Deployment of churn prediction model in financial services industry

Charles CHU, Guandong XU, James BROWNLOW, Bin FU

Research output: Chapter in Book/Report/Conference proceedingChapters

6 Citations (Scopus)

Abstract

Nowadays, data analytics techniques are playing an increasingly crucial role in financial services due to the huge benefits they bring. To ensure a successful implementation of an analytics project, various factors and procedures need to be considered besides technical issues. This paper introduces some practical lessons from our deployment of a data analytics project in a leading wealth management company in Australia. Specifically, the process of building a customer churn prediction model is described. Besides common steps of data analysis, how to deal with other practical issues like data privacy and change management that are encountered by many financial companies are also introduced. Copyright © 2017 IEEE. All rights reserved.

Original languageEnglish
Title of host publicationProceedings of 2016 International Conference on Behavioral, Economic, Socio, Cultural Computing
PublisherIEEE
ISBN (Electronic)9781509061648
DOIs
Publication statusPublished - Jan 2017

Citation

Chu, C., Xu, G., Brownlow, J., & Fu, B. (2017). Deployment of churn prediction model in financial services industry. In Proceedings of 2016 International Conference on Behavioral, Economic, Socio, Cultural Computing. IEEE. https://doi.org/10.1109/BESC.2016.7804486

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