الفهرس 
Title : A multi-criteria approach for banking loans approval decisions
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Abstract
This thesis propose an approach for approving the credit loans at banks using multi criteria decision making methods and apply the neural networks to find the importance of each criteria. A literature review about the MCDM and the intersection between MCDM and Artificial intelligent techniques.This review cover the main scientific research achievements at these fields starting from year 1772. An explanation of banking industry has been conducted include the credit functions, types of risk, information needed for managing the credit and bank loan life cycle.10 methods of MCDM have been discussed. Neural networks have been revisited and descried. A case study for approving loan on bank has been descried include data clearing and normalized and finding relative importance of variables.The main achievement of his thesis as flowing:Applying MCDM techniques on Loan Approval Decision.Suggesting an Approach for Banking Loans Approval Decisions. This thesis proposed to use AHP approach for having Banking Loans Approval Decisions and we proposed the flowing criteria: 1-Risk level with relative Importance equal 0.817 2-Bank branch with relative importance equal 0.124 3-Credit product with relative importance equal 0.053 4-Age of customer with relative importance equal 0.006 We used Neural Network method and GMDH technique to get the relative importance of each variable