An Analysis of Big Data Analytics, IoT and Augmented Banking on Consumer Loan Banking Business in Germany

Agile visual analytics for banking cyber "big data"

This paper describes the rapid development of a tailored cyber situational awareness and analysis application for the 2012 IEEE VAST Mini-Challenge 1 (MC1) – Cyber Situation Awareness. The novel aspect of this project was in the process of developing the tailored solution for a “big data” application. Aperture is an open, adaptable, and extensible Web 2.0 visualization framework, designed to pr...

iCARE: A framework for big data-based banking customer analytics

The amount of data stored by banks is rapidly increasing and provides the opportunity for banks to conduct predictive analytics and enhance its businesses. However, data scientists are facing large challenges, handling the massive amount of data efficiently and generating insights with real business value. In this paper, the Intelligent Customer Analytics for Recognition and Exploration (iCARE)...

Data Warehousing and Analytics in Banking: Concepts

In an increasingly competitive market, banks are constantly searching for sustainable competitive advantage to help them maintain their edge against competition. Over the years, banks have tried various drivers for competitive advantage, none of which were sufficient barriers for competitors. Understanding the behavior of their customers and using this knowledge to drive the interaction with cu...

Unexpected Banking Loan Losses in an Estimated DSGE Model

  In spite of realizing more loss than expected and reserved provision in loaning process, some of our banks avoid recognizing the losses, through extension of the loan contracts and consequently do not shift the realized losses to their capital. With this in mind, the major objective of this study is to design a frame-work, through which we can explain the differences between the results of t...

Big Data Cases in Banking and Securities