Towards intelligent feature engineering for risk-based customer segmentation in banking

Sam Khadivizand, Amin Beheshti, Fariborz Sobhanmanesh, Quan Z. Sheng, Elias Istanbouli, Steven Wood, Damon Pezaro

Research output: Chapter in Book/Report/Conference proceedingConference proceeding contribution

Abstract

Business Processes, i.e., a set of coordinated tasks and activities to achieve a business goal, and their continuous improvements are key to the operation of any organization. In banking, business processes are increasingly dynamic as various technologies have made dynamic processes more prevalent. For example, customer segmentation, i.e., the process of grouping related customers based on common activities and behaviors, could be a data-driven and knowledge-intensive process. In this paper, we present an intelligent data-driven pipeline composed of a set of processing elements to move customers' data from one system to another, transforming the data into the contextualized data and knowledge along the way. The goal is to present a novel intelligent customer segmentation process which automates the feature engineering, i.e., the process of using (banking) domain knowledge to extract features from raw data via data mining techniques, in the banking domain. We adopt a typical scenario for analyzing customer transaction records, to highlight how the presented approach can significantly improve the quality of risk-based customer segmentation in the absence of feature engineering.

Original languageEnglish
Title of host publication18th International Conference on Advances in Mobile Computing and Multimedia, MoMM2020 - Proceedings
EditorsPari Delir Haghighi, Ivan Luiz Salvadori, Matthias Steinbauer, Ismail Khalil, Gabriele Kotsis
Place of PublicationNew York, NY
PublisherAssociation for Computing Machinery (ACM)
Pages74-83
Number of pages10
ISBN (Electronic)9781450389242
DOIs
Publication statusPublished - 2020
Event18th International Conference on Advances in Mobile Computing and Multimedia, MoMM 2020, in conjunction with the 22nd International Conference on Information Integration and Web-Based Applications and Services, iiWAS 2020 - Virtual, Online, Thailand
Duration: 30 Nov 20202 Dec 2020

Publication series

NameACM International Conference Proceeding Series

Conference

Conference18th International Conference on Advances in Mobile Computing and Multimedia, MoMM 2020, in conjunction with the 22nd International Conference on Information Integration and Web-Based Applications and Services, iiWAS 2020
CountryThailand
CityVirtual, Online
Period30/11/202/12/20

Keywords

  • banking processes
  • business process
  • feature engineering
  • risk-based customer segmentation

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