Classification model Fundamentals
Why Rank ordering is so important?
Read on to know more about the concept and the usage of rank ordering in classification models
I have been working with credit risk models for quite some time now and I have noticed the emphasis our stakeholders put on our classification models following rank-ordering. There is a reason for that and we will learn about that in this short post.
Rank ordering is an important measure of model performance and its ability to separate out the event from the non-events.
For the explanation purpose, we will be talking about a Probability of Default (PD) model wherein Default(event) refers to the instance in which a credit card/loan customer is not able to pay back the amount that is due even after 90 days from the date when that amount became due for the first time to be paid by them. In this case, even refers to a case of customer defaulting on their payments and non-event means a good customer who has paid on time or has nothing due.
Step 1: Scoring your dataset
Let’s assume that the methodology that we used in building this model was logistic regression. Then at the end, we would have gotten an equation looking something like…
