Information Systems Review (경영정보학연구)

The Korea Society of Management Information Systems (한국경영정보학회)
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Customer Churning Forecasting and Strategic Implication in Online Auto Insurance using Decision Tree Algorithms

의사결정나무를 이용한 온라인 자동차 보험 고객 이탈 예측과 전략적 시사점

  • Lim, Se-Hun (Dept. of Management Information Systems, Sangji University) ;
  • Hur, Yeon (Dept. of Business Administration, Chung-Ang University)
  • 임세현 (상지대학교 경영정보학과) ;
  • 허연 (중앙대학교 상경학부)
  • Published : 2006.12.31
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Abstract

This article adopts a decision tree algorithm(C5.0) to predict customer churning in online auto insurance environment. Using a sample of on-line auto insurance customers contracts sold between 2003 and 2004, we test how decision tree-based model(C5.0) works on the prediction of customer churning. We compare the result of C5.0 with those of logistic regression model(LRM), multivariate discriminant analysis(MDA) model. The result shows C5.0 outperforms other models in the predictability. Based on the result, this study suggests a way of setting marketing strategy and of developing online auto insurance business.

본 연구에서는 온라인 자동차보험 고객 이탈 예측에 있어 의사결정나무를 적용하였다. 우리는 본 연구에서 2003년과 2004년 사이에 온라인 자동차 보험을 계약한 고객의 데이터를 이용하여 의사결정나무를 이용해 고객이탈을 예측하였다. 우리는 C5.0 알고리즘에 기반을 둔 의사결정나무의 예측 결과에 대한 비교를 위해 다변량판별분석과 로짓분석을 이용하였다. 분석결과 의사결정나무 알고리즘은 다른 기법보다 예측성과가 매우 뛰어난 것으로 나타났다. 이러한 실증분석 결과는 온라인 자동차 보험에 있어서 마케팅전략 수립에 유용한 가이드라인을 제공해 줄 것이다.

Keywords

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