Overview
The global insurance and finance industries will be instrumental in addressing the increasingly complex array of challenges and risks the world faces as we enter the second quarter of the 21st century.
These range from adaptation to climate change, heightened geopolitical risk, countering new cyber threats and managing increasing longevity.
The common thread that runs across these disparate challenges is establishing new means to increase resilience. Another golden thread is the possibilities provided by new insurance technologies developed by insurers that may provide the solutions needed to meet ever increasing demands.
These themes were examined at a recent cross-disciplinary workshop in London convened by TheCityUK and the World Economic Forum.
Key highlights
- The global protection gap is widening as risk grows faster than affordability. Climate shocks, cyber exposure, and geopolitical stress are increasing losses while traditional insurance struggles to remain accessible, pushing coverage out of reach or off the market entirely in high-risk areas.
- Technology is reshaping insurance from loss response to risk prevention. AI, predictive modelling, drones, and satellite data are shifting insurers toward earlier intervention, faster claims settlement, and lower operating costs, directly influencing pricing and availability.
- Parametric insurance is emerging as a viable solution for hard-to-model risks. Trigger-based products reduce adjustment costs, accelerate payouts, and expand coverage where conventional insurance proves slow, expensive, or impractical.
- Regulatory fragmentation is slowing the scale-up of data-driven insurance. Diverging data, AI, ESG, and geoeconomic rules restrict cross-border data flows, limiting the effectiveness of predictive models that depend on global-scale analysis.
- Insurance plays a central role in unlocking climate finance and resilience. Capital does not flow without insurable risk. By reducing uncertainty and lowering the cost of capital, insurance enables investment in adaptation, infrastructure, and transition projects such as carbon capture and storage.
Insurance leaders call for closer policy alignment on innovation
Insurance and finance executives outlined how their sectors are developing practical solutions to advance this agenda, grounded in current market constraints rather than abstract ambition.
Participants stressed the need for closer, more durable partnerships between industry and policymakers. Policy frameworks, regulation, and cross-border coordination need to move in step to allow new technologies and business models to function at scale.
According to Beinsure, progress hinges less on invention and more on whether governance structures keep pace with how financial services now operate across borders.
Core global risks entering mid-21st century
| Risk category | Primary challenge | Why insurance matters |
| Climate change | Rising frequency and severity of natural hazards | Enables capital deployment, recovery funding, and adaptation |
| Geopolitical risk | Supply chain disruption, conflict spillovers | Stabilises trade, infrastructure, and investment flows |
| Cyber threats | Systemic digital and operational exposure | Transfers risk, supports prevention and rapid recovery |
| Longevity | Aging populations, pension and health strain | Supports financial sustainability and long-term planning |
Every new policy carries some degree of risk. Identifying where that risk lies is crucial to identifying potential threats and reducing fraudulent claims.
Integrating real-time data analytics through big datasets, artificial intelligence, and machine learning technologies empowers companies to detect high-risk policies before solidifying agreements.
Addressing the insurance gap through innovation
Insurers and policymakers continue to focus on the widening global protection gap, the spread between insured and uninsured losses that grows with every major disaster.
The problem is structural. Insurance needs to respond to modern risk patterns without pricing itself out of reach.
When affordability breaks down, premiums climb beyond access or coverage disappears altogether as insurers retreat from certain exposures.
Innovation levers insurers use to close the protection gap
| Technology | Function | Impact on cost and access |
| Drones | Rapid, safe damage assessment | Faster claims, lower inspection costs |
| Satellite data | Broad, historical risk visibility | Better pricing accuracy and risk modelling |
| AI & predictive models | Early detection of loss drivers | Shift from reactive to preventive insurance |
| Automation | Claims and underwriting efficiency | Reduced expense ratios, improved affordability |
Technology-driven change sits at the center of that tension. Efficiency gains matter because cost pressure flows straight through to pricing and availability.
After major natural disasters, insurers increasingly deploy drones to assess damage rapidly and safely, including in locations crews struggle to reach.
This shortens inspection timelines and reduces operational friction at precisely the moment policyholders need clarity.
