A geospatial asset management model for physical and transition risk assessments and capital reallocation (GeoAM2)
A geospatial asset management model for physical and transition risk assessments and capital reallocation (GeoAM2)
批准号:
10031494
负责人:
金额:
$6.37万
依托单位:
依托单位国家:
英国
项目类别:
Small Business Research Initiative
财政年份:
2022
资助国家:
英国
项目状态:
已结题
起止时间:
2022 至 --
中文摘要
GeoAM2是一种将气候风险评估无缝整合到资产管理可持续性实践中的创新方法。具体来说,其创新之处在于其对资产的预测性风险评估,作为一种早期预警信号,为管理者提供了可能需要干预的早期迹象。GeoAM2将空间金融整合到其分析框架中,以准确表示脆弱性和损害如何在资产组合中分布。地球观测和遥感与机器学习相结合,有可能改变我们金融系统中信息的可用性。它将使金融市场能够更好地衡量和管理与气候相关的风险,以及影响不同资产类别风险和回报的各种其他因素。因此,GeoAM2是一种颠覆性的资产管理方法,它寻求实现三件事:(1)将资产管理公司拥有的资产汇总到具有广泛独特铭牌数据的数据库中;(2)对这些资产进行地理定位和标记,以确定存在的国家或地区;(3)使用集成的AI和ML算法进化即时和预测性资产风险评估分数。GeoAM2对资产/财富管理公司持有的投资的子组件进行了实时分析,并为管理人员提供了两个风险评分(即时和预测),以突出和预测这些风险将如何根据预计的政府政策发生变化。该工具作为一种早期预警环境风险评估工具,确保管理人员能够快速分散投资,避免因投资组合管理策略不佳而导致的巨额环境/气候处罚所造成的损失。
英文摘要
GeoAM2 is an innovative approach to seamlessly integrate climate risk assessment into asset management sustainability practices. Specifically, the innovation lies in its predictive risk assessment of its assets as an early-warning signal giving managers early indications of when intervention may be needed. GeoAM2 integrates spatial finance into its analytical framework to evolve accurate representation of how vulnerability and impairments are distributed across a portfolio of assets. Earth observation and remote sensing combined with machine learning have the potential to transform the availability of information in our financial system. It will allow financial markets to better measure and manage climate-related risks, as well as a vast range of other factors that affect risk and return in different asset classes.GeoAM2 is thus a disruptive approach to asset management that seeks to achieve three things: (1) aggregate assets owned by asset management firms into a database with extensive unique nameplate data; (2) geolocate and tag these assets to determine countries or regions of existence; and (3) evolve immediate and predictive asset risk assessment scores using integrated AI and ML algorithms. GeoAM2 has in place the sub-components of investments held by asset/wealth management firms and in real-time and provides two risk scores (immediate and predicted) to managers highlighting and predicting how such risks will change based on projected government policies. This tool as an early-warning environmental risk assessment tool ensures that managers can quickly diversify investments and avoid losses occasioned by huge environmental/climate penalties due to poor portfolio management strategies.
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