LOSS-SAMPLER: A tool for identifying unseen volatility in present and future Climate and Environmental Risk (CER) portfolios

气候和天气风险对全球年度GDP的综合威胁超过1300亿美元（剑桥风险研究中心，2020年），使其成为对GDP的最大威胁，无论是人为的还是自然的。面对如此严峻的气候和环境风险（CER），巨灾模型已经成为（再）保险公司不可或缺的风险管理工具，并开始迎来一个更好地理解风险的新时代。巨灾模型起源于20世纪80年代末，在过去的30年里不断发展，以帮助解决全球社会长期可持续性所面临的一些最复杂的挑战。在关于气候变化和金融稳定的演讲中，当时的英格兰银行行长直接赞扬了这些模型，指出“英国保险公司经受住了2011年的事件，这是有记录以来保险损失最严重的年份之一。您的模型得到了验证，索赔得到了支付，偿付能力得到了维持”（Mark Carney，2015）。虽然灾难建模的出现无疑为社会带来了许多好处，但我们远未挖掘出其对私营行业和社会的最大价值。我们仍然能够被灾难性事件所震惊，这些事件不仅是容易想象的，而且在当代灾难模型中得到了很好的体现，这说明一项服务甚至还没有接近实现其全部潜力。与许多历史悠久的学科相比，灾难建模领域仍然非常年轻，这些学科的数据和信息为其过程提供了支持，这也许可以解释为什么许多潜在价值目前仍未得到开发。不幸的是，在过去的三十年里，灾难建模行业主要关注于部署专注于狭义风险定义的分析-也就是说，这是一个在风险定价和资本管理情况下易于操作的定义。在这里，我们创建了一个工具，利用当代灾难模型输出来开始揭示更多的“未知-未知”-在创建灾难模型分析时存在的信息，但由于与其应用相关的操作复杂性，这些信息在历史上一直被忽视。该工具将针对过去几年需求迅速增长的两个关键业务应用程序，即：2.量化和传达气候变化的影响。这两种应用最终将促进私营企业和更广泛的社会建立对CER的适应能力。

The combined threat of climate and weather perils to annual global GDP is over $130billion (Cambridge Centre for Risk Studies, 2020), making them the largest of _any_ conceivable threat to GDP, whether man-made or natural in origin. In the face of such severe Climate and Environmental Risk (CER), catastrophe modelling has become indispensable to (re)insurers as a risk-management tool, and has begun to usher in a new era of improved understanding of risk.Originating in the late 1980s, catastrophe modelling has evolved over the past ~30 years to help tackle some of the most complex challenges facing the long-term sustainability of global society. In his speech on Climate Change and Financial Stability, the then Governor of the Bank of England directly praised the models, stating that "UK insurers withstood the events of 2011, one of the worst years on record for insurance losses. Your models were validated, claims were paid, and solvency was maintained" (Mark Carney, 2015).While there have undoubtedly been many benefits to society from the advent of catastrophe modelling, we are far from extracting its maximum value to private industry and society. Our capacity to still be shocked by catastrophic events that are not just easily conceivable, but well-represented in contemporary catastrophe models, speaks of a service that is not even close to realising its full potential.The field of catastrophe modelling is still extremely young compared to the many longstanding academic disciplines whose data and information feed its processes, which may explain why much of the potential value currently remains untapped. Somewhat unfortunately, over the past three decades the catastrophe modelling industry has primarily focused on deploying analytics that focus on a narrow definition of risk - that is, a definition that is easily operationalized in risk pricing and capital management situations.Here we create a tool that utilises contemporary catastrophe model output to begin to uncover many more "unknown-knowns" - information that exists in the creation of catastrophe model analytics, but has historically been overlooked because of operational complexities associated with its application. The tool will target two key business applications for which demand has rapidly increased in the past few years, namely:1\. Informing present-day catastrophe-risk portfolio re-structuring decisions.2.Quantifying and communicating the impact of climate change.Both of these applications will ultimately facilitate the building of resilience to CER in private industry and broader society.