Data Mining: A Tool for Enhancing Business Process in Banking Sector
R. Mahammad Shafi, Porandla Srinivas · 2012
Significant shifts in the business environment, economic volatility, changing customer and staff expectations, and the adopti on of new tech- nology make it increasingly challenging for banks to navigate technology strategy alternatives and prioritize technology investments. The banking indus- try around the world has undergone a tremendous change in the way business is conducted. Leading banks are using Data Mining (DM) tools for cus- tomer segmentation and profitability, credit scoring and approval, predicting payment default, marketing, detecting fraudulent transactions, etc. This pa- per provides an overview of the concept of Data Mining. Data might be one of the most valuable assets of any corporation, but only if it knows how to reveal valuable knowledge hidden in raw data. Data mining allows extracting diamonds of knowledge from the historical data, and predicting outcomes of future situations. It helps optimize business decisions, increase the value of each customer and communication, and improve customer satisfaction. Data mining is the process of extracting previously un- known information, typically in the form of patterns and associations, from large databases. Today, organizations are realizing the numerous advantages that come with data mining. It is a valuable tool, by identifying potentially useful information from the large amounts of data collected. An organization can gain a clear advantage over its competitors. The banking sector consists of public sector, private sector and foreign banks, apart from smaller regional and cooperative b anks. In the market, various IT-based banking products, services and solutions are available. The most common of them are Phone Banking; ATM facility; Credit, Debit and Smart Cards; Internet Banking & Mobile Banking; SWIFT Network & INFINET Network; connectivity of bank branches to facilitate anywhere banking.