Classification of insurance claim emails
Using a hybrid model for health claim email filtering could significantly reduce customer support workload, while maintaining a satisfactory response quality.
Insurance and reinsurance undertakings face an ever-increasing demand from their various stakeholders for a deeper understanding of financial results and risk profiles. Meeting this demand essentially places huge pressures on existing financial modeling capabilities. Over time, the resource requirements of these systems (both in terms of cost and time) may become excessive.
A number of potential solutions to this problem have emerged. Amongst these is the suite of ‘proxy modeling’ techniques. The primary objective of this paper is to consider a case study application of one of these techniques to variable annuity (VA) business, namely the Least Squares Monte Carlo (LSMC) technique.
The case study covers the calculation of capital requirements as at the balance sheet date (and particularly in the context of Solvency II, although the conclusions have wider application to economic capital modeling in general). Consideration is also given to the extension of the LSMC method to other contexts such as Own Risk and Solvency Assessment (ORSA). This case study successfully demonstrates how the LSMC technique may be calibrated to model VA business, bearing in mind that in successfully applying this technique to such a complex product structure we have indirectly demonstrated that it will also work successfully for other product types.