This paper addresses mortgage origination delays using text analytics and machine learning. In collaboration with Sun West Mortgage Company, Inc., we analyzed employee communication transcripts to identify 'seed terms' associated with delayed loans. Our machine learning models, built on these terms, match the performance of state-of-the-art word embedding approaches while offering superior interpretability. These models provide mortgage firms with an effective tool for early delay detection and risk mitigation.