What are the most effective ways to handle missing data in credit scoring?
Missing data is a common challenge in credit scoring, especially when using AI models that rely on large and diverse datasets. How you deal with missing data can have a significant impact on the accuracy, fairness, and interpretability of your credit scoring model. In this article, you will learn about the most effective ways to handle missing data in credit scoring, based on the type, cause, and pattern of the missingness.