Abstract
Payment Systems Providers (PSPs) are companies, which provide services of payment for their customers. Recently, according to some changes in Iran central bank rules, providing services of payment are not monitored by banks anymore. This duty is assigned to some organizations called PSPs and becomes one of the most challenging topics for them. Clustering the datasets, assessment and the way of expressing customers’ demands and the provinces of requests should be recognized for improving services to the customers, banks, financial and credit institutes. The proposed framework consists of two stages using k-means algorithm and Euclidean square distances. The k-means algorithm is applied in the first stage for five provinces, which have the highest demands. In the second stage, the mean of centroids obtained from k-means are calculated and repeat clustering according to the minimum Euclidean square distances to the new centroids then comparing the information gained by two stages.
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E., O.M.E., Babaie, S.S. (2015). Implementation of Two Stages k-Means Algorithm to Apply a Payment System Provider Framework in Banking Systems. In: Silhavy, R., Senkerik, R., Oplatkova, Z., Prokopova, Z., Silhavy, P. (eds) Artificial Intelligence Perspectives and Applications. Advances in Intelligent Systems and Computing, vol 347. Springer, Cham. https://doi.org/10.1007/978-3-319-18476-0_21
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DOI: https://doi.org/10.1007/978-3-319-18476-0_21
Publisher Name: Springer, Cham
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