（来源：新华日报） 今年以来，宿迁市湖滨新区积极探索构建"四维一体""网安集市"新模式，以"服务、知识、人才、智 慧"四大板块为抓手，通过精准化服务、常态化培育与智能化赋能，筑牢基层网络安全屏障。 "人才集市"育用结合夯实基础。组建"网安先锋队"，建立导师库开展传帮带，举办技能竞赛和攻防演练 6场，培育了一支"带不走"的基层网安力量，为"网安集市"提供人才支撑。 "智慧集市"智能预警强化管控。部署网络安全态势感知平台，运用大数据和人工智能技术实现风险智能 研判、威胁实时预警，今年以来，推送预警44期、指导处置32次，全区网络安全防御能力全面提升。 姜宁 陈昱柯 "服务集市"精准滴灌企业需求。针对企业特点，建立分级服务机制，对重点单位开展常态督导，为中小 微企业定制"普惠安全服务包"。创新推出"网安直通车"平台，实现"企业点单、专家接单"，精准匹配需 求，今年完成220家企业体检、修复漏洞300余个。 "知识集市"寓教于乐提升意识。打造"线上+线下"宣传矩阵，线上推出《明明的网安世界》等原创视 频，点击量超20万次；线下开展"网安大集"活动35场，将非遗、游戏与知识结合，覆盖群众4万余人。 ...

Core Insights - The insurance industry faces significant challenges due to frequent climate risks, highlighted by the impact of Typhoon "Hagupit" on southern China, necessitating improved risk management capabilities [1][3] - The establishment of a multi-layered risk-sharing mechanism involving direct insurance companies, catastrophe co-insurance, reinsurance companies, catastrophe bonds, special funds, and government support is crucial for building a "climate-adaptive society" [1][3] - The development of Large Risk Models (LRM) leveraging artificial intelligence is essential for enhancing risk visibility and management in the insurance sector [2][8] Group 1: Climate Risks and Insurance - Typhoon "Hagupit" has caused significant economic losses, with the insurance industry expected to face increasing claims as natural disasters become more frequent [3] - Guangdong province has pioneered catastrophe insurance, accumulating premiums of 860 million yuan and payouts of 1.93 billion yuan during the pilot phase from 2022 to 2024 [1] - The insurance sector is transitioning from post-disaster compensation to a comprehensive risk management approach that includes prevention and mitigation strategies [3][7] Group 2: Technological Advancements in Risk Management - Companies like Ping An have developed advanced systems, such as the "Eagle Eye" system, which utilizes AI and big data for real-time flood forecasting and risk management [4][6] - The insurance industry is increasingly adopting digital tools, including satellite remote sensing and IoT, to enhance risk identification and monitoring capabilities [3][6] - The emergence of AI-driven models is expected to transform risk assessment and management, allowing for real-time monitoring and dynamic evaluation of risks [9][11] Group 3: Future Directions and Opportunities - The integration of AI into risk modeling is seen as a key area for future development, enabling more accurate and responsive risk assessments [8][9] - The potential for LRM to provide real-time pricing mechanisms for catastrophe bonds and enhance climate risk diversification is being explored [9] - The government's push for AI applications in risk prevention indicates a strategic direction for the insurance industry to leverage technology for improved risk management [11]