When analyzing actuarial claims data, survival models are indispensable tools for understanding the likelihood of events occurring over time. Two of the most widely used survival models are the Kaplan-Meier estimator and the Nelson-Aalen estimator. Both methods are non-parametric, meaning they don’t require the data to follow a specific distribution, making them versatile for a variety of applications, from medical studies to insurance claims analysis. In this article, we’ll explore the differences and similarities between these two models, along with practical examples and actionable advice on how to choose the best approach for your data.