Insurance has long relied on historical data to understand and price future risk. But a new analysis from Earnix, an insurance technology provider, argues that increasingly interconnected threats are putting pressure on traditional actuarial and operating models.
The challenge extends beyond the emergence of individual risks. Cyberattacks, climate change, technological dependency, geopolitical instability, artificial intelligence, data risk and cloud infrastructure vulnerabilities can interact with one another, creating consequences that are harder to isolate and assess. Some emerging exposures also lack sufficient historical data for conventional actuarial approaches, creating additional challenges for insurers assessing where and how risks can be underwritten.
Cyber risk illustrates the shift. An incident that might previously have been treated as an IT issue can lead to operational disruption, regulatory consequences, financial losses and reputational damage. Where critical infrastructure or connected supply chains are involved, the effects can extend further. Climate risk can similarly move beyond direct physical losses, affecting supply chains, migration, social stability and public policy. France Assureurs’ 2026 Forward-Looking Risk Map highlights the increasing interconnectedness of risks facing the insurance industry.
As historical data becomes less sufficient on its own, insurers are turning towards approaches including hybrid models, machine learning, stochastic techniques and continuous recalibration. These methods can help address exposures where limited historical information makes conventional modelling more difficult. Covéa Group chief data officer Arthur Dénouveaux said, “The real challenge is preparing for what we do not yet know how to model.”
The pace at which some risks are developing is adding further pressure. Soil subsidence, heatwaves and flooding, for example, were previously considered longer-term concerns but are now creating more immediate operational challenges. CCR, using data from Météo-France, projects natural catastrophe losses could increase by 40% by 2050, rising to as much as 60% when higher asset values and territorial exposure are taken into account.
Pricing decisions are also facing greater scrutiny from insurance professionals. A survey of 368 French insurance professionals found that 57.2% identified transparency as the most important consideration in pricing and underwriting decisions. A further 43.2% cited the relationship between price and coverage, while 42% identified price competitiveness.
The quality of the underlying data presents another challenge. Earnix’s Insurance Industry Trends Report, which surveyed nearly 400 industry professionals, found that 83% of executives were concerned that their AI models were being trained using incomplete or inaccurate data. The report also found that 66% believed poor data quality was slowing decision-making.
Matmut Group director of IT transformation François-Xavier Enderlé said, “A world without insurance is a profoundly unequal world.” The findings point to the importance of insurers being able to assess emerging exposures while maintaining the data, analytics and decision-making processes needed to respond to them.
For insurers, the challenge is therefore not limited to identifying new risks. Earnix’s analysis highlights how the changing risk environment is also testing the models, data quality and analytics infrastructure insurers rely on to understand and respond to emerging exposures.
Read the full Earnix analysis.
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