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

Algorithms

Shaoyin Wang¹  Wei Nai¹  Decun Dong²  Lu Liu³ 

[1] Department of Electronic and Information Engineering, Tongji Zhejiang College, Jiaxing 314051, China;Key Laboratory of Road and Traffic Engineering, Ministry of Education, Tongji University, Shanghai 201804, China;Whitman School of Management, Syracuse University, Syracuse, NY 13244, USA;

关键词: statistics of credit card usage;    singular spectrum analysis (SSA);    time series;    behavior analysis;    trend modeling;   

DOI  :  10.3390/a11020015

来源: DOAJ

【 摘 要 】

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.

【 授权许可】

Unknown