A critical success factor in Insurance business is its ability to use information sources and contained knowledge in the most effective way. Its profitability is obtained through the Technical management plus Financial management of the funds gathered on the market. The profitability of a given customer can be evaluated through its Life Time Value (LTV). We aim at applying evolutionary algorithms to the problem of forecasting the future LTV in the Insurance Business. The Framework developed within the Eureka cofunded research projects HPPC/SEA and IKF has been adapted to the Insurance Domain through a dedicated Genetic Engine. The solution uses RDF and XMLcompliant standard. The idea of using evolutionary algorithms to design fuzzy systems date from the beginning of the Nineties and a fair body of work has been carried out throughout the past decade. The approach we followed uses an evolutionary algorithm to evolve fuzzy classifiers of the data set.
|Titolo:||Learning environment for life time value calculation of customers in insurance domain|
|Settore Scientifico Disciplinare:||Settore INF/01 - Informatica|
|Data di pubblicazione:||2004|
|Tipologia:||Book Part (author)|
|Appare nelle tipologie:||03 - Contributo in volume|