DELRAY BEACH, Fla., April 25, 2025 /PRNewswire/ -- The global report for Risk Analytics Market is slated to expand from USD 32.25 billion in 2025 to USD 51.34 billion by 2030 at an impressive CAGR of 9.7% over the forecast period, according to new research report by MarketsandMarkets™. The expansion of the risk analytics market is influenced by various factors, including the growing frequency and complexity of global risks, the increasing demand for efficient decision-making tools in companies, and technological advancements like artificial intelligence (AI) and machine learning (ML). Entities across various sectors, such as finance, healthcare, and manufacturing, are employing risk analytics to forecast potential disruptions and ensure regulatory adherence. The growing reliance on big data, combined with the rise in IoT devices, has expanded the volume of data available for analysis, enabling more precise risk evaluations. Moreover, the increase in cyber threats, coupled with the demand for robust cybersecurity strategies, is fueling the necessity for risk management solutions. Additionally, the evolving terrain of climate threats and natural calamities is prompting organizations to integrate climate risk models into their evaluations

ZestyAI, the leader in AI-driven risk analytics for insurance, today revealed that more than 12.6 million U.S. properties are at high risk of hail-related roof damage, representing $189.5 billion in potential replacement costs.Powered by ZestyAI’s Z-HAIL™ model, the analysis underscores the growing financial threat of severe convective storms (SCS), including hail, tornadoes, and wind events. In 2024 alone, damages from SCS were estimated at $56 billion—surpassing losses from hurricanes.Yet many insurers still rely on traditional models designed to estimate portfolio-level exposure, not property-level risk. As hail events increase in severity and frequency, these models often miss the structural and environmental conditions that drive real losses.“Catastrophe models have helped insurers understand where storms may strike and how losses might add up at a portfolio level,” said Kumar Dhuvur, Co-Founder and Chief Product Officer at ZestyAI. “But they weren’t built to assess risk at the individual property level, and they often miss the specific conditions that drive hail damage. By analyzing the interaction between structure-specific features and local storm patterns, we can distinguish risk between neighboring properties—enabling smarter underwriting, more precise pricing, and better protection for policyholders.”Z-HAIL evaluates hail risk using a proprietary blend of climate, aerial, and property-specific data