DATA MINING. CONCEPTS AND APPLICATIONS IN BANKING SECTOR

The concept of banking refers to the multitude of services and products that commercial banks offer to clients and include besides transactional accounts both passive and active products. Due to the increased competitiveness in banking, the relationship between the bank and the client has become an essential factor for the strategy in order to increase customer satisfaction. Currently the banking system is able to store impressive amounts of data that they collect daily, from customer data and transaction details to data on their transactional or risk profile. The process through which large amounts of data are analyzed, extracted, identified and the information obtained using mathematical and statistical models are interpreted is known as data mining. The discovery of knowledge from data involves identifying some models, some patterns with which certain events or possible risks are anticipated. This process helps banks to develop strategies in areas such as customer retention and loyalty, customer satisfaction, fraud detection and prevention, risk management, money laundering prevention. The aim of this paper is to present the concept of data mining and the concept of data discovery (KDD), but also the impact and important use of data mining techniques in the banking sector. This paper explores and reviews various data mining techniques that are applied in the banking sector but also provides insight into how these techniques are used in different areas to make decision-making easier and more efficient

EVOLUTION OF CUSTOMERS’ SEGMENTATION TECHNIQUES IN RETAIL BANKING

In the context of a highly competitive market influenced by legislative changes, the technology evolution and the changes of customer’s behavior, traditional banks must be able to provide the services and products expected by customers. The most important method in retail banking by which a bank can interact with as many customers as possible to ensure satisfaction and loyalty is the notion of customers’ segmentation. The current situation from the perspective of customers’ expectations will be brought to your attention, as well as the future situation from the perspective of legislative changes and which are the main variables and techniques that allow us a relevant customers’ segmentation in this context. The challenges and opportunities of the Directive PDS2 (Payment Service Directive) [7] will be analyzed, which together with the results of a study carried out by Ernst & Young "The relevance of the challenge: what retail banks must do to remain in the game" [5], make me say that now, more than ever, commercial banks must pay special attention to customer‘ segmentation. The objective of this paper is to present the evolution of the customers’ segmentation process starting from the 50’s – 60’s, when the first segmentation techniques appeared, until now, when because of the large quantities of data, there are used increasingly advanced techniques for extracting and interpreting data