Predicting fraud by investment managers

Stephen G. Dimmock; William C. Gerken

doi:10.1016/j.jfineco.2012.01.002

Predicting fraud by investment managers

Stephen G. Dimmock, William C. Gerken

Finance and Quantitative Methods

Research output: Contribution to journal › Article › peer-review

57 Scopus citations

Abstract

We test the predictability of investment fraud using a panel of mandatory disclosures filed with the SEC. We find that disclosures related to past regulatory and legal violations, conflicts of interest, and monitoring have significant power to predict fraud. Avoiding the 5% of firms with the highest ex ante predicted fraud risk would allow an investor to avoid 29% of fraud cases and over 40% of the total dollar losses from fraud. We find no evidence that investors receive compensation for fraud risk through superior performance or lower fees. We examine the barriers to implementing fraud prediction models and suggest changes to the SEC's data access policies that could benefit investors.

Original language	English
Pages (from-to)	153-173
Number of pages	21
Journal	Journal of Financial Economics
Volume	105
Issue number	1
DOIs	https://doi.org/10.1016/j.jfineco.2012.01.002
State	Published - Jul 2012

Bibliographical note

Funding Information:
We are grateful for comments from: one anonymous referee, James Angel, Devraj Basu, Ranadeb Chaudhuri, Elroy Dimson, Will Goetzmann, Philip Hamill, Chuan-Yang Hwang, Dusan Isakov, Zoran Ivkovic, Jun-Koo Kang, Ayla Kayhan, Naveen Khanna, Clive Lennox, Jonathan Karpoff (referee), Antonio Macias, Dinah McNichols, Jay Patel, Josh Pollet, Melvyn Teo, Fan Yu, Lei Zhang, seminar participants at West Virginia University, Singapore Monetary Authority, 2010 Asian FMA, 2010 CRSP Forum, Current Topics in Securities Regulation Conference, Emerging Scholars in Banking and Finance, 2010 EFA, 2010 FMA, Fourth Singapore International Conference, One-Day Conference on Professional Asset Management, and Oklahoma Risk Management conferences. We are especially grateful to Scott Weisbenner for helpful discussions. We acknowledge the financial support of Networks Financial Institute and its award for best paper in Financial Services Regulatory Reform.

Keywords

Disclosure
Form ADV
Fraud
Investment fraud
Operational risk
SEC

ASJC Scopus subject areas

Accounting
Finance
Economics and Econometrics
Strategy and Management

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10.1016/j.jfineco.2012.01.002

Cite this

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title = "Predicting fraud by investment managers",

abstract = "We test the predictability of investment fraud using a panel of mandatory disclosures filed with the SEC. We find that disclosures related to past regulatory and legal violations, conflicts of interest, and monitoring have significant power to predict fraud. Avoiding the 5% of firms with the highest ex ante predicted fraud risk would allow an investor to avoid 29% of fraud cases and over 40% of the total dollar losses from fraud. We find no evidence that investors receive compensation for fraud risk through superior performance or lower fees. We examine the barriers to implementing fraud prediction models and suggest changes to the SEC's data access policies that could benefit investors.",

keywords = "Disclosure, Form ADV, