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Pet insurance market grapples with soaring claims and premium pricing challenges

Pets

Pet insurers face mounting pressure as claims volumes and payouts hit record highs in 2022. Sara Costantini, regional director of Crif, UK & Ireland, explores how insurers could use enriched third-party data, including micro-level geographical information, to predict pet health risks better.

The pet insurance market has historically enjoyed strong returns, but 2022 statistics recently released by the Association of British Insurers [ABI] indicate pressure on premium pricing. At 1.3 million notified, claims volumes are the highest on record, up 28% since 2021.

Payouts at a record-breaking £1bn rose 17% since the previous year. The average pet insurance premium was £327, increasing marginally by 1% since 2021. Meanwhile, the cost of treating sick or injured pets is escalating as modern treatments emerge, which may require insurers to broaden their policy coverage and adjust premium pricing.

The past decade has seen increasing sophistication in pricing in the motor and home insurance market, but perhaps less so in the pet market. The growth of comparison sites and ease of access to competitor pricing for consumers has led home and motor insurers to adopt more dynamic pricing strategies in order to compete for market share and support retention.

Enriched, third-party data has been used to improve risk models and identify additional factors that can help to contribute to competitive advantage. Pet insurers are similarly now recognising the need to leverage new data in new ways, to maintain and grow their market position.

A new solution offering a risk-based score calculated using this previously unavailable date has been launched. Equipping insurers to understand different degrees of risk within small geographies helps them to more accurately and competitively price their policies.
Sara Costantini

Traditionally, pet insurers’ rating engines have focused primarily on the breed, age and any pre-existing medical conditions of the pet. Previously, where geography was considered, it has been at a macro level.

To assist with price optimisation, pet insurers are re-evaluating their pricing models and seeking to include additional data which can impact pet health. Understanding the geography of the pet’s location at a micro, postcode level, including housing and economic conditions and urban architecture, has been shown to help predict the probability of a pet requiring treatment covered by the insurance policy.

A new solution offering a risk-based score calculated using this previously unavailable date has been launched. Equipping insurers to understand different degrees of risk within small geographies helps them to more accurately and competitively price their policies. Competitive advantage comes from the ability to simply integrate the score with their rating engine and flex their premium pricing based on this previously unavailable intelligence.

The pet insurance market continues to grow, representing significant opportunities for established providers and new entrants. The number of UK households owning a pet jumped to 62% in 2022 from 41% in 2020, according to Statista. The UK has an estimated 13 million dogs and 12 million cats. Whilst it is reported that owners spend £9.7bn a year on their animals, anecdotally, cases of under-insured and uninsured animals are rising.

The cost-of-living crisis is causing pet owners to shop around for their cover, searching for the best-priced policy that meets their needs. As a result, competition to retain and grow market share is becoming much stronger for pet insurance providers. The ability to optimize pricing is vital for existing providers and those new entrants to the market who lack historical data.

Enriched third-party data is the way forward, as the motor and home insurance markets already demonstrated. The ability to translate that data rapidly and meaningfully to inform pricing will be crucial. Pet insurers who embrace the agility provided by enriched data combined with sophisticated pricing tools will be able to take advantage of the opportunities presented by a competitive market and, at the same time, improve their profitability and preserve their loss ratio.

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