11:30 - 12:30
This session presents two business applications of Machine Learning to finance: Credit Risk Prediction and Online Payment Fraud Detection.
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. This session presents how statistical predictive analytic techniques can be used to analyze and determine risk levels involved on credits, and approve or reject credit applications accordingly.
Fraud detection is one of the earliest industrial applications of anomaly detection and machine learning. This session introduces best practices and design guidelines for building an online payment fraud detection mechanism in Azure Machine Learning.