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A Comparative Analysis of Machine Learning Algorithms for Predicting the Telemarketing Campaigns of Portuguese Banking Institutions
- 1 School of Computer Science, South China Normal University, Guangzhou, 510631, China
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Abstract
A financial institution is an entity of business that handles deposits, money circulation, saving, and other corresponding operations. Banks supply a broad spectrum of services. This differs depending on the capacity of each bank. The bank is going to provide further amenities, which is one of the many industries that frequently engage in direct product launches. Thus, banks might employ technological innovations to do market investigation before directly releasing products, which may assist with decision-making. Marketing initiatives that offer prospective consumers the option of embracing or rejecting an offered product can be carried out using direct email, phone calls, and email campaigns. The volume of incoming data continues to expand as time goes by. One of the bank institutions in Portugal faced difficulties judging whether or not its customer base would choose to sign up for a term deposit because of the growing amount of data. Consequently, to ascertain if the consumer will subscribe to a term deposit, the data mining processes utilized here will incorporate Ensemble Learning (Gradient Boosting (GB), Xg Boost (XGB), Random Forest (RF), Linear Models (Logistic Forest (RF), Linear Models (Logistic Regression (LR), Non-Linear Models (K-Near Neighbors (KNN), Support Vector Machine (SVM), Decision Tree Classifier (DT)), and Probabilistic Models (Naive Bayes (NB))included in classification techniques. Among these, Xg Boost yields the most impressive results, with the best performance in terms of AUC, model accuracy, and cross-validation accuracy in a minimum amount of computation time.
Keywords
Direct Marketing, Telemarketing Campaigns, Machine Learning
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Cite this article
Huang,S. (2024). A Comparative Analysis of Machine Learning Algorithms for Predicting the Telemarketing Campaigns of Portuguese Banking Institutions. Advances in Economics, Management and Political Sciences,94,44-53.
Data availability
The datasets used and/or analyzed during the current study will be available from the authors upon reasonable request.
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