scholarly journals Monitoring Banking System Fragility with Big Data

2018 ◽  
pp. 01-41 ◽  
Author(s):  
Galina Hale ◽  
◽  
Jose A. Lopez ◽  
Keyword(s):  
Big Data ◽  
Banking System ◽  
System Fragility

scholarly journals Blockchain Disrupting Fintech and the Banking System

Proceedings ◽  
2021 ◽  
Vol 74 (1) ◽  
pp. 24
Author(s):  
Eduard Alexandru Stoica ◽  
Daria Maria Sitea
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Big Data ◽  
Financial Institutions ◽  
New World ◽  
Great Part ◽  
Banking System ◽  
Daily Activities ◽  
Blockchain Technology ◽  
Almost All

Nowadays society is profoundly changed by technology, velocity and productivity. While individuals are not yet prepared for holographic connection with banks or financial institutions, other innovative technologies have been adopted. Lately, a new world has been launched, personalized and adapted to reality. It has emerged and started to govern almost all daily activities due to the five key elements that are foundations of the technology: machine to machine (M2M), internet of things (IoT), big data, machine learning and artificial intelligence (AI). Competitive innovations are now on the market, helping with the connection between investors and borrowers—notably crowdfunding and peer-to-peer lending. Blockchain technology is now enjoying great popularity. Thus, a great part of the focus of this research paper is on Elrond. The outcomes highlight the relevance of technology in digital finance.

Big Data from Management Perspective

2016 ◽  
pp. 92-106
Author(s):  
Alireza Bolhari
Keyword(s):  
Social Media ◽  
Big Data ◽  
Ethical Issues ◽  
Banking System ◽  
Mobile Sensors ◽  
Complex Data ◽  
Management Perspective ◽  
Public Sectors

Competency matters. Social media, customer transactions, mobile sensors, and feedback contents are all piled up with data. This might be unstructured and complex data in voluminous quantity, often called Big Data. However, if this Big Data is managed, it might bring competency for organizations. This chapter introduces the must-know concepts and materials for organizational managers who face Big Data. Through the chapter, Big Data is defined and its emergence over the time is reviewed. The four Vs model in Big Data literature and its link to a banking system is analyzed. The chapter concludes by making a managerial awareness concerning ethical issues in Big Data. This is of high priority in public sectors as data relies for every individual in the society.

scholarly journals Determinants of Banking System Fragility: A Regional Perspective

2013 ◽  
Author(s):  
Hans Degryse ◽  
Muhammad Ather Elahi ◽  
María Fabiana Penas
Keyword(s):  
Banking System ◽  
System Fragility ◽  
Regional Perspective

scholarly journals Framework to predict NPA/Willful defaults in corporate loans: a big data approach

2019 ◽  
Vol 9 (5) ◽  
pp. 3786
Author(s):  
Girija Attigeri ◽  
Manohara Pai M M ◽  
Radhika M Pai
Keyword(s):  
Big Data ◽  
Banking System ◽  
Synthetic Data ◽  
Significant Rise ◽  
Classification Model ◽  
Critical Parameters ◽  
Financial Health ◽  
Data Platform ◽  
Systematic Identification

Growth and development of the economy is dependent on the banking system. Bad loans which are Non-Performing Assets (NPA) are the measure for assessing the financial health of the bank. It is very important to control NPA as it affects the profitability, and deteriorates the quality of assets of the bank. It is observed that there is a significant rise in the number of willful defaulters. Hence systematic identification, awareness and assessment of parameters is essential for early prediction of willful default behavior. The main objective of the paper is to identify exhaustive list of parameters essential for predicting whether the loan will become NPA and thereby willful default. This process includes understanding of existing system to check NPAs and identifying the critical parameters. Also propose a framework for NPA/Willful default identification. The framework classifies the data comprising of structured and unstructured parameters as NPA/Willful default or not. In order to select the best classification model in the framework an experimentation is conducted on loan dataset on big data platform. Since the loan data is structured, unstructured component is incorporated by generating synthetic data. The results indicate that neural network model gives best accuracy and hence considered in the framework.

Big Data From Management Perspective

Web Services ◽  
2019 ◽  
pp. 2060-2074
Author(s):  
Alireza Bolhari
Keyword(s):  
Social Media ◽  
Big Data ◽  
Ethical Issues ◽  
Banking System ◽  
Mobile Sensors ◽  
Complex Data ◽  
Management Perspective ◽  
Public Sectors

Competency matters. Social media, customer transactions, mobile sensors, and feedback contents are all piled up with data. This might be unstructured and complex data in voluminous quantity, often called Big Data. However, if this Big Data is managed, it might bring competency for organizations. This chapter introduces the must-know concepts and materials for organizational managers who face Big Data. Through the chapter, Big Data is defined and its emergence over the time is reviewed. The four Vs model in Big Data literature and its link to a banking system is analyzed. The chapter concludes by making a managerial awareness concerning ethical issues in Big Data. This is of high priority in public sectors as data relies for every individual in the society.

Monitoring banking system connectedness with big data

2019 ◽  
Vol 212 (1) ◽  
pp. 203-220 ◽  
Author(s):  
Galina Hale ◽  
Jose A. Lopez
Keyword(s):  
Big Data ◽  
Banking System
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