nach oben

Erschienen in:

2016 | OriginalPaper | Buchkapitel

Predicting Probability of Customer Churn in Insurance

verfasst von : Catalina Bolancé, Montserrat Guillen, Alemar E. Padilla-Barreto

Erschienen in: Modeling and Simulation in Engineering, Economics and Management

Verlag: Springer International Publishing

Einloggen

Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.

search-config

KI-gestützte Suche

Aus

Abstract

We focus on a real case of the motor insurance sector. We propose four different methods to predict lapsing from a portfolio of policies. We present a comparative analysis between three different performance measures in order to assess the predictive power of each model. Our comparison analyses the outcomes of a logistic regression, a conditional tree, a neural network and a support vector machine. These are all considered basic approaches to data mining and knowledge discovery. The main contribution of this paper is to show that, depending on the type of analysis and the objective of the researcher, the optimal prediction method may differ.

Sie haben noch keine Lizenz? Dann Informieren Sie sich jetzt über unsere Produkte:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

über 102.000 Bücher
über 537 Zeitschriften

aus folgenden Fachgebieten:

Automobil + Motoren
Bauwesen + Immobilien
Business IT + Informatik
Elektrotechnik + Elektronik
Energie + Nachhaltigkeit
Finance + Banking
Management + Führung
Marketing + Vertrieb
Maschinenbau + Werkstoffe
Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

über 67.000 Bücher
über 390 Zeitschriften

aus folgenden Fachgebieten:

Automobil + Motoren
Bauwesen + Immobilien
Business IT + Informatik
Elektrotechnik + Elektronik
Energie + Nachhaltigkeit
Maschinenbau + Werkstoffe

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

über 67.000 Bücher
über 340 Zeitschriften

aus folgenden Fachgebieten:

Bauwesen + Immobilien
Business IT + Informatik
Finance + Banking
Management + Führung
Marketing + Vertrieb
Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Vorheriges Kapitel An Estimation of the Individual Illiquidity Risk for the Elderly Spanish Population with Long-Term Care Needs

Nächstes Kapitel Integrated Supply Chain Planning: A Review

Zeithaml, V.A., Berry, L.L., Parasuraman, A.: The behavioral consequences of service quality. J. Mark. 60, 31–46 (1996)CrossRef

Fornell, C., Wernerfelt, B.: Defensive marketing strategy by customer complaint management: a theoretical analysis. J. Mark. Res. 24, 337–346 (1987)CrossRef

Fornell, C., Wernerfelt, B.: A model for customer complaint management. Mark. Sci. 7(3), 287–298 (1988)CrossRef

Thuring, F., Nielsen, J.P., Guillen, M., Bolance, C.: Selecting prospects for cross-selling financial products using multivariate credibility. Expert Syst. Appl. 39(10), 8809–8816 (1988)CrossRef

Keaveney, S.M.: Customer switching behavior in service industries: an exploratory study. J. Mark. 59, 71–82 (1995)CrossRef

Brockett, P.L., Golden, L.L., Guillen, M., Nielsen, J.P., Parner, J., Pérez-Marín, A.M.: Survival analysis of a household portfolio of insurance policies: how much time do you have to stop total customer defection? J. Risk Insur. 75(3), 713–737 (2008)CrossRef

Fornell, C.: A national customer satisfaction barometer: the Swedish experience. J. Mark. 56, 6–21 (1992)CrossRef

Guillen, M., Nielsen, J.P., Scheike, T.H., Pérez-Marín, A.M.: Time-varying effects in the analysis of customer loyalty: a case study in insurance. Expert Syst. Appl. 39(3), 3551–3558 (2012)CrossRef

Guillen, M., Nielsen, J.P., Pérez-Marín, A.M.: The need to monitor customer loyalty and business risk in the European insurance industry. In: Geneva Papers on Risk and Insurance, Issues and Practice, pp. 207–218 (2008)

10.

Guelman, L., Guillen, M.: A causal inference approach to measure price elasticity in automobile insurance. Expert Syst. Appl. 41(2), 387–396 (2014)CrossRef

11.

Guelman, L., Guillen, M., Pérez-Marín, A.M.: A survey of personalized treatment models for pricing strategies in insurance. Insur. Math. Econ. 58, 68–76 (2014)MathSciNetCrossRefMATH

12.

