Adding to Padraic's great comments- rather than focusing on one number, you may also use the cumulative captured response values with different percentile thresholds to decide if the model is good enough.
Let's say you have a budget to take action for the top 5 percent of your population (send reminder sms, call from contact center etc). What would be the response rate of your model at the 5th percentile vs the overall event rate (random selection)? There might be cases where the model that has a lower ROC compared to the champion model will be performing better at the extreme percentiles. You may also compute the total loss (unpaid invoice) in the top buckets to justify the value of your model before deploying in production.
Tuba.
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