This dataset provides detailed catastrophe risk zone information across multiple hazard types, including hurricane, earthquake, wildfire, flood, tornado, and hail. Each record contains geographic identifiers, hazard scores, PML estimates, and portfolio concentration limits, enabling robust risk assessment, exposure management, and spatial analysis for insurance and financial applications.

The spreadsheets include raw data used in conducting two case studies.

Central America & Caribbean Catastrophe Risk Insurance Project (World Bank project P149670, Latin America and Caribbean, Latin America and Caribbean) appears in one World Bank IEG snapshot, 2023.

The MATLAB codes are designed to simulate the proposed framework for quantitatively assessing the effect of catastrophe insurance on community recovery.

Second Central America and Caribbean Catastrophe Risk Insurance Project (World Bank project P175616, Latin America and Caribbean, Latin America and Caribbean) appears in one World Bank IEG snapshot, 2025.

This dataset provides detailed Probable Maximum Loss (PML) estimates for various catastrophe exposures, including loss amounts at multiple return periods and confidence levels. It is designed to support reinsurance purchasing, risk management, and regulatory reporting by offering granular, traceable loss metrics across exposures and event types. The dataset is ideal for actuaries, risk managers, and insurance analysts seeking to quantify and manage catastrophic risk.

Insurance Risk Analytics via Satellite Market Outlook

According to our latest research, the global Insurance Risk Analytics via Satellite market size reached USD 1.71 billion in 2025, with robust year-on-year growth driven by technological advancements and escalating demand for precise, real-time risk assessment. The market is projected to expand at a CAGR of 16.2% from 2026 to 2034, reaching a forecasted value of USD 5.01 billion by 2034. This expansion is fueled by the growing adoption of satellite data for continuous asset monitoring, climate risk modeling, and disaster response, which are fundamentally transforming how the insurance sector approaches underwriting, portfolio management, and claims resolution. For a broader view of catastrophe-related satellite applications, see our companion study on insurance catastrophe risk via satellite.

The primary growth factor fueling this market in 2025 and beyond is the increasing frequency and severity of natural disasters globally. Insurers face intensifying pressure to accurately model and price risk, particularly in property and crop insurance lines. Satellite-based analytics provide high-resolution geospatial data that enable underwriters to assess risk exposure with unprecedented accuracy, supporting more defensible premium calculations and better-informed portfolio decisions. The growing sophistication of satellite imagery, combined with AI and machine learning algorithms, is enabling real-time event detection and post-event damage assessment at scale, further embedding satellite-driven analytics as an essential component of modern insurance operations.

Regulatory requirements for risk transparency and climate risk disclosure represent another powerful growth catalyst. Governments and regulatory bodies worldwide are mandating that insurers adopt advanced risk assessment methodologies to ensure solvency and protect policyholders. Satellite data analytics offer a scalable, objective, and auditable solution for compliance, providing verifiable information on insured assets, hazard zones, and loss estimates. This is particularly critical for reinsurers and government agencies engaged in disaster recovery and climate adaptation. The ability to embed satellite analytics into enterprise risk management frameworks streamlines regulatory reporting and supports strategic capital allocation decisions.

Technological progress in satellite hardware, data processing, and cloud infrastructure continues to lower barriers to entry across the market. The proliferation of small satellite constellations and the falling cost of launch services have democratized access to high-frequency earth observation data. Cloud-based analytics environments further enhance accessibility and scalability, allowing insurers of all sizes to leverage these capabilities without material upfront infrastructure investment. This democratization is fostering innovation across the insurance value chain, from underwriting and claims management to fraud detection and customer engagement. Those interested in the specific role of radar satellites in this transformation can explore our dedicated report on SAR satellite analytics for insurance.

Regionally, North America dominates the Insurance Risk Analytics via Satellite market, accounting for approximately 35.5% of the 2025 global market value. Europe follows with a 26.5% share, driven by stringent EU climate risk and sustainability mandates. Asia Pacific, representing roughly 22.5% of the 2025 market, is the fastest-growing region at a projected CAGR of 18.4% through 2034, propelled by rapid digitalization, rising insurance penetration, and high natural disaster exposure. Latin America and the Middle East and Africa together account for about 15.5% of global market value in 2025 and present compelling emerging market opportunities, particularly in agricultural risk and disaster financing programs.

