Fuzzy modeling of client preference from large data sets: An application to target selection in direct marketing

Advances in computational methods have led, in the world of financial servi ces, to huge databases of client and market information, In the past decade , various computational intelligence (CI) techniques have been applied in m ining this data for obtaining knowledge and in-depth information about the clients and the markets. This paper discusses the application of fuzzy clus tering in target selection from large databases for direct marketing (DM) p urposes. Actual data from the campaigns of a large financial services provi der are used as a lest case. The results obtained with the fuzzy clustering approach are compared with those resulting from the current practice of us ing statistical tools for target selection.