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Research Paper | Decision Science | Volume 13 Issue 1, January 2024 | Pages: 460 - 463 | India
Analyzing Credit Card Consumer Behavior using Unsupervised Machine Learning Techniques
Abstract: Credit cards are extensively utilized financial products that provide users with ease and flexibility. However, understanding and predicting credit card consumer behavior remains a complex challenge. Machine learning has evolved as an invaluable technique for analyzing massive information and extracting important insights, allowing businesses to better understand their consumers and design effective strategies. This paper analyzes the effective application of data science with ML models in the credit card consumer behavior. It goes over different data sources, machine learning algorithms, and the advantages of using data science.
Keywords: Customer segmentation, Credit card, Unsupervised ML models
How to Cite?: Ritambhara Jha, "Analyzing Credit Card Consumer Behavior using Unsupervised Machine Learning Techniques", Volume 13 Issue 1, January 2024, International Journal of Science and Research (IJSR), Pages: 460-463, https://www.ijsr.net/getabstract.php?paperid=SR24106025150, DOI: https://dx.doi.org/10.21275/SR24106025150