Next Article in Journal
A Novel Spectrum Scheduling Scheme with Ant Colony Optimization Algorithm
Previous Article in Journal
An Optimal Online Resource Allocation Algorithm for Energy Harvesting Body Area Networks
Article Menu

Export Article

Open AccessArticle
Algorithms 2018, 11(2), 15; https://doi.org/10.3390/a11020015

Modeling the Trend of Credit Card Usage Behavior for Different Age Groups Based on Singular Spectrum Analysis

1
Department of Electronic and Information Engineering, Tongji Zhejiang College, Jiaxing 314051, China
2
Whitman School of Management, Syracuse University, Syracuse, NY 13244, USA
3
Key Laboratory of Road and Traffic Engineering, Ministry of Education, Tongji University, Shanghai 201804, China
*
Author to whom correspondence should be addressed.
Received: 12 December 2017 / Revised: 24 January 2018 / Accepted: 26 January 2018 / Published: 29 January 2018
View Full-Text   |   Download PDF [4515 KB, uploaded 29 January 2018]   |  

Abstract

Credit card holders from different age groups have different usage behaviors, so deeply investigating the credit card usage condition and properly modeling the usage trend of all customers in different age groups from time series data is meaningful for financial institutions as well as banks. Until now, related research in trend analysis of credit card usage has mostly been focused on specific group of people, such as the behavioral tendencies of the elderly or college students, or certain behaviors, such as the increasing number of cards owned and the rise in personal card debt or bankruptcy, in which the only analysis methods employed are simply enumerating or classifying raw data; thus, there is a lack of support in specific mathematical models based on usage behavioral time series data. Considering that few systematic modeling methods have been introduced, in this paper, a novel usage trend analysis method for credit card holders in different age groups based on singular spectrum analysis (SSA) has been proposed, using the time series data from the Survey of Consumer Payment Choice (SCPC). The decomposition and reconstruction process in the method is proposed. The results show that the credit card usage frequency falls down from the age of 26 to the lowest point at around the age of 58 and then begins to increase again. At last, future work is discussed. View Full-Text
Keywords: statistics of credit card usage; singular spectrum analysis (SSA); time series; behavior analysis; trend modeling statistics of credit card usage; singular spectrum analysis (SSA); time series; behavior analysis; trend modeling
Figures

Figure 1

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).
SciFeed

Share & Cite This Article

MDPI and ACS Style

Nai, W.; Liu, L.; Wang, S.; Dong, D. Modeling the Trend of Credit Card Usage Behavior for Different Age Groups Based on Singular Spectrum Analysis. Algorithms 2018, 11, 15.

Show more citation formats Show less citations formats

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Related Articles

Article Metrics

Article Access Statistics

1

Comments

[Return to top]
Algorithms EISSN 1999-4893 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top