Insurance Cat Risk via Satellite Market Size and Growth Outlook

Across all regions, the Insurance Catastrophe (Cat) Risk via Satellite market size reached USD 1.94 billion in 2024, reflecting a robust momentum driven by the insurance sector's urgent need for real-time, high-precision risk assessment tools. The market is poised to expand at a remarkable CAGR of 15.2% from 2025 to 2033, with the forecasted market size anticipated to achieve USD 6.41 billion by 2033. This vigorous growth is propelled by the increasing frequency and severity of natural disasters, coupled with advancements in satellite technology that enable insurers to better quantify, monitor, and mitigate catastrophic risks on a global scale.

One of the primary growth factors for the Insurance Catastrophe (Cat) Risk via Satellite market is the escalating impact of climate change, which has led to a significant rise in the frequency and intensity of catastrophic events such as hurricanes, wildfires, floods, and earthquakes. Insurers are under mounting pressure to enhance their risk modeling capabilities to remain competitive and solvent in the face of such unpredictable losses. Satellite data provides a unique, real-time vantage point, enabling insurance companies to assess risks with unprecedented granularity and accuracy. This capability not only improves underwriting processes but also supports proactive loss prevention and rapid claims response, making satellite-based solutions indispensable for the modern insurance industry. The growing integration of artificial intelligence and machine learning with satellite imagery further amplifies the value proposition, allowing for predictive analytics that can anticipate and quantify emerging risks.

Another key driver fueling market expansion is the increasing adoption of satellite-enabled solutions by government agencies and reinsurers, who play a critical role in managing systemic risks at national and global levels. Governments are leveraging satellite data to enhance disaster preparedness, coordinate emergency responses, and develop more resilient infrastructure. Reinsurers, meanwhile, utilize satellite-derived insights to refine their catastrophe models, optimize reinsurance treaties, and reduce exposure to correlated risks. The synergy between public and private stakeholders in harnessing satellite technology is fostering a collaborative ecosystem that accelerates innovation and broadens the application spectrum of cat risk solutions. Additionally, regulatory bodies are increasingly mandating the use of advanced risk assessment tools, further catalyzing the adoption of satellite-based services across the insurance value chain.

The rapid evolution of satellite technology itself is a significant market catalyst. The advent of high-resolution Earth observation satellites, improved communication payloads, and the proliferation of small satellites (CubeSats) have dramatically lowered the cost and increased the accessibility of satellite data. This democratization of satellite imagery has enabled even smaller insurers and brokers to integrate advanced risk analytics into their operations. Moreover, the convergence of satellite data with geospatial analytics, cloud computing, and big data platforms has unlocked new possibilities for real-time monitoring and dynamic risk scoring. As a result, the Insurance Catastrophe (Cat) Risk via Satellite market is witnessing an influx of innovative solution providers, driving competition and accelerating the pace of technological advancement.

From a regional perspective, North America currently leads the Insurance Catastrophe (Cat) Risk via Satellite market, accounting for the largest share in 2024, followed closely by Europe and Asia Pacific. The United States, in particular, benefits from a mature insurance sector, robust regulatory frameworks, and significant investments in satellite infrastructure. Europe is experiencing strong growth due to stringent regulatory requirements around solvency and risk management, as well as an increasing focus on climate resilience. Asia Pacific, while still emerging, is rapidly catching up, fueled by rising insurance penetration, frequent natural disasters, and government initiatives to modernize disaster risk management. Latin America and the Middle East & Africa, though smaller in market size, are expected to witness accelerated adoption as satellite technology becomes more affordable and accessible.

What this repo is for Detect catastrophe model failure. Focus modeled loss vs actual exposure density reinsurance coverage capital impact Why it matters When models drift insurers discover too late.

SEE Catastrophe Risk Insurance Facility TA SECO (World Bank project P156455, Western Balkans, Europe and Central Asia) appears in one World Bank IEG snapshot, 2021.

This dataset provides detailed information on property catastrophe excess of loss reinsurance treaties, including financial terms, coverage limits, reinstatement provisions, territorial scope, and involved parties. It enables comprehensive analysis of catastrophe risk transfer, treaty structuring, and market benchmarking for insurers and reinsurers.

Insurance Catastrophe Modeling AI Market Size and Growth Outlook

Across all regions, the Insurance Catastrophe Modeling AI market size reached USD 1.98 billion in 2024, demonstrating robust demand across the insurance and reinsurance sectors. The market is expected to register a CAGR of 16.7% from 2025 to 2033, leading to a forecasted market size of USD 9.47 billion by 2033. This impressive growth trajectory is primarily driven by the increasing frequency and severity of natural disasters, the rising adoption of artificial intelligence in risk modeling, and the insurance industry's urgent need for advanced analytical tools to manage complex catastrophe risks more effectively.

