Statistical and Data Analytics Approaches to Parameter Tuning for Enhancing QoS of E-Banking Transactions: A Case Study of Sample Bank

As e-banking networks have advanced rapidly, the majority of financial transactions are conducted through the use of credit cards. A number of qualitative indices, including error rate and response time, are influenced by the performance of each node in the transaction process. This study examines the issue of tuning the time-out between a sample bank's switch and core systems using a statistical data analysis. By analyzing the transaction data of three years and applying statistical parameter tuning approach, resources can be allocated effectively to prevent errors and delays, thereby improving the QoS of e-banking. Moreover, this approach can be applied to other banks or payment systems to enhance performance without requiring significant hardware modifications. Results from the parameter tuning, based on analyzing data, showed a considerable improvement in the error average and variance and an increase in bank switch capacity, which was confirmed by statistical analysis and the central bank’s reports.

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