Subrogation Prediction Through Text Mining and Data Modeling
June 10th, 2008. Sergei Ananyan of Megaputer Intelligence presents at the 4th Annual National Workers’ Compensation Subrogation Strategies Executive Summit. Synopsis Insurance companies have to timely process overwhelming volumes of claims, frequently quite complex and lengthy. In this challenging environment, they can easily miss valid subrogation opportunities and thus not recover the money they are entitled to. Subrogations help recover substantial funds, but only a small percentage of cases represent valid subrogation opportunities. Currently, insurance companies task either individual adjusters or special recovery teams with determining the subrogation potential of handled claims. However, there is a general agreement in the industry that manual analysis of subrogation potential is rather inaccurate and time consuming, and a better solution is being sought. Intelligent automated systems combining text mining and data modeling techniques proved to be efficient in identifying valid subrogation opportunities. Such systems exploit the joint use of linguistic and semantic text…