Credit risk management for the Jordanian commercial banks: A business intelligence approach
Sep 20, 2012
DOI:
Published in: Australian Journal of Basic and Applied Sciences
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
Other Researches
The internet played a heroic role in the information revolution by bringing with it a greater scope of change, not only technologically, but societally as well. Convergence of computers and communications and what they do with information has change...
Predicting energy Consumption using artificial neural networks: a case study of the UAE
Predicting energy consumption is very important for improving resource planning and for more efficient production. This study uses artificial neural network (ANN) models to predict energy consumption in the United Arab Emirates (UAE). The multilayer...
Generational Diversity and Work Values
Work values are a significant factor that impacts employees’ job satisfaction and their commitment to work. Understanding generational diversity among employees and using the right strategy to manage them are important for organizational success. Di...
Loan decision models for the Jordanian commercial banks
Credit risk remains the most critical challenge facing bank’s management as it adversely affects the profitability and stability of the bank. However, despite the rise in loan delinquency and the serious competition in the banking market, loan appli...
Big Data: Unleashing The Match Between Quality and Quantity
The quantity and complexity of data in business activities are growing exponentially. The advancement of technology, low-cost hardware and storage devices, and extensive use of the Internet and online applications pushed the projected size of the co...
Credit risk assessment model for Jordanian commercial banks: neural scoring approach
Despite the increase in the number of non-performing loans and competition in the banking market, most of the Jordanian commercial banks are reluctant to use data mining tools to support credit decisions. Artificial neural networks represent a new f...
Using data mining for an intelligent marketing campaign
Recently, as the population of customers is becoming global, the growing competitive pressure has forced the marketing industry to use different strategies in order to create valuable customers and serve them profitably. Through scrutinizing custome...
Neuro-based artificial intelligence model for loan decisions
Problem statement: Despite the increase in consumer loans defaults and competition in the banking market, most of the Jordanian commercial banks are reluctant to use artificial intelligence software systems for supporting loan decisions. Approach: T...
Applying neural networks for loan decisions in the Jordanian commercial banking system
Artificial Neural Networks play an increasingly important role in financial applications for such tasks as pattern recognition, classification, and time series forecasting. This study develops a proposed model that identifies artificial neural netwo...
Neural networks in bank insolvency prediction
he current paper aims to predict bank insolvency before the bankruptcy using neural networks, to enable all parties to take remedial action. Artificial neural networks are widely used in finance and insurance problems. Artificial neural networks are...