survival-bias

This paper systematically evaluates reject inference methods in credit scoring and identifies a failure mode where accuracy improves while recall collapses, creating an illusion of improvement while rejection quality deteriorates. It proposes a controlled exploration strategy that breaks the feedback loop and shows that even minimal exploration rates are sufficient to diagnose the problem.

This academic paper identifies and characterizes Simpson's paradox in behavioral curve modeling, demonstrating how aggregation systematically distorts parametric estimates of user dynamics due to survival bias. The authors validate this distortion across datasets like Goodreads and Amazon Electronics and propose hierarchical peak estimation methods to mitigate the issue.