Credit risk prediction with Azure Machine Learning

Credit risk analysis is important to financial institutions that provide loans to businesses and individuals. Credit loans and finances have risk of being defaulted or delinquent. To understand risk levels of credit users, credit providers normally collect vast amount of information on borrowers. Statistical predictive analytic techniques can be used to analyze and determine risk levels involved on credits, and approve or reject credit applications accordingly.

My workshop at Directions EMEA 2017 (Credit Risk Prediction with Azure Machine Learning) demonstrates how to perform cost-sensitive binary classification in Azure Machine Learning to predict credit risk based on the information given on a credit application built in a Dynamics 365 solution.


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