Cognitive Claims AI

认知主张人工智能

• 批准号: 508821-2017
• 负责人: Pralat, Pawel
• 金额: $ 1.82万
• 依托单位: Ryerson University
• 依托单位国家: 加拿大
• 项目类别: Engage Grants Program
• 财政年份: 2017
• 资助国家: 加拿大
• 起止时间: 2017-01-01 至 2018-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=640144
• 关键词: Cognitive; Claims; AI

IMC is developing a tool for the Property & Casualty (P&C) insurance industry. P&C companies are seekingways to minimize their cost of claims (currently running at some 60% of premiums) as well as increase theirrate of fraud detection, which they estimate at 10% of actual fraud.IMC believes it is possible to improve this performance by using available data to predict the behaviour of theclaimant and treat them appropriately. The most useful data would be the statement of claim by the customer,however, as this is in the form of a telephone interview, it is not readily useable for algorithmic modelling.Therefore, IMC is seeking to find a way of turning the content of the statement of claim into data useable forpredictive modelling of the claim outcome. IMC has identified a number of tools for converting naturallanguage data into numerical scores, but the considered prediction problems are non-standard and so requiredevelopment of novel approaches to data modeling. The opportunity to collaborate with Dr. Pralat inresearching the potential for such algorithms will allow IMC to determine if this tool represents a viableopportunity.

IMC正在为财产和伤亡（P＆C）保险行业开发工具。宝洁公司正在寻求最大程度地减少其索赔成本（目前约60％的保费成本），并增加其欺诈检测的效率，他们估计，它们以实际欺诈的10％估计，IMC认为可以通过使用可用数据来预测公认和适当对待他们的行为来提高这种绩效。最有用的数据将是客户的索赔声明，但是，由于这是电话采访的形式，因此不容易适用于算法模式。因此，IMC正在寻求找到一种将索赔声明的内容转换为可用于预测索赔结果的可用数据的索赔声明。 IMC已经确定了许多用于将自然语言数据转换为数值得分的工具，但是所考虑的预测问题是非标准的，因此需要开发新的数据建模方法。与Pralat博士进行合作的机会，研究了这种算法的潜力将使IMC能够确定此工具是否代表可行的proptunity。