What drives reputational risk? Evidence from textual risk disclosures in financial statements

Abstract The drivers of reputational risk are still far from explicit, making proactive management and quantitative research rather difficult. Basel Committee on Banking Supervision encourages financial institutions to systematically identify drivers; however, such represent an unsolved problem. Therefore, the objective this paper is systemically textual disclosures in reports. We find that reports contain abundant information about causes risk, thus indicating possibility identifying drivers. To accurately extract massive unstructured disclosure data, we modify a text mining method make it more suitable for type data with noise words. Based 352,326 headings extracted 11,921 annual released by 1570 U.S. 2006 2019, total 13 identified extend upon existing studies. importance their dynamic evolutions also quantified discover greatest concern. This can clarify sources help companies realize provide theoretical basis further studies, especially measurement risk.