Surface water flood forecast-based loss estimation for resilient finance

基于地表水洪水预测的弹性金融损失估计

• 批准号: 10056206
• 金额: $ 43.85万
• 依托单位: PREVISICO LIMITED
• 依托单位国家: 英国
• 项目类别: Small Business Research Initiative
• 财政年份: 2023
• 资助国家: 英国
• 起止时间: 2023 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=10056206
• 关键词: Surface; water; flood; forecast; based

Following initial supervision of climate related financial risks, The Bank of England requires UK banks and insurers to stress test their assets and liquidities against climate risks biennially; the next stress test is planned for summer 2023\. Participating insurers will need to respond to questions around their strategic responses to the three CBES scenarios. Central to these are the abilities of banks to have sufficient reserves for climate shocks. Estimating damage from flooding has always been reliant on understanding the depth and duration of events. Use of depth-damage curves has become industry standard for finance and insurance modelling. However, before an event, no system has been able to supply such data as existing technologies only show areas at risk based on generic event simulations. By simulating predicted depth times of floods ahead of events, Previsico has created the ability to produce pre-event automated loss estimations, for the first time, globally. Specifically, loss estimates for surface water and small watercourse flooding provide critical insights for the financial sector to support decision making, driving climate resilience. Further, loss estimates delivered alongside real-time risk assessments for assets can 1) help insurers reserve enough capital in advance of events so that they are able to pay-out their customer's claims in a timely and cost-effective manner and 2) support improved flood response capabilities for both the financial sector and associated stakeholders, helping deliver direct and indirect savings to assets and critical infrastructure, and mitigate impacts on the wider economy by supporting business continuity.During Phase 1, a MVP - representing the combination of flood forecasts and nowcasts and forecasted losses on a single dashboard and email - was developed, tested and then demonstrated in a non-production environment. Phase 2 will correspond to the operationalisation, live trialling and then refinement of the developed MVP in partnership with financial sector partners/clients with different specialisms and therefore, applications/uses for the technology. Specifically, the developed MVP will be extensively trialled across the UK, with stakeholder feedback on the form and functionality of the developed MVP collected. Furthermore, and through focused feedback sessions with selected partners, feedback on algorithm performance will be sought and used to significantly improve the accuracy of outputs, the granularity of forecasting losses, and the way forecasts are communicated. An integral part of this work will be accessing the partners portfolios of loss data to back-test past events, comparing their claims experience against Previsico's loss predictions.

在对气候相关金融风险进行初步监管后，英格兰银行要求英国银行和保险公司每两年对其资产和流动性进行气候风险压力测试；下一次压力测试计划在2023年夏季进行。参与的保险公司将需要回答有关其对三种CBES情景的战略反应的问题。这些问题的核心是银行是否有足够的储备来应对气候冲击。估计洪水造成的损失一直依赖于了解事件的深度和持续时间。深度损害曲线的使用已经成为金融和保险建模的行业标准。然而，在事件发生之前，没有系统能够提供这样的数据，因为现有技术只能显示基于一般事件模拟的风险区域。通过在事件发生前模拟预测洪水深度时间，Previsico首次在全球范围内创建了事件发生前自动损失估计的能力。具体而言，地表水和小水道洪水的损失估算为金融部门提供了重要的见解，以支持决策，推动气候适应能力。此外，与实时资产风险评估一起提供的损失估计可以1)帮助保险公司在事件发生前储备足够的资金，以便他们能够以及时和具有成本效益的方式支付客户的索赔；2)支持提高金融部门和相关利益相关者的洪水响应能力，帮助为资产和关键基础设施提供直接和间接的节省。并通过支持业务连续性来减轻对更广泛经济的影响。在第一阶段，MVP（代表洪水预报和即时预报的结合，并在单个仪表板和电子邮件上预测损失）进行了开发、测试，然后在非生产环境中进行了演示。第二阶段将与具有不同专业知识的金融部门合作伙伴/客户以及该技术的应用/用途合作，对开发的MVP进行操作、现场试验和改进。具体来说，开发的MVP将在英国广泛试用，并收集利益相关者对开发MVP的形式和功能的反馈。此外，通过与选定的合作伙伴进行集中反馈，将寻求关于算法性能的反馈，并用于显着提高输出的准确性，预测损失的粒度以及预测的沟通方式。这项工作的一个组成部分将是访问合作伙伴的损失数据组合，以回测过去的事件，将他们的索赔经验与Previsico的损失预测进行比较。