Climate, technology and the protection gap: Top trends reshaping property damage insurance in 2025

26 February 2026

Rachael Murphy

Property damage insurers faced a convergence of challenges in 2025, as climate-driven catastrophes, technological transformation, and widening protection gaps fundamentally reshaped risk assessment, claims handling, and market dynamics across the UK and global markets.

Climate catastrophes drive record losses

Global insured losses from natural catastrophes reached an estimated US$80bn in the first half of 2025, nearly double the 10-year average, with full-year totals projected to approach or exceed US$107bn, down slightly against Swiss Re’s earlier forecast of $150bn.

Wildfire losses, especially the January 2025 California wildfires, accounted for approximately US$40bn alone, the highest such wildfire loss on record, whilst severe convective storms accounted for about US$31bn in H1 2025. The US was therefore the most affected market, accounting for 83% of global insured losses.

The UK market mirrors this escalation. UK insurers paid out a record £585m in weather-related property damage claims in 2024, driven by storms, river floods, and freezing conditions - a 28% year-on-year increase. In the first nine months of 2025, £936m of the total £4.6bn in property payouts (approximately 21%) were due to adverse weather, underscoring the persistent role of climate-linked perils.

In Europe, readers will recall the shocking scenes of devastation following catastrophic flood events in Spain in Q4 2024.

Over the past decade, average annual global insured losses climbed with insured loss growth occurring at roughly 5-7% annually in real terms, driven by urban expansion in risk zones, climate intensification, and more frequent severe weather. This trajectory represents a structural shift rather than cyclical volatility and we anticipate catastrophic weather events will continue at an increasing pace in 2026.

The widening protection gap

Reducing the protection gap has been an agenda item for insurers and policymakers alike for years. However, the World Economic Forum reported a $223bn climate protection gap globally in September 2025, suggesting only around 40% of global catastrophe losses are insured. Faced with escalating climate risks, some insurers are retreating from high-risk zones across the US, leaving behind widening coverage gaps and exposing vulnerable communities to growing financial strain.

The absolute protection gap growing faster than insured losses due to urban expansion into hazard-prone areas, climate-driven frequency of secondary perils, and insurance affordability and availability constraints.

The UK demonstrates stronger insurance penetration but faces similar pressures. A significant proportion of weather-related losses remain uninsured in the UK, driven by flood exclusions and excesses, underinsurance due in part to inflationary pressures on sums insured, and small business business interruption and supply-chain exposure.

Could Parametric insurance be the answer to reducing the climate protection gap? Unlike traditional coverage, parametric insurance pays out automatically when specific conditions (like wind speed or rainfall) are met. This makes it possible for communities to access funds quickly and accelerate the recovery process. This represents an opportunity for transformational shift in approach to insurance models.

Transformational AI-driven claims processing

Artificial intelligence (AI) is now central to claims assessment, fraud detection, and settlement automation for both first-party and third-party claims, with insurers using AI to automate image-based damage evaluation, leading to faster decision-making and a reduction manual workloads. Avantia's launched its 'Holmes' AI-powered claims solution in the summer, claiming controlled tests demonstrated the technology making fraud detection six times more effective and achieved 98% accuracy in payment calculations.

Other examples of the tech advances include remote inspections using drones, satellite imagery and assessments based on homeowners' photos and videos, replacing physical adjuster visits in less complex cases, resulting in shorter processing times, reduced cost, and more customer self-service. Mobile and online self-service claims portals allow policyholders to file, track, upload evidence, and receive updates instantly are increasingly standard, delivering better real-time user engagement and satisfaction.

However, these advances create new risks around bias and transparency. The FCA has expressed concern that AI-driven personalisation could exclude certain groups from accessing financial products, potentially constituting unlawful discrimination, requiring insurers to document all algorithmic decision-making processes and conduct regular fairness assessments.

We expect the risk AI-related property damage and business interruption (BI) claims to increase in prevalence over the coming year, whether from AI malfunctions damaging plant and machinery, and BI claims where disruptions occur. As ever, with new and rapidly changing technologies, the risks around policyholder errors and knowledge gaps and the challenges facing insurers over ‘silent-AI’ cover are all areas that will require consideration in 2026.

Emerging fraud challenges

Whilst technology enables efficiency, there is emerging concern that generative AI and digital tools can be used to fabricate or inflate evidence in claims, potentially increasing fraudulent submissions, requiring insurers to invest more in advanced fraud detection and authentication systems. Fraudulent claims increased to £1.1bn in 2024, with the Association of British Insurers estimating fraudulent property insurance claims cost over £143m annually.

The 'failure to prevent fraud' offence, which came into force on 1 September 2025, focuses on where firms themselves benefit from fraud, creating new compliance obligations for insurers and intermediaries.