The real shift comes when drone output is combined with satellite data. Satellites provide broad geographic reach and long historical records. Drones supply precise, real-time detail at asset level.
Used together, they allow insurers to build richer risk assessments without slowing the claims process.
According to World Economic Forum, this layered data approach improves loss estimation accuracy while compressing settlement timelines, which supports faster payouts and speeds recovery for households and businesses trying to rebuild under financial strain.
Property insurance grows costlier and less accessible
Meanwhile, as traditional property insurance grows costlier and less accessible in high-risk areas vulnerable to natural disasters, the development of parametric insurance products offers a potentially promising alternative.
Unlike conventional policies, parametric insurance quickly pays out based on set triggers, such as storm category or wind speed, rather than lengthy loss assessments.
This reduces underwriting and adjustment costs, making coverage more affordable. At the same time, specialist insurance markets that exist specifically to cover tougher risks such as severe weather-exposed properties are continuing to grow.
Parametric solutions are among the most transformative innovations
Parametric solutions are among the most transformative innovations to emerge from the Lloyd’s Lab, an Insurtech accelerator. They deliver the potential for quick, transparent and helpful solutions for hard-to-model risks that extend far beyond natural catastrophes.
Lab firms like Parametrix and Otonomi are proving how parametric models can address IT outages and fragile supply chains, leveraging automation and algorithmic underwriting to accelerate recovery and boost efficiency
Dawn Miller, CCO of Lloyd’s
However, greater efficiency alone is unlikely to be sufficient to meet the increasingly complex challenges societies face. Therefore, many insurers are redefining their role.
Instead of simply responding to disasters and losses, the industry is moving towards prediction and prevention to help mitigate risks before they materialise.
Traditional vs parametric insurance models
| Feature | Traditional insurance | Parametric insurance |
| Payout trigger | Verified loss assessment | Predefined event threshold |
| Claims process | Time-intensive, manual | Automated, near-instant |
| Cost structure | Higher adjustment expenses | Lower underwriting and admin costs |
| Best suited for | Well-modelled risks | Hard-to-model or high-frequency risks |
Parametric use cases beyond natural catastrophes
| Risk type | Example application | Benefit |
| IT outages | Cloud or system downtime | Immediate liquidity for recovery |
| Supply chains | Logistics disruption | Faster operational restart |
| Weather volatility | Renewable energy output | Revenue stabilisation |
| Cyber incidents | Business interruption | Predictable, rapid payout |
AI adoption across the insurance services
AI and predictive modelling open a path away from reactive loss response toward earlier intervention across failure detection, fraud, cyber intrusion, and automated mitigation.
Reaching that point depends on large-scale data collection and cross-border analysis, which is where friction sets in.
Expanding regulatory fragmentation and stricter data localisation rules now restrict the movement of precisely the data sets proactive models rely on, slowing deployment and limiting effectiveness.
The adoption of AI across the financial services industry and wider economy is also creating new risks to manage. For example, there are increasingly difficult questions surrounding liability for errors made by AI systems.
AI adoption: opportunity vs risk in insurance and finance
| Dimension | Opportunity | Risk introduced |
| Operations | Automation and speed | Model error liability |
| Risk management | Predictive prevention | Data bias and opacity |
| Cyber security | Advanced threat detection | AI-enabled attack escalation |
| Decision-making | Scaled analytics | Governance and accountability gaps |
AI also carries its own vulnerabilities: it is likely to increase the sophistication and volume of cyber-attacks, but it also brings benefits, providing new tools to defend against such risks. Cyber, too, is emerging as a systemic risk that carries its own challenges.
Insurance is shifting from hindsight to real time foresight. By strengthening data ingestion across legacy platforms, fusing AI with event based systemic modelling, and investing in our teams’ capabilities and nurturing underwriting expertise, we can deliver holistic protection on climate and cyber and support global resiliency
Sara Farrup, Head of Global Markets, AXIS Capital
More broadly, insurance works alongside the wider finance sector as a practical enabler of growth, transition, and resilience by absorbing risk that would otherwise stall investment.
