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Original Article
Customer Engagement, Product Utilization, and Retention Analytics in European Banking: A Multi-Dimensional Churn Intelligence Framework
Ganapathi Kakarla1
1 Independent Researcher, PGDM Artificial Intelligence and Data Science, IIHMR, Bangalore, Karnataka, India.
Published Online: May-August 2026
Pages: 837-845
Cite this article
↗ https://www.doi.org/10.59256/indjcst.20260502090References
1. Au, W. H., Chan, K. C. C., & Yao, X. (2003). A novel evolutionary data mining algorithm with applications to churn prediction. IEEE
Transactions on Evolutionary Computation, 7(6), 532-545. https://doi.org/10.1109/TEVC.2003.819264
2. Bolt, W., Humphrey, D., & Uittenbogaard, R. (2008). Transaction pricing and the adoption of electronic payments: A cross-country
comparison. International Journal of Central Banking, 4(1), 89-123.
3. Bundesbank (2024). Banking statistics report: German retail banking landscape. Deutsche Bundesbank. Frankfurt am Main.
4. EBA (2023). Risk assessment of the European banking system. European Banking Authority. Paris.
5. ECB (2024). Financial stability review: European banking sector resilience. European Central Bank. Frankfurt am Main.
6. Eling, M., & Lehmann, M. (2018). The impact of digitalization on the insurance value chain and the insurability of risks. The Geneva
Papers on Risk and Insurance, 43(3), 359-396. https://doi.org/10.1057/s41288-017-0073-0
7. Hadden, J., Tiwari, A., Roy, R., & Ruta, D. (2007). Computer assisted customer churn management: State-of-the-art and future trends.
Computers & Operations Research, 34(10), 2902-2917. https://doi.org/10.1016/j.cor.2005.11.007
8. Hirschman, A. O. (1970). Exit, voice, and loyalty: Responses to decline in firms, organizations, and states. Harvard University Press.
Cambridge, MA.
9. Hoehle, H., Scornavacca, E., & Huff, S. (2012). Three decades of research on consumer adoption and utilisation of electronic banking
channels: A literature analysis. Decision Support Systems, 54(1), 122-132. https://doi.org/10.1016/j.dss.2012.04.010
10. Keramati, A., Ghaneei, H., & Mirmohammadi, S. M. (2014). Developing a prediction model for customer churn from electronic banking
services using data mining. Financial Innovation, 5(1), 1-23. https://doi.org/10.1186/s40854-019-0130-2
11. Lemmens, A., & Croux, C. (2006). Bagging and boosting classification trees to predict churn. Journal of Marketing Research, 43(2), 276-
286. https://doi.org/10.1509/jmkr.43.2.276
12. Reichheld, F. F., & Sasser, W. E. (1990). Zero defections: Quality comes to services. Harvard Business Review, 68(5), 105-111.
13. Reichheld, F. F., & Schefter, P. (2000). E-loyalty: Your secret weapon on the web. Harvard Business Review, 78(4), 105-113.
14. Reinartz, W. J., & Kumar, V. (2002). The mismanagement of customer loyalty. Harvard Business Review, 80(7), 86-95.
15. Van Doorn, J., Lemon, K. N., Mittal, V., Nass, S., Pick, D., Pirner, P., & Verhoef, P. C. (2010). Customer engagement behavior:
Theoretical foundations and research directions. Journal of Service Research, 13(3), 253-266. https://doi.org/10.1177/1094670510375599
16. Verbeke, W., Dejaeger, K., Martens, D., Hur, J., & Baesens, B. (2012). New insights into churn prediction in the telecommunication sector:
A profit driven data mining approach. European Journal of Operational Research, 218(1), 211-229.