Guelman, L., Guillen, M., Pérez-Marín, A.M.: A decision support framework to implement optimal personalized marketing interventions. Decis. Support Syst. 72, 24–32 (2015)CrossRef

13.

Guelman, L., Guillen, M., Pérez-Marín, A.M.: Uplift random forests. Cybern. Syst. 46(3–4), 230–248 (2015)CrossRef

14.

Guillen, M.: Regression with categorical dependent variables. In: Predictive Modeling Applications in Actuarial Science. Predictive Modeling Techniques, vol. 1, Cambridge University Press, Cambridge (2014)

15.

Fawcett, T.: An introduction to ROC analysis. Pattern Recognit. Lett. 27, 861–874 (2006)CrossRef

16.

Gigliarano, C., Figini, S., Muliere, P.: Making classifier performance comparisons when ROC curves intersect. Comput. Stat. Data Anal. 77, 300–312 (2014)MathSciNetCrossRef

17.

Stripling, E., Vanden Broucke, S., Antonio, K., Baesens, B., Snoeck, M.: Profit maximizing logistic regression modeling for customer churn prediction. In: IEEE International Conference on Data Science and Advanced Analytics (DSAA), pp. 1–10 (2015)

18.

Liu, Y., Zhang, H.H., Wu, Y.: Hard or soft classification? Large-margin unified machines. J. Am. Stat. Assoc. 106(493), 166–177 (2011)MathSciNetCrossRefMATH

19.

Hothorn, T., Hornik, K., Zeileis, A.: Unbiased recursive partitioning: a conditional inference framework. J. Comput. Graph. Stat. 15(3), 651–674 (2006)MathSciNetCrossRef

20.

Bishop, C.M.: Neural Networks for Pattern Recognition. Oxford University Press, Oxford (1995)MATH

21.

Ripley, B.D.: Pattern Recognition and Neural Networks. Cambridge University Press, Cambridge (1996)CrossRefMATH

22.

Boser, B.E., Guyon, I.M., Vapnik, V.N.: A training algorithm for optimal margin classifiers. In: Proceedings of the Fifth Annual Workshop on Computational Learning Theory, pp. 144–152. ACM (1992)

23.

Karatzoglou, A., Meyer, D., Hornik, K.: Support vector machines in R. J. Stat. Softw. 15(9), 1–28 (2006)CrossRef

24.

Hsu, C.W., Chang, C.C., Lin, C.J.: A Practical Guide to Support Vector Classification. Department of Computer Science, National Taiwan University, Taiwan (2003)

25.

Tao, D., Tang, X., Li, X., Wu, X.: Asymmetric bagging and random subspace for support vector machines-based relevance feedback in image retrieval. IEEE Trans. Pattern Anal. Mach. Intell. 28(7), 1088–1099 (2006)CrossRef

26.

Meyer, D., Dimitriadou, E., Hornik, K., Weingessel, A., Leisch, F.: Package ‘‘e1071”. Misc. Functions of the Department of Statistics (e1071), TU Wien. The comprehensive R archive network (2012)

27.

Chang, C.C., Lin, C.J.: LIBSVM: a library for support vector machines. ACM Trans. Intell. Syst. Technol. (TIST) 2(3), 27 (2011)

28.

Gelman, A., Hill, J.: Missing-data imputation. Data Analysis Using Regression and Multilevel/Hierarchical Models, 1st edn, pp. 529–544. Cambridge University Press, Cambridge (2006)

Titel: Predicting Probability of Customer Churn in Insurance
verfasst von: Catalina Bolancé
Montserrat Guillen
Alemar E. Padilla-Barreto
Verlag: Springer International Publishing
Buch: Modeling and Simulation in Engineering, Economics and Management
Print ISBN: 978-3-319-40505-6

Electronic ISBN: 978-3-319-40506-3

Copyright-Jahr: 2016
DOI: https://doi.org/10.1007/978-3-319-40506-3_9

Springer Professional

Abstract

Bitte loggen Sie sich ein, um Zugang zu Ihrer Lizenz zu erhalten.

Sie haben noch keine Lizenz? Dann Informieren Sie sich jetzt über unsere Produkte:

Springer Professional "Wirtschaft+Technik"

Springer Professional "Technik"

Springer Professional "Wirtschaft"