Intensification of regulatory scrutiny

Rising oversight around claim acceptance rates and fairness, with some insurers reported to have low acceptance levels, is prompting consumer complaints and regulatory interest, creating greater transparency expectations and potential compliance updates. The FCA's Consumer Duty requirements continue to expand in scope for 2025, with increasing scrutiny for insurers to enhance transparency by sharing more data to demonstrate fair value for their products.

What this means for property damage insurers

With climate risks rising, technology changing fast, and regulations evolving, insurers need to rethink their strategies. Insurers must balance the opportunities presented by AI-driven efficiency, current market capacity and parametric insurance considerations against structural challenges of climate change, widening protection gaps, and heightened regulatory expectations. Success requires sophisticated climate modelling, robust AI governance frameworks, and proactive adaptation to both physical and regulatory climate change.

Articles in this section include:

Business interruption and Section 13A: lessons from Probitas v Pro 2 Care

Authors: Deveshi Patel and Francis Mackie

In Probitas Syndicate 1492 v Pro 2 Care [2025] EWHC 1921 (Comm), the High Court granted summary judgment in favour of Probitas following a business interruption claim by Pro 2 Care, which arose from a Combined Care Home policy. The Court addressed whether the policy provided business interruption cover, concerning water damage to a residential property whilst it was being renovated for use as a children's care home.

Policy construction

The Court held that Pro 2 Care did not have more than a merely arguable case that the policy afforded business interruption cover. The Court concluded that an ordinary policyholder, reading the Schedule and Policy Wording conscientiously and, in their entirety, would have concluded that cover was limited to property damage insurance only.

The Schedule of Values and Deductibles specified detailed sums insured for buildings (£900,000), contents (£100,000) and computers (£15,000), but critically omitted any policy limits for business interruption cover. The Schedule did not identify a schedule of values and deductibles or state the ‘maximum indemnity period’ or ‘sums insured’ for business interruption purposes, information which is essential for calculating any business interruption indemnity.

The Court concluded that, given the ‘conscientious reader’ would not be able to locate any of the critical information required if the policy did in fact afford business interruption cover, it did not make commercial sense to conclude that such cover was provided without any statement of the relevant details or applicable limits.

No operational business

Even if the policy had afforded business interruption cover, the Court held that such cover had not been engaged because no business was being carried out at the property either when the policy incepted or when the water damage occurred, and accordingly there was no insurable interest.

The Court emphasised that it is essential to business interruption insurance that cover indemnifies against the risk of an interruption to business income, namely a partial or total loss of business revenue by reason of an insured event, with such loss calculated as the reduction in actual revenue generated during the indemnity period. The Court further held that:

“it is inherent in the concept of business interruption that there is a business, in the sense of a corporate entity offering goods and services in exchange for money, that is ongoing when the interruption occurs.”

Pro 2 Care admitted that it earned no gross revenue from the property between policy inception and the date of damage and therefore failed to satisfy the definition of ‘business’ under the policy.

Delay in start-up cover

The Court distinguished business interruption cover from delay in start-up (‘DSU’) or advanced loss of profits (‘ALOP’) cover, which specifically caters for delays to new projects and is triggered when an incident delays a project beyond its anticipated commercial operation date and instead commences at a future date when revenues would otherwise have been generated. The Court held that what Pro 2 Care ‘lost’ was its hope of starting a care home business from a particular future date, a risk requiring specialist DSU cover, not standard business interruption insurance.

Section 13A of the Insurance Act 2015

Pro 2 Care counterclaimed for losses of £2,670,950 caused by Probitas' alleged breach of section 13A of the Insurance Act 2015. Pro 2 Care argued that Probitas failed to pay the sums due under the property damage section of the policy within a reasonable time, causing an unreasonable delay of 11 months.

Section 13A of the Act implies a term into every insurance contract that if the insured makes a claim, the insurer must pay the sums due within a reasonable time. This includes a reasonable time to investigate and assess the claim, however what constitutes as ‘reasonable’ remains unclear, and will depend on the factual matrix and all relevant circumstances of each individual claim. The Court held that the issue of unreasonable delay under section 13A is a paradigm example of a factual dispute requiring evidence that cannot be resolved summarily and declined to grant summary judgment on the counterclaim.

