The Power of Sharing: Why Collaborative Data is Essential to a Healthy Pet Insurance Market

The Power of Sharing: Why Collaborative Data is Essential to a Healthy Pet Insurance Market

Across insurance personal lines, industry-wide data sharing has been standard practice for decades in the UK. It underpins fairer pricing, faster claims management, stronger fraud mitigation and critically better outcomes for honest customers. As pet insurance matures and consequently claims volumes and pay-outs rise, applying the same collaborative disciplines can deliver tangible benefits: smoother consumer profiling and underwriting, risk-based pricing, quicker and more accurate claims processes, and streamlined fraud detection.

Why is data sharing essential today?

The pet market has grown rapidly, with rising veterinary costs and record claims volumes. ABI data shows that in 2024 UK pet insurers paid a record £1.23bn, the third consecutive year above £1bn, across 1.8m claims (about 4,900 per day). The average claim reached £685, with some procedures, like elbow dysplasia treatment, costing £50,000+. More pets are insured than ever (4.6m, +3% vs 2023 and +33% vs 2019), but claims inflation remains an issue [1].

In this context, responsible data sharing can help insurers:

• Validate and pay genuine claims faster, improving NPS and reducing attrition.
• Detect fraud, preventing the costs of dishonest behaviour being passed to honest policyholders. In 2024, UK insurers detected over 98,400 fraudulent claims worth £1.14bn, with motor and property the biggest contributors, a clear reminder of what coordinated data can prevent.
• Strengthen underwriting discipline, using cross-market history to check material facts and curb non-disclosure, now increasingly important at underwriting, not just at the claim stage.

What have personal lines learned from 25+ years of data sharing?

The UK’s Claims and Underwriting Exchange (CUE), established in 1994 and managed by the Motor Insurers’ Bureau (MIB), is a central database of incidents reported to insurers across motor, home and personal injury. Its purpose is to make fraud harder and pricing fairer for honest customers. Over time, CUE has evolved from a claims-only backstop to a tool used earlier in the lifecycle, including at quotation and underwriting.

Positive impacts are evidenced in other insurance lines:

• Underwriting: checking prior incidents to uncover a full claims history and reduce non-disclosure, optimising customer profiling and pricing, preventing fraud at point of quote and point of sale.
• Claims handling: spotting duplicate, inflated or recycled claims; reconciling conflicting histories across multiple carriers; and accelerating legitimate settlements when facts line up.
• Fraud detection: identifying patterns such as serial claimants, organised rings and overlapping losses across insurers, capabilities later reinforced via fraud intelligence bureaus and organisations.

These market-level utilities succeeded because they are reciprocal, members both contribute and access information, regulated by clear governance and compliant processing.

How can these lessons be applied to pet insurance?

Pet insurance faces a distinctive blend of high emotion, complex clinical pathways and escalating treatment costs. Data sharing can deliver three concrete wins:

1. Sharper underwriting at onboarding: Bring checks forward to application: has the pet or owner recorded prior claims or disclosed chronic conditions on other policies? Early insight reduces adverse selection and prevents issues surfacing only at claim time. Personal lines have shown how moving from “claims-only” checks to “pre-inception” screening improves portfolio quality.
2. Faster, fairer claim management: Verify ownership, pre-existing conditions, pet information submitted, previous claims or concurrent policies across the market to reduce friction and pay genuine claims sooner. This matters when owners face four-figure vet bills and need rapid decisions. The claims stage is where trust is truly earned between pet insurers and their policyholders.
3. Stronger fraud controls without penalising the honest majority: Common pet frauds include fake accidents to cover pre-existing conditions or intentionally injured pets, insuring imaginary pets, staging pet disappearances, pet swapping and the submission of inflated and exaggerated veterinary bills. Cross-insurer visibility is the most effective and practical way to reveal such patterns, protecting honest policyholders from subsidising losses and insurers from paying out for fraudulent claims. Broader industry statistics confirm the scale of fraud pressure and the value of collaboration.
4. Fewer complaints and higher customer satisfaction through upfront clarity: Validate key information at policy inception rather than at claim stage. Confirm pre-existing conditions, prior claims and coverage limits early, so pet parents don’t feel miss-sold to when they need help most. This proactive approach not only reduces disputes and strengthens trust but also ensures owners understand what their policy truly covers and allows them to make educated decisions regarding the health and care of their pet.

Crucially, data sharing enables insurers to take more informed decisions and price policy premiums on the true risk involved: when prior clinical history and cover details are available, legitimate claims can be triaged and approved faster, especially for time-sensitive treatments.

What does “good” look like for a pet data‑sharing scheme?

Risk management and fraud prevention are at the heart of insurance. For decades, the Claims and Underwriting Exchange (CUE) has been a cornerstone for UK insurers, providing a trusted way to verify claims histories. As a centralised resource built collaboratively by insurers and provided by nominated suppliers – CRIF is one of those – CUE still delivers unmatched support for smarter risk assessment and fraud mitigation, helping protect both insurers and their customers.

Drawing on the CUE model, and adapting for pet specifics, pet insurers can now have a holistic view of the pet insurance claim, and the parties involved:

1. Scope & identifiers

• Core fields to validate animal identity (e.g., microchip when available), owner, prior claims/incidents, policy start/end dates, and key outcome codes, sufficient to detect fraud and validate cover without unnecessary medical detail.

1. Lifecycle coverage

• Rather than limiting checks to the claims stage, pet insurers can now apply validation from underwriting and onboarding right through to claims. This mirrors the evolution in Motor and Home, where success came from moving beyond “claims-only” checks to a full-cycle approach, improving accuracy, reducing risk and strengthening trust.

1. Reciprocity rules & data quality

• Contribute to access, set data-quality SLAs, enable corrections and challenge processes, log access, and report KPIs (e.g., prevented duplicates, reduced average time-to-settlement).

1. Compliance and consumer duty

• Compliance frameworks and consumer duty principles are essential to ensure fair treatment and trust. Industry best practice includes clear participation and reciprocity rules, privacy-by-design approaches, and competition law awareness. These measures safeguard data integrity, uphold transparency, and protect genuine customers from fraud while maintaining market fairness.

What parallels can we draw with private medical insurance (PMI)?

PMI has long balanced sensitive health data with the need to validate eligibility and manage fraud. The lesson for pet insurance is not to mirror clinical depth, but to share proportionate, insurance-purpose data (claims/incident metadata, policy status, identifiers) under a robust governance. Insurers can rely on legitimate interests for fraud prevention and insurance administration, while applying strict access controls and minimisation.

What does the future hold for liability and customer outcomes?

Third-party liability for dogs is already included in many pet policies and widely recommended (typical limits up to £2m), reflecting increasing public sensitivity to incidents involving dogs. While there is no general UK legal requirement for dog owners to hold liability cover, industry and consumer guidance highlight why this protection matters. Should uptake expand further, cross-insurer verification of liability claims and histories will grow in importance.

Pet insurance is on the same journey motor and home made a generation ago: from siloed information to responsible, reciprocal data sharing that raises standards for everyone. If we pair a tightly scoped dataset with strong privacy and competition guardrails, the rewards are clear: faster, fair payouts for genuine customers, and healthier books of business for insurers.

[1] https://www.abi.org.uk/news/news-articles/2025/5/insurance-payouts-for-pawly-pets-top-1-billion-for-third-year-in-a-row/