Case Study 13 – How a manager used Analytics to understand the factors which affect credit score and how.
Industry – Banking and Financial Services
We follow DCOVA and I methodology to solve the problem. To Understand this methodology, check this whitepaper –
Business Problem – The manager has data of the customers with credit score. She wants to understand the factors which affect credit score and how. She also wants to use the historical data on banks customers to predict the credit score for the new customers coming in.
The manager approaches the analytics team with the problem and shares the data and the details. The analytics team gets the data and then explores the data to treat the data for missing values, outliers and correlations. The team comes out with visualization. One of the visualization is shown below –
This chart shows the correlation amongst all the numeric variable.
The analytics team then does statistical analysis to first uses the linear regression model to come out with the equation with all the variables as to how they affect the credit score. The team then use the same equation to predict the credit score of the customers in the test data and compare the results with the existing score.
The same equation will be used to predict the “credit score” for the new customers. The team presents the report to the manager. The manager along with the team then puts the model into production so that the new customers “credit score” can be calculated.