Finding better machine learning model for default prediction I have two logistic regression models, model 1 and model 2. I want to find out which model is better. I'm predicting the default rate. I have compared the two models using Gini, plotted gini on month to month basis.
But I want a business metric which can help me show a monetary benefit that model 2 can give over model 1. A good metric to fascinate stakeholders and make them realize that yes model 2 will make them more money.


I want a business metric which can help me show a monetary benefit that model 2 can give over model 1. A good metric to fascinate stakeholders and make them realize that yes model 2 will make them more money.

You are doing it wrong. Your aim is not to find a metric that would make your model look good so you could sell it, but to have a metric to validate the model. You should meet with the business and find out what metric that they care about and apply it to the problem. It can either prove that the model does work for the problem, or that it doesn't. It doesn't necessarily need to give results consistent with your machine learning metric. In fact, in real-life scenarios, it is not always the case that the best-performing model is the deployed one (e.g. sometimes you may prefer a model that is more easily interpretable, easier to maintain, or has faster inference time).
