We calculate the incidence of misconduct among financial advisers at the firm, county, and state level as calculated in Egan, Matvos, and Seru (2017). We compute the average incidence of misconduct among all active financial advisers (“registered representatives”) registered with the Financial Industry Regulatory Authority (FINRA).
Data on individual advisers and misconduct are from FINRA’s BrokerCheck website.
Further details on data set construction are available in Egan, Matvos, and Seru (2017).
Definition of Misconduct
We calculate the incidence of misconduct among financial advisers based on public disclosure data. FINRA requires that “all individuals registered to sell securities or provide investment advice are required to disclose customer complaints and arbitrations, regulatory actions, employment terminations, bankruptcy filings, and criminal or judicial proceedings.” FINRA reports the disclosures on each adviser’s record through BrokerCheck.
Disclosures are categorized into twenty-three different categories. Not all disclosures are indicative of wrongdoing. We classify the following six disclosures as being indicative of misconduct:
- Customer Dispute-Settled
- Regulatory-Final
- Employment Separation After Allegations
- Customer Dispute – Award/Judgment
- Criminal – Final Disposition
- Civil-Final
In other words, we restrict our attention to those disputes and regulatory events that were resolved against the adviser.
Summary Statistics
We calculate the incidence of misconduct at the firm, county and state level. In addition reporting each adviser’s disclosure history, regulators report the firm and location each adviser operates in.
For each firm, county, and state we compute the percentage of financial advisers operating in the firm/location that have one or more misconduct disclosures on his/her record over the sample period.
Gender Data
The BrokerCheck data set does not provide information on the gender of the financial adviser. We use data from GenderChecker to match the gender of each adviser based on the first name of the adviser. GenderChecker uses data from the UK Census in conjunction with other proprietary data sources to match the first names of individuals to gender. GenderChecker takes a conservative approach to assigning genders from names. If a name appears in the census (or one of GenderChecker’s other data sources) as both male and female even once, the name is classified as being unisex. We assign a specific gender to just over 80% of the advisers in our database.