Description:
In this paper, we investigate the impact of Wells Fargo’s 2016 "Cross-Selling" scandal by using publiclyavailable Consumer Financial Protection Bureau (CFPB) complaint data and farm level risk andsentiment scores. We use natural language processing (NLP) to construct negative sentiment scores(NSS) based on the complaint texts, and employ the synthetic control method (SCM) to estimate howthe sentiment score changed as a result of the scandal. We find that, contrary to popular belief, negativesentiment towardsWells Fargo (WF) decreased following the crisis. The result is also statisticallysignificant and robust to alternative specifications. The findings suggest that effective internal practicesaimed at improving customer satisfaction could help with more than just minimizing the negativeeffects of business scandals