The top management team, comprising directors, supervisors, and executives (hereafter, DSEs), is the primary group responsible for corporate financial misconduct. By applying knowledge graph embedding (KGE) to DSE profiles, we construct a novel profiles implied fraud tendency (PIFT) that captures semantic similarity across three dimensions — (personal) basic traits, governance structure, and cross ties—from a holistic perspective. Empirical tests using Logit and binary Probit models reveal that: Higher PIFTs are associated with a greater likelihood of financial violations; Compared to single-dimension indicators, PIFT demonstrates superior predictive power. Further analyses show that: Non-independent directors play a dominant role in driving PIFT’s effectiveness; The proportion of fraudulent firms in the same industry strengthens PIFT’s impact, whereas state ownership has no significant effect on PIFT; Higher regional legal enforcement enhances the link between PIFT and fraud risk, though state ownership remains insignificant. This study establishes a new starting point for applying knowledge graph embedding in corporate finance research, following the standard empirical financial research paradigm.