Loan ChargeOff Prediction with SQL Server

By for June 29, 2017

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This solution demonstrates how to build and deploy a machine learning model with SQL Server 2017 with R Services to predict if a Bank loan will need to be charged off within next 3 months
> **Note:** You can read more about this solution and deployment guides in the [Loan Chargeoff solution]( published on GitHub. > **Required preliminary agreement:** You need to accept the Terms of Use for the Data Science Virtual Machine on your Azure Subscription before you deploy this VM the first time. Click [here]( to agree to these terms. ## Overview There are multiple benefits for lending institutions to equip with loan chargeoff prediction data. Charging off a loan is the last resort that the bank will do on a severely delinquent loan, with the prediction data at hand, the loan officer could offer personalized incentives like lower interest rate or longer repayment period to help customers to keep making loan payments and thus prevent the loan of getting charged off. To get to this type of prediction data, often credit unions or banks manually handcraft the data based on customers' past payment history and performed simple statistical regression analysis. This method is highly subject to data compilation error and not statistically sound. This solution template demonstrates a solution end to end to run predictive analytics on loan data and produce scoring on chargeoff probability. A PowerBI report will also walk through the analysis and trend of credit loans and prediction of chargeoff probability. Read more about this solution, including step-by-step instructions on how to deploy it, at the [Loan ChargeOff Prediction Website]( ## Pricing Your Azure subscription used for the deployment will incur consumption charges on the services used in this solution, approximately $2.06(USD)/hour for the default VM. >Please ensure that you stop your VM instance when not actively using the solution. Running the VM will incur higher costs. > >**Please delete the solution if you are not using it.** ## Disclaimer ©2017 Microsoft Corporation. All rights reserved. This information is provided "as-is" and may change without notice. Microsoft makes no warranties, express or implied, with respect to the information provided here. Third party data was used to generate the Solution. You are responsible for respecting the rights of others, including procuring and complying with relevant licenses in order to create similar datasets.