Articles - Retail, leisure and hospitality: Cutting out AI fraud claims



AI can make fraudulent claims look more credible, especially when your teams are under pressure. How can going ‘back to basics’ help protect your retail, leisure or hospitality business? AI is amplifying existing risks, Willis’ Cyber in Focus 2026 report shows. In this insight, we look at how AI is heightening fraud and claims across the retail, leisure and hospitality industries and how you can get ahead of these AI-amplified risks to your revenue and reputation.

By Teresa Long, Industry Leader – Retail, Leisure and Hospitality for GB Risk and Broking, WTW

How is AI driving heightened fraud risk for retail, leisure and hospitality businesses?
AI is helping fraudulent claimants transform what would have been a short or patchy complaint into a detailed claim, with a chronology, confident wording and realistic images that support their account. Fraudsters can produce this content in seconds, enabling high volumes of claims without substance with little demand on their time or other resources.

The volume and sophistication of fraudulent claims is making it harder for teams to distinguish them from genuine customer issues, particularly where retail, leisure and hospitality organisations feature busy sites, lean customer service or claims teams or high staff turnover.

What practical steps reduce retail, leisure and hospitality organisations’ exposure to AI-enabled claims?
Reducing your exposure to AI-enabled claims demands the ‘back to basics’ discipline similar to that you might apply to traditional claims: strong reporting disciplines, training your people to identify warning signs and creating clear audit trails.

Your people need to know that polished wording and professional-looking images don’t prove the facts. Frontline staff are your first line of your claims defensibility. They need clear prompts they can be ready to deploy during busy shifts or backed-up complaints queues: what happened, who saw it, what records are there?

Junior or transient staff may not see how a missed photo or incomplete log or can drive investigation costs, your business’ reputation and your ability to defend a claim. They may also need explicit permission to pause, check the incident log, ask for missing information or escalate to someone with claims experience.

Processes that are hard to access or take too long to carry out are likely to fail on a busy shop floor or hotel reception, during restaurant service or if you operate a call centre where your people are handling high volumes of complaints. Think about easy-to-use processes, clear ownership of roles and responsibilities when someone makes a claim — both on-site and online – and a route to preserving evidence and escalating cases.

How can you review claims data to identify AI-related issues early?
Monitor and analyse claims activity, making sure you have a process that flags warning signs, such as repeated wording or image types, unusual timings or concentrations in particular locations. You need to be able to capture unusual activity and have a process for triggering a closer review.

If your claims teams have a way of comparing the trends it’s seeing with wider market experience, they’ll be in a better position to separate isolated service issues from AI-supported.

Can you trace a claim from first contact to settlement, challenge or escalation. Where did it start? Who handled it first? What evidence did they capture?

If a location, product line or channel shows higher volumes, you may want to investigate whether poor recording, weak escalation, an operational issue or AI-supported claims activity caused the increase.

If you’re facing high volumes of claims, your teams may benefit from a clear framework for triaging cases that look doubtful but lack enough evidence to justify a harder stance. This framework should help teams weigh cost, available evidence, customer experience and reputational risk consistently, ultimately saving time and resources.

How can your organisation strengthen claims defensibility against AI-enabled fraud?
Check smaller sites can capture the same core information as your flagship locations: date, time, place, people involved, condition of the area or product, action taken and evidence preserved.

Test your written procedures against recently closed incident records and claims files. Review the records, speak to the teams who created them and check whether your escalation routes are clear to the people using them. The findings from these exercises can identify practical improvements in training, forms and reporting, or give you assurance you’re getting the basics right.

Get the industry specialist support you need to protect your business against AI-enabled claims. Get in touch with our retail, leisure and hospitality specialists.

 

 

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