Key takeaways for insurers

Policy clarity and schedule completeness: Whilst the Court found in favour of the insurer in this instance, insurers should ensure schedules unambiguously identify operative sections and contain all necessary details (sums insured, indemnity periods, and deductibles) for any cover purportedly provided.
Distinguish BI from DSU cover: Insurers should clearly distinguish between standard business interruption cover (which requires an existing operational business generating revenue) and specialist delay in start-up cover (which addresses delayed completion of new projects). This distinction should be clearly communicated to brokers and insureds.
Section 13A claims require careful handling: The Court's refusal to grant summary judgment on the section 13A counterclaim demonstrates that allegations of unreasonable delay in claims handling will typically require a full evidential examination at trial. Insurers should therefore maintain comprehensive records of all communications with the insured, document claims handling timelines, make staged payments where appropriate and ensure that any unavoidable delays are clearly communicated to the insured.
Reconsideration does not equal acceptance: The Court rejected Pro 2 Care's waiver defence, holding that Probitas had never represented that the previously declined claim was now accepted. Lloyd's had merely communicated that Probitas had agreed to reconsider the claim, which it subsequently did before declining it again. Insurers should therefore ensure that any correspondence with the insured is clearly identified as being without prejudice to any reservation of rights until the coverage position has been determined.

Expert evidence failures: Lessons from SSB Law and the Post Office scandals

Author: Francesca Townsend

The SSB Law collapse

The coverage of the collapse of SSB Law has rightly focussed on the thousands of ‘no win, no fee’ clients facing substantial financial loses because of significant adverse costs because of policy decisions taken by SSB’s directors. In recent weeks, two non-solicitor directors of SSB Group have been disqualified from working in the profession after the SRA made findings of dishonesty. Furthermore, readers may be aware of the Legal Services Board investigation into the regulatory failings of the SRA.

However, there is scant detail on the issues that befell SSB Law’s clients in these high-volume cavity wall insulation claims. Some of the key issues arose from inappropriate use of expert evidence, and it is this issue that we will explore in this article.

Jagger v AXA Insurance UK Plc

By way of an example, in the claim of Jagger (and others) v AXA Insurance UK Plc (2023) 7 WLUK 263, SSB Law issued directly against a defendant insurer pursuant to the Third Parties (Rights Against Insurers) Act 2010, following an insolvency event of one of its policyholders, Heatwave Energy Solutions Limited. The allegations alleged defective or inappropriate installation of cavity wall insulation.

SSB Law sought to rely on the evidence of Mr Charles Millar who was presented as an expert in cavity wall insulation despite SSB having sufficient knowledge from numerous earlier cases in which Mr Millar was withdrawn from providing expert evidence. SSB Law had known that Mr Millar would not be able to participate in any future proceedings at the date of issue of Ms Jagger’s claim. The insurer made an application to strike out or in the alternative for summary judgment, and this was upheld in part. District Judge Dawson determined that it was an abuse of process for SSB Law to rely on the evidence of an expert whose independence was in real and serious doubt.

The Post Office scandal

This issue has of course been echoed in the Post Office (Horizon) scandal, most starkly evidenced by the computer expert Gareth Jenkins. Mr Jenkins was an expert witness in several prosecutions brought by the Post Office and was pivotal in helping the Post Office defend its faulty software system in both criminal and civil cases. Whilst the law states that expert witnesses should be unbiased, independent and that their duty is to the court, Mr Jenkins was in fact an employee of Fujitsu, the company that designed and operated the Horizon system used by Post Office branches.

Not only was Mr Jenkins’ impartiality dubious, but Mr Jenkins told the Post Office Inquiry that he did not understand his duties or what required of him as an expert witness and that there were instances where Mr Jenkins was encouraged to amend the wording used in his statements to be more favourable to the Post Office’s case.

The issues with expert evidence prevalent in both the SSB Law and Post Office scandals emphasises that robust and impartial expert evidence is fundamental to the success of litigation.

Essential requirements for expert evidence in property damage claims

In property damage claims, not only does the chosen expert need to be independent, credible and persuasive, but the expert evidence must also:

Establish the extent of damage: Document what damage actually occurred, including the full scope and severity of the damage sustained.
Prove causation: Evidence a direct link between the ‘incident’ and the damage claimed.
Substantiate the financial loss: Evidence the monetary value being claimed. This can include evidence of the costs of repair and replacement, the diminution in value of the property, loss of use or rental income, and any consequential losses.

The failure of a claimant to adequately discharge the requirements outlined above can facilitate arguments from those acting for the defendant and/or its insurers that any damage occurred was pre-existing, caused by events other than the incident, which is the subject of the claim, or by poor maintenance generally. To this extent, claimants could find their claims under-valued or rejected entirely if it is determined that their expert evidence is lacking.

Key takeaways for defendants and insurers

For defendants and insurers faced with a claim, it is important consider that the strength of supporting evidence determines not only the persuasiveness of a claim but its very viability in legal proceedings.

However, this cuts both ways. Insurers should ensure that their early investigations and decisions are well evidenced, and considerations should be given to obtaining robust expert evidence at an early stage to enable reliance on indemnity decisions.

