In the fast growing economy, the role of credit plays a very significant role. Most of the financial institutions offer credit to their customers who are in need to meet their personal requirements and as to pay it back within specific period. Any institution which provides the credit service will predict the credit risk towards an individual which highlights the capability of the person to pay back the amount along with their previous available pay back records. Many predictive models were developed to predict the credit risk with many different variables. In the present work, the different credit risk predictive models were evaluated and compared based on the quality of decision making. The primary data were collected from 151 respondents through various online sources with the structured questionnaire and the secondary data from the previous records. The metrics derived from the predictions reveal high accuracy and precision. From the analysis, the prediction accuracy and time for the linear SVM technique was better than all other methods. .
CITATION STYLE
Bhuvaneswari, U., & Sophia, S. (2019). A predictive analysis of credit risk evaluation and the quality decision making using different predictive models. International Journal of Recent Technology and Engineering, 8(1), 1965–1969.
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