Emerging Risks: Is the Insurance Industry Ready for an Increasingly Unpredictable World?
Earnix Team
August 2, 2026
For decades, insurance has been built on a relatively simple promise: understanding the past to anticipate the future.
Today, however, emerging risks continue to evolve, and the industry's greatest challenge may no longer be improving prediction alone.
The landscape has fundamentally changed. Emerging risks are no longer simply challenging traditional approaches to risk modeling. They are also exposing the limitations of operating models designed for a far more stable environment.
Not only are entirely new risks emerging, but they are becoming increasingly interconnected, dynamic, and systemic, extending well beyond their original scope.
What these risks have in common is that they are often insufficiently documented to be modeled using traditional actuarial approaches.
Cyberattacks, climate change, technological dependencies, geopolitical tensions, artificial intelligence, data-related risks, and cloud infrastructure vulnerabilities no longer operate in isolation.
Instead, they interact, cascade, and evolve faster than the frameworks designed to anticipate them. As a result, insurers are fundamentally rethinking how they understand and manage risk while adapting their decisions as conditions continue to change.
Insurers therefore have a critical role to play in maintaining the insurability of regions and communities. Certain geographic areas and risk exposures are gradually becoming more difficult to insure, challenging not only existing business models but also the very foundations of traditional insurance.
Emerging Risks Are Reshaping the Insurance Landscape
Consider a cyberattack.
Today, a single cyber incident can trigger operational disruption, regulatory consequences, financial losses, reputational damage, and even systemic impacts when it spreads across critical infrastructure or interconnected business partners.
The same interconnected dynamics can be seen in climate-related risks.
The challenge now extends far beyond natural catastrophes alone. Climate-related risks are increasingly affecting:
Supply chains
Economic migration
Social instability
Public policy
The overall exposure of geographic regions
Several conclusions naturally emerge.
The boundaries between traditional risk categories are becoming increasingly blurred.
As risks become more interconnected, decision-making must become more connected as well.
Pricing, underwriting, claims, and customer engagement can no longer operate independently when the risks themselves do not.
This shift is clearly reflected in France Assureurs' 2026 Forward-Looking Risk Map, where the industry's most significant risks now appear increasingly interconnected and mutually reinforcing.
The Limits of Traditional Models
Within insurance, data science has long been closely associated with actuarial work. However, as risk complexity continues to increase, the need for advanced analytical capabilities is growing rapidly.
Today's actuaries must increasingly:
Build hybrid models
Leverage artificial intelligence and machine learning
Incorporate stochastic modeling techniques
Analyze increasingly complex systems
Why?
Some emerging risks simply lack sufficient historical data. Others evolve so quickly that models require continuous recalibration.
Emerging risks are fundamentally reshaping insurance while exposing the limitations of traditional approaches.
As Arthur Dénouveaux, Chief Data Officer at Covéa Group, explained during Earnix Excelerate Paris earlier this year:
"The real challenge is preparing for what we do not yet know how to model."
Against this backdrop, Insurance-native AI capabilities are opening new possibilities for simulation, anomaly detection, weak signal identification, and large-scale analysis.
However, unlocking their full potential requires these applications to work together. The real value lies in connecting them so that insights can be translated into timely, consistent decisions that evolve alongside changing conditions.
In other words, insurers adopting these capabilities can become increasingly confident in estimating the likelihood of certain events while simultaneously anticipating far greater consequences when those events occur.
This trend is also reflected in recent research from France Assureurs, which identifies artificial intelligence, data quality, and IT process risks among the industry's fastest-growing concerns.
Our latest Insurance Industry Trends Report reinforces this finding. Based on responses from nearly 400 insurance professionals, 83% of executives are concerned that their AI models may be trained on incomplete or inaccurate data.
When Speed Becomes a Risk
For many years, certain risks were still viewed as medium- or long-term challenges. Today, however, many have become immediate—or near-term—operational priorities, particularly climate-related risks such as soil subsidence, heatwaves, and flooding.
According to CCR's projections based on Météo-France data, climate change could result in:
40% higher natural catastrophe losses by 2050
Up to 60% higher losses when factoring in the increasing value of insured assets and growing exposure across territories
This shift is fundamentally changing the balance of the insurance industry.
Understanding risk is no longer enough. Early detection has become essential, but so has the ability to respond quickly. Insurers must continuously adapt their decisions as market conditions evolve while maintaining fair pricing and protecting profitability.
Customers' expectations are evolving as well. According to a survey of 368 insurance professionals in France on the impact of pricing and underwriting decisions on customer relationships:
57.2% identified transparency and understanding as the most important factor.
43.2% highlighted alignment between pricing and the promise of compensation.
42% cited price competitiveness.
These findings reflect a broader shift in what customers expect from their insurer. Fairness is no longer judged solely by the premium itself, but by the consistency between the price paid, the level of coverage provided, and the overall customer experience.
Against this backdrop, pricing and underwriting models must become more flexible and agile. At the same time, organizations need the operational agility to turn new insights into concrete actions quickly and consistently.
The ability to make timely, trusted, and connected decisions is becoming a strategic advantage. It enables insurers to respond more rapidly to market changes while maintaining strong governance, control, and alignment across the organization.
Turning Insights into Action
The challenge is no longer simply producing more analysis. It is ensuring that knowledge can be operationalized consistently across the organization.
Data has become critical infrastructure. Its value no longer lies solely in collecting or analyzing information, but in enabling organizations to make reliable decisions as their environment continues to evolve.
Yet our latest Insurance Industry Trends Report shows that many insurers still struggle to unlock its full potential. In fact, 66% of executives say poor data quality slows decision-making.
As risks become more complex, data quality becomes increasingly critical. But high-quality data alone is not enough. Organizations must also be able to explain how decisions were reached, monitor them over time, and adapt them as conditions evolve. This is why data governance, IT process compliance, digital sovereignty, and information quality are becoming strategic priorities across the insurance industry.
Behind every technological advancement lies one fundamental question:
How can insurers continue making reliable decisions in environments that are becoming increasingly demanding and unpredictable?
At its core, the rise of emerging risks reflects a much broader transformation taking place across our societies. It also highlights the responsibility insurers face in building the capabilities required to adapt over the long term.
Our economies are becoming more:
Digital
Interconnected
Dependent on complex technological systems
Vulnerable to cascading disruptions
In this environment, the role of insurance extends far beyond simply paying claims.
As François-Xavier Enderlé, Director of IT Transformation at Matmut Group, observed:
"A world without insurance is a profoundly unequal world."
A resilient insurance system remains a cornerstone of economic and social stability. It enables individuals to protect what matters most, gives businesses the confidence to invest, helps communities recover after disruption, and allows economies to absorb uncertainty.
As emerging risks continue to evolve, the industry's primary challenge is to evolve alongside them. Doing so requires insurers to transform new knowledge into operational decisions rapidly, consistently, and at scale.
More sophisticated models will remain essential, but they represent only part of the equation. As emerging risks become increasingly interconnected, competitive advantage will depend not only on understanding them, but on turning that understanding into trusted, connected decisions that can evolve as quickly as the risks themselves.
Achieving this requires more than technical innovation. It requires connecting data, analytics, governance, and execution so decisions can be made consistently, explained with confidence, and adapted as conditions evolve. In an increasingly unpredictable world, insurers that build these capabilities will be best positioned to respond to change while maintaining trust, resilience, and long-term competitiveness.
Watch the Earnix Excelerate Paris session to explore these challenges in greater depth.