De-risking capital remains one of insurance’s least visible but most effective functions, especially as markets move into infrastructure-heavy and technology-intensive transition phases.
Climate finance has often treated insurance as secondary
That view misses a constraint investors understand well. Capital does not flow at scale unless projects carry insurable risk profiles. Climate adaptation initiatives face the same test. Without coverage, financing terms deteriorate or deals fail outright.
Carbon capture and storage offers a clear example. These projects sit across new value chains with layered operational, environmental, and long-tail liability exposures.
Insurance structures developed around them reduce financing friction by lowering the cost of capital and addressing risks lenders and equity investors struggle to price on their own.
According to Beinsure, this ability to translate complex risk into bankable form explains why insurance remains a central, deployable resource in the transition economy rather than a peripheral add-on.
Why insurance is critical to climate finance
| Project type | Key risk challenge | Insurance contribution |
| Climate adaptation | Long-term loss uncertainty | Improves project bankability |
| Infrastructure | Construction and operational risk | Lowers financing costs |
| Carbon capture & storage | Long-tail liability exposure | Enables lender and investor participation |
| Energy transition | New technology risk | Absorbs uncertainty investors avoid |
Regulatory friction limiting insurance innovation
| Regulatory bucket | Constraint created | Impact on insurers |
| Data governance | Localisation requirements | Limits global model accuracy |
| AI regulation | Divergent compliance rules | Slows deployment at scale |
| ESG frameworks | Inconsistent standards | Increases reporting complexity |
| Geoeconomic controls | Cross-border restrictions | Reduces competition and capacity |
AI regulations for the future
While the industry stands ready to expand its expertise and impact, it must contend with a range of regulatory barriers.
Some are long-standing, arising from regulation not being attuned to new types of risk. But other, newer, barriers threaten much needed competition in the global provision of solutions.
This new generation of regulatory barriers can be grouped into thematic “buckets” illustrating areas where cross-border regulatory divergence is growing:
- Data governance and digital identity
- AI and technology requirements
- Sustainability and ESG requirements
- Emerging geoeconomic measures
To address these challenges, governments and regulators must work alongside the insurance and finance sectors to harmonise approaches across jurisdictions and reduce unnecessary regulatory complexity.
Unlocking the full potential of the insurance industry to address complex, long-term challenges will require commensurate policy consistency and predictability, over visionary timescales that many governments are not typically used to.
Short-termism will not do, because lack of long-range policy predictability and consistency will not provide the investor confidence that is required.
FAQ
The protection gap is the difference between insured and uninsured losses. It widens as climate events, cyber risks, and geopolitical shocks grow faster than affordable insurance capacity, pushing premiums higher or forcing insurers to withdraw from certain risks.
Technology improves efficiency and lowers costs. Tools such as drones, satellite imagery, AI-driven modelling, and automation speed up claims, improve risk assessment, and reduce operational friction, which supports broader coverage availability.
Drones provide real-time, asset-level damage data, while satellites offer wide geographic coverage and historical context. Combined, they improve loss estimation accuracy and shorten claims settlement timelines without slowing payouts.
Parametric insurance pays out when predefined triggers are met, such as wind speed or storm category, rather than after full loss adjustment. This reduces claims handling costs and enables faster, more predictable payouts.
AI and predictive modelling allow insurers to anticipate failures, fraud, cyber incidents, and operational disruptions. This shifts the focus toward prevention and early intervention rather than post-loss response.
Data localisation rules, fragmented regulations, and inconsistent AI governance restrict cross-border data flows. These barriers reduce the effectiveness of predictive models that rely on global-scale data analysis.
Investment does not scale without insurable risk. Insurance reduces the cost of capital for complex projects such as carbon capture and storage by absorbing operational and long-tail liabilities, making these initiatives financially viable.
……………………
AUTHORS: John Cooke – Co-Chair, Liberalisation of Trade in Services (LOTIS) Committee, TheCityUK, Mingcong Li – Lead, Trade in Services, World Economic Forum
Edited by Tetiana Mykhailova – Commercial Director of Finance Media, CFO Beinsure Media
