Abstract

Abstract:
The process of assessing the risk of loans is extremely important for any bank and this is within the endeavor that aims to preserve the granted funds and avoid falling into situations of inability to pay these funds, and this importance is as well no less for the economy as a whole, as a good assessment of the risk of loans by banks will directly contribute in directing these loans correctly towards the economic projects that have the actual ability to achieve growth and continuation, and this will in turn be reflected on the economic effectiveness, especially if this economy does not contain an active financial market, but with the developments in the banking environment, the process of assessing the risk of these loans has been made more difficult, so there was a need for new models that depend on artificial intelligence that have a greater ability to keep up with all these developments, the most prominent of which was the artificial neural networks model, the most important thing that distinguishes this model from other smart models is its high ability to adapt and accommodate new variables because of its non-linearity in the way it solves problems since it has proven its efficiency in the field of assessing the risk of loans, especially in the aspect related to speed and accuracy in performance and this is in many banks in the world, as for the Algerian commercial banks, the application of this type of model is still in its early beginnings, such as this study that aims to build an artificial neural network model to assess the risk of bank loans and apply it to a sample of files related to investment loans that were granted during the period of 2015-2018, which was sent by a number of commercial agencies of the National Bank of Algeria to the Regional Directorate in the East located in Annaba, and then after that the effectiveness of using this model was compared with the traditional method adopted in this bank, as this study found that the artificial neural networks model is more effective than the method used to assess the risk of investment loans in this bank.
Key words: investment loans, Artificial intelligence, artificial neural networks, loan risk assessment.

Information

Item Type:	Thesis
Divisions:	» Laboratory of Research and Economic Studies » Faculty of Economic, Commercial and Management Sciences
ePrint ID:	2641
Date Deposited:	2021-07-14
Further Information:	Google Scholar
URI:	https://www.univ-soukahras.dz/en/publication/article/2641

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