this paper presents a comprehensive review of the works done, during the 2000–2012, in the application of data mining techniques in credit scoring. yet there isn’t any literature in the field of data mining applications in credit scoring. using a novel research approach, this paper investigates academic and systematic literature review and includes all of the journals in the science direct onli...

the study was designed to analyze credit receipt and enterprise performance by small scale agro based enterprises in the niger delta region of nigeria. a multistage sampling technique was adopted in selecting 264 agro based enterprises and 96 agro based enterprises that accessed informal and formal credit respectively. the heckman model was used to examine the factors affecting amount of inform...

the issuing of credit cards by banks and other financial and credit institutions is a new experience in iran. the compatibility of credit cards with islamic rules and islamic banking and establishment of a legal structure for maintaining security for such cards, avoiding frauds and settling relating disputes is one of the most challenging issues of the iranian legislation. as the issuance and u...

Kevin L. Kliesen is an economist and John A. Tatom is an assistant vice president at the Federal Reserve Bank of St. Louis. James P. Kelley provided research assistance. This article was written while Tatom was a visiting economist at the Austrian National Bank Tatom received useful comments in seminars on this paper at the Bank of the Netherlands, the Swiss National Bank and the institute of A...

expert systems can help to build banks customers' credit scoring models. here, selection of key features of the credit scoring is important. also, it is possible to express the features values as fuzzy. the problem is how to improve features selection by genetic algorithm, in way that these features can be employed as input in fuzzy expert system. this paper presents a hybrid credit scorin...

the study was designed to investigate the comparative analysis of agricultural credit users and non-users among cassava farmers in ohafia local government area of abia state. a sample of 50 credit users and 50 non-credit user cassava-based farmers were selected by multistage random sampling technique. data were collected with a well structured questionnaire administered to a total of 100 random...

This study is on the determinants of credit access by small scale farmers in Dekina Local Government Area of Kogi State, Nigeria. The specific objectives are to; identify the major source of credit among the small scale farmers; estimate the determinants of farmers’ access to formal credit; compare the farm income of farmers who have access to formal credit and those who have not and identify c...

nowadays, credit risk is recognized as one of the most important bankruptcy factors of banks and financial institutions. in order to manage and control this risk, design of credit rating models is undeniable necessity. credit rating is used to identify the probability of credit default and on the other side classify the customers into two groups: good and bad accounts. until now, various statis...

potential growth of dairy sector is highest and more reliable compared to crop sector, indicating that dairy sector can play vital role to increase income among farmers in rural areas than crop sector in sri lanka. credit and farmer training in management ability have been major concerns of dairy development efforts. therefore, this study wasconductedto assess the impact of credit and farmer tr...

We describe initial experiments using meta-learning techniques to learn models of fraudulent credit card transactions. Our experiments reported here are the first step towards a better understanding of the advantages and limitations of current meta-learning strategies on real-world data. We argue that, for the fraud detection domain, fraud catching rate (True Positive rate) and false alarm rate...