From volatility to resilience: how a new era of risk is transforming underwriting

This article is based on a discussion between Penny Seach, Chief Underwriting Officer at Zurich, and Joe Peiser, CEO of Risk Capital at AON, moderated by Peter Caminiti at Zurich’s Global Risk Management Summit 2025.

Navigating a world of accumulating risk

Today’s risk landscape reflects a period of profound complexity. Geopolitical shocks, climate volatility and litigation headwinds are interacting in new and unpredictable ways. What once appeared as isolated events are now part of a tightly interwoven system, where disruption in one area can quickly ripple across others.

Artificial intelligence (AI) is reshaping both our understanding of this complexity and our ability to respond. The scale, speed and sophistication of technology, data and analytical solutions is rapidly transforming traditional approaches to both underwriting and risk management. The move from static, retrospective models to dynamic, predictive intelligence is helping businesses understand and quantify risk and concentration vulnerabilities in a far more thoughtful and insightful manner.

This is particularly notable in three domains: geopolitical volatility, natural catastrophe risk and liability exposures.

Geopolitical volatility: Redefining scenario planning

Geopolitical risk has unsurprisingly surged up the corporate agenda, and is often suggested a top ten risk for leaders. From trade tensions and tariff changes to regional wars and political unrest, global uncertainty is testing both supply chains and strategic planning.

Businesses are shifting from ‘just in time’ supply chains to ‘just in case’ models, as companies increase their buffer stocks. Meanwhile, mapping out secondary and tertiary suppliers is becoming the norm. 

However, businesses are not just navigating heightened volatility, but also the aggregated impact of multiple risks – or unknown concentration of exposure. It is immensely challenging to connect these dots and consider the possible impacts of these correlations.

In this environment, close cooperation between businesses and their insurers is essential. Today, underwriters are looking beyond single risk exposures to the broader risk culture within an organization. They are working with customers holistically to collectively consider a range of scenarios and possible approaches to risk.

Natural catastrophe: from reactive response to proactive resilience

Meanwhile, the frequency and cost of extreme weather events are continuing to rise. What is particularly challenging for insurers and risk professionals is the growing impact of secondary perils such as convective storms, wildfire and flood. This systemic change in the severity of non-linear climate trends defies the assumptions that underpin traditional catastrophe models.

AI-enhanced catastrophe modelling, remote sensing technologies and Internet of Things (IoT) data streams are changing that, providing a level of real-time risk granularity previously unattainable. Machine learning models can now analyse high-resolution satellite imagery, weather pattern data and historical loss records to generate more informed risk projections, supporting the underwriting process.

Advances in modelling allow underwriters to assess risk and deploy capacity with greater confidence. In turn, the increasing modelling sophistication is attracting alternative capital providers as they seek uncorrelated yield and portfolio diversification.  

Crucially, these advances are not only transforming underwriting decisions – they are shaping resilience strategies. With better insight into localised exposures, organisations can model and quantify the impact of investments needed to build stronger resilience across all their locations, and then prioritise investments with the strongest impact. The mantra of Build Better Before is replacing the traditional post-loss recovery mindset of Build Back Better.

Litigation: identifying hotspots before they ignite

While natural catastrophe and geopolitics capture headlines, litigation remains a persistent source of volatility – particularly in the U.S., where social inflation continues to drive up claim costs. Nuclear verdicts and third-party litigation funding have become structural challenges for many sectors.

In contrast to natural catastrophe risk, resilience measures for liability aren’t as tangible as say reinforcing a flood wall – it requires a fundamentally different approach. Embedding risk awareness and transparency into company culture is essential. Documentation, audit trails and data governance have become frontline defences.

AI is helping insurers and corporates gain insights into these trends. By analysing court rulings, claims data, social media discourse and emerging regulatory trends, AI tools can help flag jurisdictions or industries where litigation activity is accelerating. This intelligence enables risk professionals to identify potential hotspots, and adjust risk strategies.

A new approach to underwriting: strategic, holistic and data-driven

Underwriters and risk professionals are used to managing uncertainty: they are specialists in interpreting risk and probability. However, the level of uncertainty today is so profound that, when combined with AI-driven innovations, it demands new approaches to understanding, managing and mitigating risks. This makes engagement and dialogue between insurers and customers more important than ever.

For corporates, the message is clear: those who leverage AI and advanced analytics to build a more strategic understanding of their risk profile and translate this into a smart resilience strategy will be best placed to achieve financial stability and long-term success.

For underwriters, this environment is triggering a more collaborative, holistic approach. With many underwriters now integrating AI-enhanced modelling and targeted risk engineering support directly into their customer offering, the underwriting conversation is evolving into an ongoing partnership grounded in shared intelligence and scenario planning.

Global volatility is likely to remain high. Against this backdrop, companies may benefit from reviewing their risk and insurance strategies with their insurers, using advanced analytics to support independent, well‑informed decisions on coverage and resilience. Risk professionals can work with their insurers to:

1. Reassess risk financing: use AI-powered models to quantify the trade-off between risk retention and risk transfer, demonstrating tangible financial outcomes that can secure executive buy-in.
2. Invest in climate adaptation measures: target investments where modelled data shows the highest potential return on resilience – from property retrofits to supply chain diversification.
3. Embed proactive liability modelling: Continuously analyse regulatory changes and litigation trends to detect gaps in coverage, ensuring risk mitigation and structures remain responsive to emerging exposures.

Conclusion: innovation as an enabler of resilience

AI is not a silver bullet – but it is an enabler. In a world defined by volatility, its ability to enhance foresight, connect data and uncover interdependencies to support decision-making is transforming how risks are managed and insured.

With insurers investing heavily in AI-enhanced modelling, data science and risk engineering, the industry is at a pivotal moment. The opportunity lies in collaboration – in using AI not merely as a tool for efficiency, but as a potential catalyst for resilience.

In this new era of underwriting, success will depend not only on how well we model risk, but on how well we work together to develop data-informed resilience strategies.

Originally published in Commercial Risk on April 14, 2026.