Faculty Cybernetics, Statistics and Economic Informatics, The Bucharest University of Economic Studies, 6 Piata Romana, 1st district, 010374 Bucharest, Romania
Faculty Cybernetics, Statistics and Economic Informatics, The Bucharest University of Economic Studies, 6 Piata Romana, 1st district, 010374 Bucharest, Romania
Faculty Cybernetics, Statistics and Economic Informatics, The Bucharest University of Economic Studies, 6 Piata Romana, 1st district, 010374 Bucharest, Romania
Machine learning techniques have proven good performance in classification matters of all kinds: medical diagnosis, character recognition, credit default and fraud prediction, and also foreign exchange market prognosis. Customer segmentation in private banking sector is an important step for profitable business development, enabling financial institutions to address their products and services to homogeneous classes of customers. This paper approaches two of the most popular machine learning techniques, Neural Networks and Support Vector Machines, and describes how each of these perform in a segmentation process.
Smeureanu, I., Ruxanda, G., & Badea, L. M. (2013). Customer segmentation in private banking sector using machine learning techniques. Journal of Business Economics and Management, 14(5), 923-939. https://doi.org/10.3846/16111699.2012.749807
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