Credit Analysis in Banking Industry

Abstract

Our economy depends on data which is everywhere, in every section, in every country. We produce and convert it into useable data. Information allows us to enhance the business processes and provide our customers and partners with the best quality standards, services and products. The phenomenal rise in information, and problems encountered while dealing with huge amount of data, make it necessary for an organization to introduce a technique that can overcome these problems and provide an effective solution. Every year the banking organizations, generate enormous amount of valuable data from their customers and their transactions. These valuable data need to be saved and analyzed effectively using big data analytic techniques so as to get the necessary and useful insights for the banking sector. Big Data Analytics (BDA) provides a better consumer experience with better data management creating transparency, collecting more accurate and detailed performance data, setting up controlling experiments, segmenting populations to customize actions, and replacing/supporting human decisions making with automated algorithms. The primary focus of our proposed work will be on identifying the issues that the banking sector faces in decision making while granting loans to customers, in detail and providing an optimal solution using the Big Data approach and tools like Hadoop, HDFS, Spark etc.