https://doi.org/10.1016/j.ejor.2011.09.031
17. Verhoef, P. C. (2003). Understanding the effect of customer relationship management efforts on customer retention and customer share
development. Journal of Marketing, 67(4), 30-45. https://doi.org/10.1509/jmkt.67.4.30
18. Xie, Y., Li, X., Ngai, E. W. T., & Ying, W. (2009). Customer churn prediction using improved balanced random forests. Expert Systems
with Applications, 36(3), 5445-5449. https://doi.org/10.1016/j.eswa.2008.06.121
Transactions on Evolutionary Computation, 7(6), 532-545. https://doi.org/10.1109/TEVC.2003.819264
2. Bolt, W., Humphrey, D., & Uittenbogaard, R. (2008). Transaction pricing and the adoption of electronic payments: A cross-country
comparison. International Journal of Central Banking, 4(1), 89-123.
3. Bundesbank (2024). Banking statistics report: German retail banking landscape. Deutsche Bundesbank. Frankfurt am Main.
4. EBA (2023). Risk assessment of the European banking system. European Banking Authority. Paris.
5. ECB (2024). Financial stability review: European banking sector resilience. European Central Bank. Frankfurt am Main.
6. Eling, M., & Lehmann, M. (2018). The impact of digitalization on the insurance value chain and the insurability of risks. The Geneva
Papers on Risk and Insurance, 43(3), 359-396. https://doi.org/10.1057/s41288-017-0073-0
7. Hadden, J., Tiwari, A., Roy, R., & Ruta, D. (2007). Computer assisted customer churn management: State-of-the-art and future trends.
Computers & Operations Research, 34(10), 2902-2917. https://doi.org/10.1016/j.cor.2005.11.007
8. Hirschman, A. O. (1970). Exit, voice, and loyalty: Responses to decline in firms, organizations, and states. Harvard University Press.
Cambridge, MA.
9. Hoehle, H., Scornavacca, E., & Huff, S. (2012). Three decades of research on consumer adoption and utilisation of electronic banking
channels: A literature analysis. Decision Support Systems, 54(1), 122-132. https://doi.org/10.1016/j.dss.2012.04.010
10. Keramati, A., Ghaneei, H., & Mirmohammadi, S. M. (2014). Developing a prediction model for customer churn from electronic banking
services using data mining. Financial Innovation, 5(1), 1-23. https://doi.org/10.1186/s40854-019-0130-2
11. Lemmens, A., & Croux, C. (2006). Bagging and boosting classification trees to predict churn. Journal of Marketing Research, 43(2), 276-
286. https://doi.org/10.1509/jmkr.43.2.276
12. Reichheld, F. F., & Sasser, W. E. (1990). Zero defections: Quality comes to services. Harvard Business Review, 68(5), 105-111.
13. Reichheld, F. F., & Schefter, P. (2000). E-loyalty: Your secret weapon on the web. Harvard Business Review, 78(4), 105-113.
14. Reinartz, W. J., & Kumar, V. (2002). The mismanagement of customer loyalty. Harvard Business Review, 80(7), 86-95.
15. Van Doorn, J., Lemon, K. N., Mittal, V., Nass, S., Pick, D., Pirner, P., & Verhoef, P. C. (2010). Customer engagement behavior:
Theoretical foundations and research directions. Journal of Service Research, 13(3), 253-266. https://doi.org/10.1177/1094670510375599
16. Verbeke, W., Dejaeger, K., Martens, D., Hur, J., & Baesens, B. (2012). New insights into churn prediction in the telecommunication sector:
A profit driven data mining approach. European Journal of Operational Research, 218(1), 211-229.
https://doi.org/10.1016/j.ejor.2011.09.031
17. Verhoef, P. C. (2003). Understanding the effect of customer relationship management efforts on customer retention and customer share
development. Journal of Marketing, 67(4), 30-45. https://doi.org/10.1509/jmkt.67.4.30
18. Xie, Y., Li, X., Ngai, E. W. T., & Ying, W. (2009). Customer churn prediction using improved balanced random forests. Expert Systems
with Applications, 36(3), 5445-5449. https://doi.org/10.1016/j.eswa.2008.06.121
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