Individuals facing financial difficulties often make decisions driven by emotions rather than rational analysis. EDAR, a pipeline for Emotion and Dialogue Act Recognition, is designed specifically for the debt collection process in France. By integrating EDAR into decision-making systems, debt collection outcomes could be improved. The pipeline employs Machine Learning and Deep Learning models, demonstrating that smaller models with fewer parameters can achieve high performance, offering an efficient alternative to large language models.