The Role of Big Data in Avoiding the Banking Default in Algeria (The Possibility of Upgrading the Preventive Centers of the Bank of Algeria as a Source of Big Data)

MOHAMED ILIFI1 and HAMZA BELGHALEM2

Senior Lecturer, Faculty of Economics, Business, and Management Sciences, University ofDjilali Bounaama, Khemis Miliana, Algeria, E-mail: This email address is being protected from spam bots, you need Javascript enabled to view it

temporary Assistant Professor, Faculty of Economics, Business, and Management Sciences, University of Djilali Bounaama, Khemis Miliana, Algeria, E-mail: This email address is being protected from spam bots, you need Javascript enabled to view it

ABSTRACT

This chapter aims to demonstrate the role of extensive data in providing the necessary information to the Algerian banks for the effective management of banking risks to achieve safety and security in the Algerian banking units and thus avoid banking stumbling. Stability and centralization of budgets created by the Algerian Bank as a large data source help Algerian banks detect banking risks and avoid banking stumbling. We have noted that these centers have all the huge data attributes, in terms of information volume, velocity, variety, and value, which helps Algerian banks to make better decisions based on the information resulting from the analysis of the huge data through these centers and thus effectively manage risk and avoid bank defaults.

15.1 INTRODUCTION

Due to the recent developments in the banking environment, the Algerian banking system has kept pace with its changes and introduced it into the competitive environment.

This has led to an increase in the severity of banking risks to this system, which led to attention to ways and methods that enable it to beat and overcome those risks. However, as banking risks intensified and diversified significantly, this made it difficult to count them due to the high sample size.

Dealing with this type changed the way the statisticians think or even the methods used in analyzing these data quickly and accurately. Furthermore, the enormous amount of data produced, processed, and made accessible to banking institutions has become a source of strength for the accurate and fastest possible identification of risks. Therefore, Algerian banks should adopt preventive centers to effectively store and analyze information, particularly after the issuance of monetary law, which helps banks avoid bank defaults.

To take note of the various aspects of this topic, we divided this chapter into three main themes:

  • Section 15.2: Theoretical framework for big data.
  • Section 15.3: Basic concepts of bank default.
  • Section 15.4: The role of preventive centers as a source of big data in avoiding the problem of banking default in Algeria.
 
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