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2020 Conference

del 18 al 20 de May del 2020

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A1b Are CFP® Professionals Less Likely to Engage in Misconduct? Exploring the Importance of Job Classification When Comparing Misconduct Rate Among Financial Service Professionals

martes, el 19 de mayo de 2020 a las 16:15–17:30 CDT
Room 1
Key Words

Financial advisors, misconduct, FINRA, SEC

Short Description

Researchers have increasingly relied on regulatory data to analyze financial advisor misconduct. While these data are promising for the purposes of better understanding how regulators can best protect consumers, little is known about how data limitations may systematically bias the results of such analyses. Using a dataset of FINRA-licensed individuals that was enriched to include variables not present in the publicly-available FINRA data, a series of binary logistic regressions are used to illustrate how unobserved differences may bias misconduct analyses. When using CFP® status as the sole predictor of misconduct, CFP® professionals are found to be 86% percent more likely to have engaged in culpable advisory-related misconduct compared to non-CFP® professionals. However, we present evidence that this relationship is spurious. After controlling for other factors and using the enriched data to limit the analysis to only those solely working as financial advisors, CFP® professionals are found to be 20% less likely to have engaged in culpable advisory-related misconduct. Because job classifications are generally not available in the standard SEC and FINRA datasets, these findings illustrate how the inability to control for job classifications (or other unobserved differences) may bias misconduct analyses relying solely on regulatory data.

First & Corresponding Author

Derek Tharp, University of Southern Maine
Authors in the order to be printed

Derek Tharp, Steven Lee, Jeffrey Camarda, Pieter de Jong

Additional Authors

Steven Lee, The American College of Financial Services
Jeff Camarda, Camarda Wealth Advisory Group
Pieter de Jong, University of Northern Florida
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