Portfolio Valuation and Premium Optimization

GLP does not believe that these two functions can be addressed separately. The value of a portfolio is dependent on having the premiums fully optimized. Most software used for this purpose relies on regression analysis to overlay known cost of insurance charges over a base mortality table to project the minimum premium necessary to keep a policy in force. However, based on our experience developing universal life insurance products, we know that this approach cannot identify all of the “levers” that are put into life insurance product designs.

For many products, the regression analysis solution will identify much of the value available through premium optimization. But regression analysis becomes less successful with the more complicated current assumption products and most of the secondary guarantee universal life products. GLP uses its product design software to create individual product models for these more complicated products, thereby identifying the value that the regression analysis methods miss.