Assessing the value of seasonal climate forecasts for risk management

气候变化对极端天气事件的运营构成直接风险。虽然风险建模行业了解共享的社会经济路径在未来气候（直到2100年）中可能如何影响被保险资产，但目前还没有尝试管理未来几个月的金融波动。例如，在2019- 2020年秋季英国洪水事件期间，保险公司面临着昂贵的索赔支出，而农民在2018年春季遭受了严寒，随后是最热、最干燥的夏季之一。极端天气/气候风险的季节性变化取决于许多不同的气候指数，企业面临各种天气风险，这些风险在未来几个月内可能更（或更少）发生。由于保险定价目前不灵活，当特定的天气灾害在业务期间更频繁和更广泛时，结算费用有时会高得多。因此，季节性气候预报的经济效益是巨大的，但它们在很大程度上是无法量化的。这个项目旨在制定一个可靠和严格的方法，以验证一个更本地化和详细的季节预测产品，我们可以与我们的金融客户分享。我们的愿景是，我们可以为我们的潜在客户的审计和模型评估过程提供这种分析。例如，在农业空间层面向作物保险公司提供干旱/洪水风险信息。我们期望通过执行更完整的验证评估来满足更广泛行业的需求，我们可以更快地接触到更多的客户。因此，克服这一评估挑战将使业务能够在一个独特的、具有潜在破坏性的新市场中增长。我们的目标是将NPL的验证应用于我们在其他地区的预测产品，必要时使用他们的可转让方法。由于气候风险影响大多数业务，解决这一挑战将为零售需求管理、参数作物保险、可再生能源管理、资产再保险和银行业务带来更广阔的市场机会。

Climate change poses an immediate risk to operations from extreme weather events. While the risk modelling industry understands how Shared Socioeconomic Pathways are likely to impact insured assets in a future climate (up to the year 2100), there is currently no attempt to manage financial volatility over the coming months. For example insurers faced expensive payouts from claims during the UK flooding events during autumn 2019-20, while farmers suffered from the severe cold during spring 2018 followed by one of the hottest and driest summers. Seasonal variability in extreme weather/ climate risk depends on many different climate indices, with business exposed to a variety of weather perils that can either be more (or less) likely within the upcoming months. Since insurance pricing is not currently flexible, settlements can sometime be much more costly when a specified weather hazard is more frequent and widespread within an operational period.The economic benefit of seasonal climate forecasts is therefore substantial, yet they are largely unquantified. This project aims to formulate a credible and rigorous methodology for the validation of a more localised and detailed seasonal forecast product that we can share with our financial clients. The vision is that we can then supply this analysis with our prospective clients for their auditing and model evaluation process. For instance providing drought/ flood risk information to crop insurers at a farming spatial level. We expect that by performing a more complete validation assessment to meet the requirements of the wider industry, we can reach more customers much faster. Overcoming this assessment challenge would therefore enable business growth within a uniquely new and potentially disruptive market.We aim to apply NPL's validation to our forecast products in other geographies as necessary using their transferable methodology. Since climate risk impacts most operations, solving this challenge would facilitate wider market opportunities in retail demand management, parametric crop insurance, renewable energy management, asset reinsurance and banking.