Credit Card Business in Malaysia: A Data Analytics Approach

Yaseen, Mohamed Khaled; Raheem, Mafas; Sivakumar, V.

doi:10.14569/ijacsa.2020.0111247

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2022

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“…1. The research uses the Random Forest algorithm to predict customer satisfaction with credit card services (Yaseen et al, 2020). 2.…”

Section: Introductionmentioning

confidence: 99%

Segmentation of Credit Card Customers Based on Their Credit Card Usage Behavior using The K-Means Algorithm

Karo Karo

2022

J. Soft. Eng. Inf. Comm. Tech.

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The intensity of credit card customers in making transactions has increased in the last 10 years in Indonesia. This is both a challenge and an opportunity for the Bank. Customer segmentation information is beneficial to reduce bad debts or increasing customer credit card limit capacity. This study aims to segment credit card customers based on their usage behavior with a clustering approach using the K-means algorithm. While the process of evaluating segmentation results using the silhouette index. Based on the experimental results, six groups are the best number of clusters. The six groups are shopping hobbies, payment process at maturity, payment by installments, withdrawing cash, buying expensive goods, and types that rarely use credit cards.

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“…1. The research uses the Random Forest algorithm to predict customer satisfaction with credit card services (Yaseen et al, 2020). 2.…”

Section: Introductionmentioning

confidence: 99%