I-Corps: Intelligent risk management for the US crop insurance industry

这个i-Corps项目的更广泛的影响/商业潜力是为与农业相关的行业提供新的田野级别的情报，以可持续发展和生产力的细粒度指标的形式为关键的农业决策提供信息。消费品(CPG)公司可以使用这些可持续发展指标和相关服务来量化和监测其承包农田的环境足迹，这可能有助于实现其可持续采购目标。农田生产力指标与相关的财务信息结合在一起时，对任何与农业有关的财务决策都是重要的。例如，(再)保险公司可以使用这些生产率指标在生长季开始之前评估潜在的保险风险，确定再保险合同的定价，并为发展中国家开发基于指数的新作物保险产品。农业贷款机构可以使用这些指标来估计单个农户的潜在违约风险，并量化其整个农业贷款组合的综合风险。我们的指标还可以为农田投资者提供更全面的农田适宜性、盈利能力和耕作风险的评估，以便做出明智的土地投资决策。最后但并非最不重要的一点是，大宗商品交易商还可以使用实时产量预测来预测市场上潜在的价格变化。这个i-Corps项目探索农业行业的颗粒级可持续性和生产率指标市场。这些技术包括卫星数据、基于深域知识的建模、人工智能和云计算相结合，以实现完整且可扩展的解决方案，以评估现场级信息的可持续性、生产力和金融风险。这些细粒度指标包括1)作物指标(例如作物类型、作物产量、过去30年每年变化的农田边界和预测)；2)可持续性指标(例如田间规模的管理实践、碳排放、土壤有机碳的储存和变化、作物水分消耗、土壤水分、氮淋失)；以及3)财务风险(例如作物保险损失率的概率分布、农场层面的收入财务预测)。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

The broader impact/commercial potential of this I-Corps project is in providing agriculture-related industries with novel field-level intelligence to inform critical farming decisions in the form of granular metrics for sustainability and productivity. Consumer packaged goods (CPG) companies could use these sustainability metrics and related services to quantify and monitor the environmental footprint on their contracted farmland, which may help to achieve their sustainable sourcing targets. The farmland productivity metrics, when incorporated with related financial information, are important for any farming-related financial decisions. For example, the (re)insurance companies could use these productivity metrics to assess the potential insurance risk before the growing season starts, determine the pricing of reinsurance contracts, and develop new index-based crop insurance products for developing countries. Farm loan lenders could use these metrics to estimate the potential default risk for individual farmers, and quantify the aggregated risk for their entire farm loan portfolio. Our metrics could also provide a more comprehensive evaluation of farmland’s suitability, profitability and farming riskiness for farmland investors to make informed land investment decisions. Last but not least, the commodity traders could also use the real-time yield forecast to predict the potential price changes in the market.This I-Corps project explore the market for granular level sustainability and productivity metrics in the agriculture industry. The technologies include satellite data, modeling based on deep domain knowledge, artificial intelligence, and cloud computing combined together to achieve a complete and scalable solution to assess field-level information for sustainability, productivity, and financial risks. These granular metrics include 1) crop metrics (e.g. crop types, crop yield, annually-changing field boundary, for both past 30 years and forecasting; 2) sustainability metrics (e.g. field-scale management practices, carbon emission, storage and change of soil organic carbon, crop water consumption, soil moisture, nitrogen leaching); and 3) financial risks (e.g. probabilistic distribution of loss ratio for crop insurance, farm-level financial projection for revenue).This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.