One of the most significant growth factors for the Insurance Catastrophe Modeling AI market is the escalating impact of climate change, which has resulted in a notable surge in catastrophic events such as hurricanes, floods, wildfires, and earthquakes. These events have not only become more frequent but also more severe, leading to larger insured losses and greater unpredictability for insurers and reinsurers. As a result, there is a heightened demand for sophisticated catastrophe modeling solutions powered by AI, which can process vast amounts of data, simulate multiple disaster scenarios, and provide actionable insights for risk mitigation, pricing, and capital allocation. The integration of AI into catastrophe modeling enables the industry to move beyond traditional actuarial methods and embrace predictive analytics, real-time data feeds, and machine learning algorithms, all of which enhance the accuracy and granularity of risk assessment.

Another pivotal driver is the digital transformation sweeping through the insurance sector, compelling organizations to modernize their legacy systems and adopt cloud-based, AI-driven platforms for catastrophe modeling. Insurers and reinsurers are increasingly recognizing the limitations of conventional models, which often fail to account for emerging risks and complex interdependencies in today's dynamic risk landscape. By leveraging AI, companies can automate data ingestion from a multitude of sources, such as satellite imagery, IoT sensors, and social media, and rapidly generate probabilistic forecasts and loss estimates. This not only improves underwriting and claims management but also supports regulatory compliance and capital adequacy assessments. Furthermore, the growing availability of third-party catastrophe modeling services and the proliferation of insurtech startups are fueling market competition and innovation, making advanced modeling accessible to a broader range of stakeholders.

The regulatory environment is also playing a crucial role in shaping the Insurance Catastrophe Modeling AI market. Regulatory bodies across major markets are increasingly mandating the use of advanced risk assessment tools and transparent modeling practices to ensure the financial stability of insurers and protect policyholders. This has accelerated investments in AI-powered catastrophe modeling solutions, particularly among large insurance and reinsurance companies seeking to strengthen their risk management frameworks and enhance their ability to respond to catastrophic events. In addition, the growing emphasis on environmental, social, and governance (ESG) considerations is prompting insurers to adopt more robust catastrophe models that can account for climate-related risks and support sustainable business practices.

The advent of Parametric Insurance Analytics AI is revolutionizing the way insurers approach catastrophe modeling. Unlike traditional indemnity-based insurance, parametric insurance provides payouts based on predefined parameters or triggers, such as the magnitude of an earthquake or the wind speed of a hurricane. This innovative approach leverages AI to analyze vast datasets and accurately determine these parameters, ensuring swift and transparent claim settlements. By integrating Parametric Insurance Analytics AI, insurers can offer more flexible and tailored products, enhancing their ability to manage risk and meet the evolving needs of policyholders. This technology not only streamlines the claims process but also reduces administrative costs and minimizes disputes, making it an attractive option for both insurers and insureds in the face of increasing climate-related risks.

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One Concern publishes no plans, tiers, or prices for the Domino AI API or for any of its products. There is no pricing page on oneconcern.com, no sign-up flow, and no self-service path to a credential — access begins with a sales conversation and API tokens are issued by the customer success team. This is an enterprise contact-us commercial model.

Analysis-ready U.S. county-year climate and flood-insurance risk data with 83,804 rows. The release combines redacted National Flood Insurance Program claim aggregates, NOAA Storm Events, and FEMA disaster declarations from 2000 onward. It includes transparent frequency, severity, damage, human-impact, declaration, and composite percentile measures. The composite score is descriptive and must not be treated as an insurance rate, underwriting decision, catastrophe-model output, or causal estimate. NFIP coverage totals represent coverage attached to claims, not all policies in force. Monetary values are nominal dollars.

