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credit risk :The credit risk is the most common  risk that the banks exposed, as it mentioned above  It is the losses resulting from inability of credit customers to fulfil their obligations. the main risk when granting a loan is that the borrowers  will not be able to fulfill their obligations towards the bank and that the bank will lose its funds ,hence, Most of their revenues are generated by credits, i.e. lending operations. Therefore Credit lending is the one of the most important profit generators for a bank( SanjaVukovic,2012). Thus it is very important to mange and asses a credit risk assessmentit is the process of assessment borrowers  to discriminate between creditworthy and non-creditworthy borrowers .   Credit risk assessment  decisions are complex and unstructured problems and it  cannot be readily solved formally(kambal,etl,  2013). And it is difficult to determined  all factors  involve in grant decision loan .There are two ways to assess credit risk the traditional way which is through human Judgmental and the automate way its is through formal evaluation methods which are called credit scoring  Judgmental systemsIn the past and Until recently the decision to grant a loan based on human  judgment and subjective decisions which were issued by loan officers using their experience to asses the risk of default (Thomas ,2000). Hence, loan granting decisions were inaccurate, more subjective and time consumingcredit scoring systems:Due to inefficiency , inaccurate traditional(judgmental ) way of assessing borrowers when they request for a loan ,we need  to automate credit risk assessment  process through formal evaluation methods which are called credit scoring  The objective of quantitative credit scoring models is to assign credit applicants to one of two groups: a `good credit a group that is likely to repay the “financial obligation, or a `bad credit a group that should be denied credit because of a high likelihood of defaulting on the “financial obligation(David West*). Therefore, credit scoring is a very typical Data Mining (DM) classification problem

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