SEKAID (Shannon Entropy Knowledge Acquisition in Insurance Domain) Methodology for Adaptive Data Mining Analysis

J. López-Herrera (Spain)


Simulation, artificial intelligence, Data Mining, preferences, insurance


SEKAID is a prediction methodology based on Shannon Entropy [1, 2]. From the analysis of clients’ insurance policy portfolios, it can be determined if the policy will be cancelled or not during a determined period of time. With the obtained results, marketing campaigns can be undertaken [3] which allow the client loyalty of the portfolio to be improved [4]. To demonstrate the effectiveness of this methodology, an automobile insurance portfolio is analyzed. A software application was developed to help perform the necessary tests in order to determine the most adequate configuration..

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