Analyzing the efficiency of markets is essential for both business managers and policymakers. On the one hand, private companies need to be as efficient as possible, given that their competitiveness and their chance of survival depend on it. On the other hand, public businesses claim to be committed to investing public funds in the best way. To be competitive, firms need to improve their performance by incorporating the benchmark practices of their field in their management, and studying efficiency levels may help identify potential areas for development. However, does the efficiency score depend on the method chosen to calculate it? In this paper, our aim is to compare the rate of agreement between two different approaches to measure efficiency, the parametric and the non-parametric. For the parametric procedure, we use stochastic frontier analysis (SFA), while in the case of the non-parametric, we use data envelopment analysis (DEA) and the dynamic approach of the DEA, the window DEA. To do so, we analyze 923 non-life (property/casualty) US insurance companies in the period 2007–2011. According to our results, comparable efficiency scores are found using SFA and DEA methodologies. More importantly, the two approaches rank companies in a similar order, mostly agreeing on which are the most and the least efficient firms. Therefore, we support that the approaches can be used complementarily.