Credit Risk Assessment for an Islamic Bank in Bosnia and Herzegovina
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Assessing creditworthiness of a company using financial data analysis is one of the most important elements of an overall credit risk estimate. The Basel II and III rules have precisely defined, among other rules, risk management tools, minimal capital requirements as well as higher level of financial discipline. Similar rules exist in the USA as well. Still, there are many differences in commercial banking implementations of credit risk assessment, whereas all methods strive to predict default probability more precisely. In that sense, clients’ financial data over time are analyzed by the banks in order to make credit decision. In this paper, we present some introductory results in Islamic bank credit risk assessment where an Islamic bank data are taken from a case of diminishing musharakah. Financial ratios as hard banking data were used for evaluation of Islamic bank client credit risk level. The aim of the paper is to develop credit risk model for company clients in order to predict probability of default (PD). The dataset used in this paper consisted of 151 small and medium companies that are clients of one Islamic bank in Bosnia and Herzegovina (B&H) for 2012 and 2013. Logistic regression (LR) is used for model development. Islamic banks due to their profit–loss sharing (PLS) have additional need for assessing probability of successful client financing, or joint investment. Up until 2008 and big worldwide financial credit crisis, Islamic banks relied only on expert opinions in credit decisions instead of more sophisticated mathematical and statistical methods. As globalization is taking hold and due to Islamic financing worldwide growth there is a need for better creditworthiness predictions and better tools for Islamic banks.
KeywordsHard data Probabilistic models Credit risk Default risk Islamic banking
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