Cognitive Claims AI

IMC正在为财产和意外险（P&C）行业开发一个工具。财险公司正在想方设法降低索赔成本（目前约占保费的60%），同时提高欺诈检出率，他们估计欺诈检出率约为实际欺诈的10%。IMC认为，有可能通过利用现有数据预测索赔人的行为并适当对待他们来改善这种表现。最有用的数据将是客户的索赔声明，然而，由于这是电话访谈的形式，它不容易用于算法建模。因此，IMC正在寻求一种方法，将索赔声明的内容转化为可用于索赔结果预测建模的数据。IMC已经确定了一些将自然语言数据转换为数值分数的工具，但是考虑的预测问题是非标准的，因此需要重新开发新的数据建模方法。有机会与Pralat博士合作研究这种算法的潜力，将使IMC能够确定该工具是否代表一个可行的机会。

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.