Authors : Mohelska Hana and Vokalova Andrea
Abstract: Data mining is a process of sifting through a very large amounts of data for useful information. Data mining uses artificial intelligence techniques, neural networks and advanced statistical tools to reveal trends, patterns and relationships which might otherwise have remained undetected. Currently, this information is used increasingly, despite the significant difference in the way that organizations handle such information. This study aims to describe data mining in the financial sector by using two typical banks which together hold more than 7.8 million clients in the Czech financial sector. A common feature of these companies is their size and total number of clients. The study evaluates the role and importance of data mining in these large banking institutions. The first research question of the presented study is dealing with a utilization of DM and its influence on profit and on the total number of clients. The second research question is evaluating the level of client’s segmentation and its advantages in both banks. Generally, the Czech financial sector uses DM very sophisticated in order to not only evaluate its actual state (thank to reporting, etc.) but also in order to help the predictions of future needs and state.
Mohelska Hana and Vokalova Andrea, 2019. Data Mining Applications in a Financial Sector-Case Study of Czech Republic. Journal of Engineering and Applied Sciences, 14: 9300-9305.