How to Study the Monotonicity and Stability of Variables in a Scoring Model using Python

# Plain English Summary If your company uses AI to score risk (like deciding loan approvals), you need to check that your scoring system actually makes sense—that higher scores consistently mean higher risk, not random results. This article explains how to test whether your risk factors are reliable and stay consistent over time, which matters because a broken scoring system can lead to unfair or costly decisions. The technical how-to uses Python, but the core idea is simple: validate that your model's logic holds up before you rely on it.