An Application of Data Mining in Individual Pension Savings and Investment System

Abstract

Individual Pension System (IPS) is a personal future investment system that allows individuals to regularly save for their retirement. IPS is enacted by the law and supported by the government through state contribution. In Turkey, IPS entered into force on October 27, 2003 and it achieved an impressive progress over the last years. This improvement has caused increase in amount of raw data stored in databases. However, accumulated data are complicated and big to be processed and cannot be analyzed by classical methods. Data mining is becoming an essential tool to discover hidden and potentially useful knowledge from raw data. For this reason, application of data mining techniques on Individual Pension Savings and Investment system is necessary. In this study, one of the data mining techniques, decision tree classification, was used to determine customers’ profile. SPSS Clementine 12.0 software was used to develop a classification model. Analyses were performed by various decision tree algorithms. Some customer information of a pension company operating in Turkey were extracted from system. The significant rules about customers were revealed by analysis. The results of analysis indicated that the CHAID algorithm showed the best prediction with an accuracy of 85.64% among C5.0, C&R Tree, QUEST

Keywords

• Data mining,customer profile,individual pension system

An Application of Data Mining in Individual Pension Savings and Investment System

Öz

Individual Pension System (IPS) is a personal future investment system that allows individuals to regularly save for their retirement. IPS is enacted by the law and supported by the government through state contribution. In Turkey, IPS entered into force on October 27, 2003 and it achieved an impressive progress over the last years. This improvement has caused increase in amount of raw data stored in databases. However, accumulated data are complicated and big to be processed and cannot be analyzed by classical methods. Data mining is becoming an essential tool to discover hidden and potentially useful knowledge from raw data. For this reason, application of data mining techniques on Individual Pension Savings and Investment system is necessary. In this study, one of the data mining techniques, decision tree classification, was used to determine customers’ profile. SPSS Clementine 12.0 software was used to develop a classification model. Analyses were performed by various decision tree algorithms. Some customer information of a pension company operating in Turkey were extracted from system. The significant rules about customers were revealed by analysis. The results of analysis indicated that the CHAID algorithm showed the best prediction with an accuracy of 85.64% among C5.0, C&R Tree, QUEST.

Anahtar Kelimeler

• Data mining,customer profile,individual pension system

Kaynakça

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