AI in property damage claims: Time, money, fraud and complaints

Author: Joreen Lord and Rachael Murphy

AI is an extremely prevalent topic that is in the peaks of progression. It impacts many aspects of daily life. AI has revolutionised the property damage claims process, transforming what was once a labour-intensive claims assessment process into a streamlined operation that in some cases can be completed in a fraction of the time compared to traditional claims handling methods. This technological shift is reshaping how insurers, policyholders, and legal professionals approach property damage claims.

Time: Automated damage assessments

AI-powered image recognition can help regarding the estimate of repair costs and severity by analysing policyholder photographs and videos of the damage. This reduces the necessity for on-site loss adjustment.

However, as is a common factor with AI output, this process relies heavily on the quality of the data inputted. The assessment can only be as good as the images provided. Hidden angles, poor image quality, and lighting can hinder the end results. There is also the possibility that policyholders may miss insured defects (or seek to hide pre-existing issues) that a professional adjuster would spot.

AI systems may struggle to assess damage that requires nuanced opinion, such as structural integrity issues, water damage behind walls or foundational issues which may not be immediately visible from photographs.

Specialised input is often a drawback of AI in many situations and in the assessment of property damage AI models are trained on common damage scenarios and may fail to properly assess unusual or complex damage. Other limitations that would be akin to the limitations of a traditional desktop analysis include the inability to touch, measure contextually or test materially to assess the extent of damage. However, provided claims handlers are aware of these limitations it will prove a useful first-line assessment tool, freeing up handlers to deal with the more complex damage claims.

Money: Cost reduction across the claim lifecycle

AI systems can process thousands of claims simultaneously, to help ease one the bottlenecks that once plagued disaster response (although of course capacity within the supply chain for reinstatement works will remain a critical delay factor in response times during catastrophic events).

The use of automated damage assessment reduces cost to insurers by reducing the need for physical inspections, saving adjuster time and travel costs.

Predictive analytics can also potentially predict claim outcomes and settlement parameters to assist with reducing litigation spend.

AI can predict claim outcomes and settlement amounts based on historical data, improving reserve accuracy by enabling more informed decision-making. However, AI systems can struggle with unusual or complex damage scenarios that fall outside their training data, requiring human oversight for non-standard cases.

Fraud: The hidden cost to us all

AI fraud detection has the capacity to prevent fraudulent payouts form insurers. Algorithms can support insurers by identifying suspicious patterns and anomalies in claims data, helping the efficacy of detecting fraudulent claims from the outset. These systems cross-reference claim details with weather data, public records, and historical patterns whilst examining photographs for signs of manipulation or staging. It can also conduct comparative analysis of policyholder and witness evidence as it develops over time, to assess discrepancies or verify connections. At a time when property insurance fraud is growing. The ABI estimates insurance fraud adds around £50 to each honest policyholder’s premium. AI is increasingly used as a tool to fight against fraudulent practices, such as claims exaggeration.

Complaints: Legal and regulatory challenges

Using AI within property damage claims can lead to questions about who is responsible when AI makes an incorrect assessment. The insurer? The technology provider? The algorithm developer?

Disputes increasingly arise over AI-generated valuations, with policyholders raising concerns about algorithmic bias and discrimination. Given the recent Which super-complaint which partly focussed on concerns with both the sales and claims processes within UK home insurance lines, it is evident that there are still significant enhancements required to improve consumer confidence. Deployed in the right way, AI could significantly improve the customer experience during the claims process.

As a result, human oversight of AI decision making is required, but for now at least the UK government has sought to balance fairness against the risk of stifling innovation, since the introduction of its principles-based guidance in 2024, rather than formal statutory legislation. As a result the FCA’s regulatory approach remains principles-based and outcomes focussed, relying on existing frameworks, such as the Consumer Duty and SM&CR to mitigate AI-associated risks.

What’s next?

The property damage claims landscape continues to evolve as AI technology advances. In 2026 and beyond, we anticipate the launch of more AI-backed continuous monitoring technology to assist with detection of issues sooner and minimise the subsequent damage.

The industry is moving towards hybrid models combining AI efficiency overlayed with human decision making. Automated systems will increasingly handle routine claims with real-time dashboards enabling policyholders to check claims status, leading to improvements in the claims experience. Experienced adjusters and handlers will be free to focus on complex cases requiring nuanced evaluation. The perception of AI advancement will likely lead to an increase in customer service expectations. The enhancements in efficiency will quickly become seen as the new ‘normal’ demanded by policyholders, so we do not anticipate allegations of delay in more complex cases will fall away any time soon.

AI has undeniably made property damage claims faster, more efficient, and more cost-effective. Yet realising its full potential whilst maintaining fairness, transparency, and the human touch remains the industry's ongoing challenge. Success requires balancing innovation with consumer protection, ensuring AI serves as a tool for improvement rather than a mechanism for claim avoidance.