Credit risk management for the Jordanian commercial banks

A business intelligence approach

Hussain A. Bekhet, Shorouq Fathi Kamel Eletter

Research output: Contribution to journalArticle

3 Citations (Scopus)

Abstract

Commercial banks in Jordan are regarded as vitally important and competitive financial organizations that seek profit by providing various financial services to various customers while managing different types of risk. Credit forms a cornerstone of the banking industry as credit behavior stronglyinfluences the profitability and stability of a bank. Therefore, loan decisions for such instuitions are crucialbecause they can avert credit risk. However, loan application evaluation at Jordanian banks is subjective based oncredit officer's intuition and sometimes a combination of credit officer'sjudgment and traditional credit scoring models. On the other hand, banks store data about their customers in data warehouses which can be viewed as hidden knowledge assets that can be accessed and used through data mining tools. Artificial Neural Networks (ANN) represent a recent development of a new family 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 systemto 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 accepted and rejected applications from different Jordanian commercial banks was used to build the artificial neural model. The experimental results show that artificial neural networks area promising addition to the existing classification methods.

Original languageEnglish
Pages (from-to)188-195
Number of pages8
JournalAustralian Journal of Basic and Applied Sciences
Volume6
Issue number9
Publication statusPublished - 01 Sep 2012

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Credit
Business intelligence
Commercial banks
Credit risk management
Loans
Artificial neural network
Data mining
Evaluation
Credit risk
Banking industry
Intuition
Knowledge assets
Data warehouse
Profitability
Jordan
Decision support
Credit scoring
Profit
Network model
Financial services

All Science Journal Classification (ASJC) codes

  • General

Cite this

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Credit risk management for the Jordanian commercial banks : A business intelligence approach. / A. Bekhet, Hussain; Eletter, Shorouq Fathi Kamel.

In: Australian Journal of Basic and Applied Sciences, Vol. 6, No. 9, 01.09.2012, p. 188-195.

Research output: Contribution to journalArticle

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