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Financial Regulation

Paper Session

Sunday, Jan. 7, 2024 8:00 AM - 10:00 AM (CST)

Marriott Rivercenter, Grand Ballroom Salon I
Hosted By: American Finance Association
  • Chair: Vikrant Vig, London Business School

Regulatory Leakage Among Financial Advisors: Evidence From FINRA Regulation of "Bad" Brokers

Colleen Honigsberg
,
Stanford University
Edwin Hu
,
New York University
Robert Jackson
,
New York University

Abstract

The regulatory framework for financial advisors is fragmented, with multiple state and federal regulators. Although prior empirical literature on financial advisors has largely focused on individuals regulated as brokers under FINRA's primary authority, we define financial advisors by function rather than by regulatory classification. This allows us to create a single database containing brokers regulated primarily by FINRA, investment advisers regulated by the SEC, investment advisers regulated primarily by state securities regulators, and insurance producers regulated by state insurance regulators. There is significant overlap across the regimes; more than 40% of the advisors in our data are registered with more than one regulator, suggesting similar job functions. As we show, this overlap has implications for regulatory discipline. For example, in 2018 and 2019, FINRA proposed rules designed to nudge ``bad'' brokers out of the industry. We show that these proposals caused thousands of high-risk brokers to exit the FINRA broker regime, but that the majority of these individuals did not leave financial services---98% are currently registered with state regulators as insurance producers. Thus, the net effect of the rule is unclear, as its primary effect was arguably to cause the targeted set of brokers to be subject to lower levels of monitoring than before.

Measuring Regulatory Complexity

Jean-edouard Colliard
,
HEC Paris
Co-Pierre Georg
,
EDHEC Business School

Abstract

Despite a heated debate on the complexity of financial regulation, a comprehensive framework to study regulatory complexity is lacking. We propose one inspired by the analysis of algorithmic complexity in computer science. We use this framework to distinguish different dimensions of complexity, classify existing measures, develop new ones, compute them on two examples—Basel I and the Dodd-Frank Act—and validate them using novel experiments. Our framework offers a quantitative approach to the policy trade-off between regulatory complexity and precision. Our toolkit is freely available and allows researchers to measure the complexity of any normative text and test alternative measures.

Pricing of Climate Risk Insurance: Regulation and Cross-Subsidies

Ishita Sen
,
Harvard University
Sangmin Oh
,
University of Chicago
Ana-maria Tenekedjieva
,
Federal Reserve Board

Abstract

We study the consequences of state-level price (rate) regulation for U.S. homeowners’ insurance, a $15 trillion market that provides households protection against climate losses. Using two distinct identification strategies and novel data on regulatory filings and ZIP code level rates, we find that insurers in more regulated states adjust rates less frequently and by a lower magnitude after experiencing losses. Importantly, they overcome these rate-setting frictions by adjusting rates in less regulated states, consistent with insurers cross-subsidizing across states. In the long-run, these behaviors lead to a decoupling of rates from risks, implying distortions in risk sharing across states.

Discussant(s)
Stefan Lewellen
,
Pennsylvania State University
Shikhar Singla
,
London Business School
Janis Skrastins
,
Washington University-St. Louis
JEL Classifications
  • G2 - Financial Institutions and Services