Credit risk management and business intelligence approach of the banking sector in Jordan

Banking segment is one of the ultimate key segments that support the sustainable economic progress in Jordan. Hence, banks in Jordan are considered as tremendously significant financial establishments that pursue profit by providing various financial services to various customers through dealing wit...

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Autor principal:	Khaled Alzeaideen
Formato:	article
Lenguaje:	EN
Publicado:	Taylor & Francis Group 2019
Materias:	credit risk capital market measures of risk jordanian banks business intelligence artificial neural networks data mining knowledge assets commercial banks jordan Business HF5001-6182 Management. Industrial management HD28-70
Acceso en línea:	https://doaj.org/article/2187a45895f344378a86d7071db8a496
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spelling	oai:doaj.org-article:2187a45895f344378a86d7071db8a4962021-12-02T16:07:36ZCredit risk management and business intelligence approach of the banking sector in Jordan2331-197510.1080/23311975.2019.1675455https://doaj.org/article/2187a45895f344378a86d7071db8a4962019-01-01T00:00:00Zhttp://dx.doi.org/10.1080/23311975.2019.1675455https://doaj.org/toc/2331-1975Banking segment is one of the ultimate key segments that support the sustainable economic progress in Jordan. Hence, banks in Jordan are considered as tremendously significant financial establishments that pursue profit by providing various financial services to various customers through dealing with different kinds of risk. Therefore, loan decisions for such institutions are crucial because they can avert credit risk. However, loan sanction assessment at Jordanian banks is particularly based on credit officer’s intuition and sometimes a combination of credit officer’s judgment and traditional credit scoring models. Consequently, it is important to assess the riskiness of the banking sector in Jordan. Then again, banks kept data regarding their clienteles in data warehouses that can be looked as concealed knowledge assets that can be read and exercised via data mining tools. Artificial Neural Networks (ANN) denote a recent development of statistical techniques and promising tools of data mining and data processing. The current study attempts to develop an artificial neural network model as a decision support system to credit approval evaluation at Jordanian commercial banks based on applicant’s characteristics; the proposed model can be utilized to aid credit officers make better decisions when evaluating future loan applications. A real-world credit application of cases of both granted and rejected applications from different Jordanian banks was employed to develop the artificial neural model. The experimental outcomes showed that artificial neural networks area promising addition to the existing classification methods.Khaled AlzeaideenTaylor & Francis Grouparticlecredit riskcapital market measures of riskjordanian banksbusiness intelligenceartificial neural networksdata miningknowledge assetscommercial banksjordanBusinessHF5001-6182Management. Industrial managementHD28-70ENCogent Business & Management, Vol 6, Iss 1 (2019)
institution	DOAJ
collection	DOAJ
language	EN
topic	credit risk capital market measures of risk jordanian banks business intelligence artificial neural networks data mining knowledge assets commercial banks jordan Business HF5001-6182 Management. Industrial management HD28-70
spellingShingle	credit risk capital market measures of risk jordanian banks business intelligence artificial neural networks data mining knowledge assets commercial banks jordan Business HF5001-6182 Management. Industrial management HD28-70 Khaled Alzeaideen Credit risk management and business intelligence approach of the banking sector in Jordan
description	Banking segment is one of the ultimate key segments that support the sustainable economic progress in Jordan. Hence, banks in Jordan are considered as tremendously significant financial establishments that pursue profit by providing various financial services to various customers through dealing with different kinds of risk. Therefore, loan decisions for such institutions are crucial because they can avert credit risk. However, loan sanction assessment at Jordanian banks is particularly based on credit officer’s intuition and sometimes a combination of credit officer’s judgment and traditional credit scoring models. Consequently, it is important to assess the riskiness of the banking sector in Jordan. Then again, banks kept data regarding their clienteles in data warehouses that can be looked as concealed knowledge assets that can be read and exercised via data mining tools. Artificial Neural Networks (ANN) denote a recent development of statistical techniques and promising tools of data mining and data processing. The current study attempts to develop an artificial neural network model as a decision support system to credit approval evaluation at Jordanian commercial banks based on applicant’s characteristics; the proposed model can be utilized to aid credit officers make better decisions when evaluating future loan applications. A real-world credit application of cases of both granted and rejected applications from different Jordanian banks was employed to develop the artificial neural model. The experimental outcomes showed that artificial neural networks area promising addition to the existing classification methods.
format	article
author	Khaled Alzeaideen
author_facet	Khaled Alzeaideen
author_sort	Khaled Alzeaideen
title	Credit risk management and business intelligence approach of the banking sector in Jordan
title_short	Credit risk management and business intelligence approach of the banking sector in Jordan
title_full	Credit risk management and business intelligence approach of the banking sector in Jordan
title_fullStr	Credit risk management and business intelligence approach of the banking sector in Jordan
title_full_unstemmed	Credit risk management and business intelligence approach of the banking sector in Jordan
title_sort	credit risk management and business intelligence approach of the banking sector in jordan
publisher	Taylor & Francis Group
publishDate	2019
url	https://doaj.org/article/2187a45895f344378a86d7071db8a496
work_keys_str_mv	AT khaledalzeaideen creditriskmanagementandbusinessintelligenceapproachofthebankingsectorinjordan
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Credit risk management and business intelligence approach of the banking sector in Jordan

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