It is a simple line graph of percentage of events against deciles (scoring bins). The rank ordering is maintained in this example. You can check the rank ordering in the image below. It means the model predicts the highest number of events in the first decile and then goes progressively down. To see rank ordering, calculate the percentage of events (defaults) in each decile group and check the event rate should be monotonically decreasing. Score above 70 is susceptible and might be overfitting so rigorous validation is required. And there should not be more than 10 points (in absolute) difference between training and validation KS score. Ideally, it should be in first three deciles and score lies between 40 and 70. Important Note - In this case, KS is maximum at third decile and KS score is 59.1. KS = Maximum difference between Cumulative % Event and Cumulative % Non-Event The calculation of KS test is explained below. In probability of default (bank defaulters) model, it checks whether the credit risk model is able to distinguish between good and bad customers. KS Test measures to check whether model is able to separate events and non-events.
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