Logic-based formula management strategies in an actuarial consulting system

In many decision support systems, multiple decision methods and models must be combined for solving a complex problem. Expertise is required for selecting, adapting and coordinating appropriate models. This paper describes the design and implementation of a knowledge-based model management system called the Actuarial Consulting System (ACS). The ACS supports actuaries in making pricing decisions in the domain of life insurance. Actuarial knowledge is organized using a graph formalism called Formula Derivation Network (FDN), represented in Prolog as a hierarchy of predicates. On the user level, a Problem Analyzer converts a problem specification by the user into a search problem on the stored collection of FDNs. Using different search strategies, including human expert rules, the Surface Planner generates an efficient solution strategy (sequence of models). At the lowest level, a Plan Executor retrieves or requests model data and issues appropriate function calls to a subroutine library.