Commercial insurers are facing a combination of geopolitical, economic and technological pressures that are challenging underwriting models built around relatively stable risk patterns and periodic pricing updates. In a recent Earnix blog, Mark Breading, senior partner at ResourcePro, argues that the changing risk environment is creating new requirements for how insurers collect data, assess exposure and price commercial risks.
Several forces are contributing to the pressure. Conflicts in Ukraine and the Middle East, alongside tariff and trade uncertainty, are affecting supply chains, shipping routes and energy costs. These changes can alter commercial exposures quickly, making it harder for insurers relying on slower rating cycles to keep risk assessments current.
Catastrophe losses are another major factor. The insurance industry has experienced six consecutive years of catastrophe losses above $100bn, while inflation and population movements into areas exposed to natural hazards are increasing the potential scale of losses. These developments are adding further complexity to commercial underwriting.
Financial markets have also become less predictable. Interest rates have moved from a prolonged period of near-zero levels to significantly higher rates, changing investment returns and influencing the behaviour of businesses and consumers. Together, these conditions are making the data underpinning traditional underwriting models less stable.
Technology is creating opportunities for insurers to respond. Telematics and Internet of Things devices can provide continuous information about vehicles, properties and other exposures, giving carriers access to more detailed risk data than static datasets can provide.
New insurance models are also changing how commercial risks can be transferred. Parametric, embedded and on-demand insurance can offer alternative approaches to coverage, particularly across areas such as fleets and commercial property.
Artificial intelligence is introducing an additional challenge. Carriers can use AI to support more dynamic pricing and underwriting, but they must also consider the risks AI creates for their commercial customers. For example, increased automation could reduce employee numbers and affect premium volumes in areas such as workers’ compensation, while creating new exposures that insurers need to understand and price.
The excess and surplus market is another area attracting attention as MGAs develop specialist programmes for complex commercial risks. These businesses can address exposures that do not fit easily within standard insurance products, creating demand for more specialised underwriting capabilities.
For InsurTech providers, the changing environment creates opportunities across data infrastructure, AI-driven pricing, alternative risk transfer and MGA technology. The ability to turn increasingly available data into timely, governed and commercially viable underwriting decisions could become an important differentiator for both technology providers and carriers.
Breading ultimately argues that insurance pricing needs to become more responsive as risk continues to change. The Earnix analysis highlights the growing role of AI, real-time data and technology infrastructure in enabling insurers to adapt their underwriting approaches, potentially creating a wider gap between carriers investing in these capabilities and those relying on traditional processes.
]Read the full Earnix analysis here.
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