The Natural Catastrophes Insurance Market was valued at USD 93.6 Billion in 2025 and is projected to grow to USD 120 Billion by 2035, at a CAGR of 2.6%. Natural Catastrophes Insurance Market Overview: Natural Catastrophes Insurance Market Overview: The Natural Catastrophes Insurance Market Size was valued at 91.2 USD Billion in 2024. The Natural Catastrophes Insurance Market is expected to grow from 93.6 USD Billion in 2025 to 120 USD Billion by 2035. The Natural Catastrophes Insurance Market CAGR (growth rate) is expected to be around 2.6% during the forecast period (2025 - 2035). Key Natural Catastrophes Insurance Market Trends Highlighted The Global Natural Catastrophes Insurance Market is witnessing significant trends shaped by the increasing frequency and severity of climate-related events, driving up demand for insurance products tailored to cover natural disasters. Key market drivers include the growing concerns about climate change, prompting both individuals and businesses to seek adequate coverage for potential natural catastrophes. Furthermore, advancements in technology and data analytics are enhancing risk assessment and underwriting processes, making insurance products more accessible and tailored to specific needs. Opportunities to be explored include the expansion of coverage options to include emerging risks, such as cyber-attacks on critical infrastructure, alongside traditional natural disasters.Insurers are also focusing on developing innovative policies that incentivize risk mitigation measures, such as improved building standards or investments in infrastructure resilience. As global initiatives strengthen around climate adaptation, there is a potential for collaboration between insurers and governments to foster community preparedness programs. Recent trends indicate a shift towards parametric insurance solutions, which provide rapid payouts based on predefined triggers, such as wind speed or rainfall levels, rather than traditional claims processes. This shift enhances the efficiency of claims and supports quicker recovery efforts.Globally, regulatory bodies are increasingly encouraging transparency in risk communication and investment in sustainable practices in the insurance sector. These dynamics are expected to evolve steadily, aligning with projected market expansion and increasing emphasis on sustainability in the years leading up to 2035. Source: Primary Research, Secondary Research, WGR Database and Analyst Review Natural Catastrophes Insurance Market Segment Insights: Natural Catastrophes Insurance Market Regional Insights The Global Natural Catastrophes Insurance Market has showcased diverse regional dynamics, with North America holding a majority share in overall valuation, valued at 35 USD Billion in 2024, and expected to rise to 45 USD Billion by 2035. This region's robust insurance infrastructure and regulatory support play a significant role in its dominance. Europe is experiencing steady expansion, driven by increased awareness of natural disaster risks and the need for enhanced coverage solutions. The APAC region is also seeing moderate increase, influenced by rising urbanization and climate change impacts prompting governments and individuals to seek more insurance options.South America displays a gradual decline in some areas, yet opportunities for growth persist due to the increasing frequency of natural disasters demanding better risk management. Middle East and Africa (MEA) face challenges, however, the region is expected to gradually develop its insurance frameworks, leading to potential growth in the long run. The Global Natural Catastrophes Insurance Market statistics reveal that trends related to climate change adaptation, urban development, and regulatory factors will continue influencing the insurance landscape across these regions, creating both challenges and opportunities for stakeholders. Source: Primary Research, Secondary Research, WGR Database and Analyst Review • North America : In North America, the adoption of AIoT technologies in natural catastrophes insurance is growing, aiding in risk assessment and real-time mon

This dataset supports the empirical analysis presented in the article “Catastrophic Risk and Systemic Risk in the Insurance Sector: DeltaCoVaR forecasting.” Its purpose is to facilitate the reproducibility and further analysis of the relationship between climate-related catastrophe occurrence, market conditions, and the systemic risk contributions of major global insurance companies. The dataset contains weekly estimates of DeltaCoVaR, used to measure individual insurers’ contributions to systemic risk, together with variables identifying catastrophe occurrence and market regimes. It also includes out-of-sample DeltaCoVaR forecasts generated using insurer-specific Generalized Additive Models for Location, Scale and Shape (GAMLSS) for one-, two-, and three-week forecasting horizons. The data cover ten major global insurance companies and span the period from 2004 to 2024. They enable the analysis of systemic risk under different combinations of catastrophe and market conditions, including normal and crisis periods, and provide the data underlying the main empirical and forecasting results reported in the article.

Kazakhstan: Southeast Europe and Central Asia Catastrophe Risk Insurance Facility (World Bank project P152230, Republic of Kazakhstan, Europe and Central Asia) appears in one World Bank IEG snapshot, 2021.

This dataset provides comprehensive details on aggregate excess of loss (XOL) reinsurance treaties, including coverage terms, financial parameters, claims experience, and involved parties. It enables risk managers, actuaries, and analysts to assess treaty performance, loss aggregation, and frequency of catastrophic events across policy years. Ideal for portfolio management, pricing analysis, and regulatory reporting in the insurance and reinsurance sector.

Global Climate Risk Insurance Market is segmented by Application (Insurance_Risk Management_Real Estate_Government_Renewable Energy), Type (Catastrophe Bonds_Weather Derivatives_Climate Resilience Policies_Property Coverage_Flood & Wildfire Insurance), and Geography (North America, LATAM, West Europe, Central & Eastern Europe, Northern Europe, Southern Europe, East Asia, Southeast Asia, South Asia, Central Asia, Oceania, MEA)

Data used for writing the paper entitled "The role of Insurance in disaster risk reduction in South America" to be submitted in the Special issue Economic Hydrology of Hydrology Journal.