better triage that routes exaggerated claims fraud separately from fabricated fraud at intake, data lookups that run inside the case rather than across disconnected portals, and documentation that builds a defensible settlement basis from the moment the referral arrives: these are operational changes, not a fundamental rebuild. The SIU teams that have made them are seeing better conversion rates and cleaner MI reporting, and the teams that have not made them are typically carrying a backlog they do not have clear sight of.

If your referral queue is longer than your investigation throughput, and your exaggerated loss conversion rate is not a number you can pull quickly, that is the right place to start.