Big dataBanking Sector.Big data analytics is the complicated process of examining large and different types of data sets or big data to reveal information including hidden patterns, unknown correlations, market trends and customer preferences which will help organizations make informed business decisions...
Investments in Big Data analytics in banking sector totaled$20.8 billionin 2016, according to the IDCSemiannual Big Data and Analytics Spending Guide of 2016. This makes the domain one of the dominant consumers ofBig Data servicesand an ever-hungry market for Big Data architects, solutions and b...
Real-time view and analysis are critical towards competitive advantage in the financial/banking sector. The usage of Big Data analytics is gradually being integrated in many departments of the CaixaBank (security, risks, innovation, etc.). Therefore, there is a heterogeneous group of experts with...
Against this backdrop, this study investigates the impact of data-driven decision-making (DDDM) on productivity in the presence of data analytics capability of Pakistan’s banking sector. We explore this link based on innovation diffusion theory using Instrumental Variable Two-Stage Least Square. A...
(AsianFin)—The banking sector faces significant hurdles in applying large models due to stringent requirements for data compliance, security, accuracy, and reliability. Although initially expected to lead in large model adoption, the financial industry lags behind others like legal and HR sectors. Ch...
Application of Data Mining in Banking Sector: 1.Marketing: Data mining carry various analysis on collected data to determine the consumer behavior with reference to product,price and distribution channel. The reaction of the customers for the existing and new products can also be known based on wh...
At present, the role of the banking sector has increased significantly, not only in the development of national economies, but also of the world economy as a whole. In this regard, the special importance acquires an objective comparative assessment of large financial institutions by groups indicator...
(AsianFin)—The banking sector faces significant hurdles in applying large models due to stringent requirements for data compliance, security, accuracy, and reliability. Although initially expected to lead in large model adoption, the financial industry lags behind others like legal and HR sectors. Ch...
Data analytics is transforming investment banking for investors, managers, and institutions alike. Here are 5 important industry trends to watch.
Based on a two stage method this paper investigates the determinants of the cost efficiency (CE) of Egyptian banking sector. Employing data envelopment analysis (DEA). We compare the CE of large, medium and small banks and the CE of foreign and domestic banks using a balanced panel which cov...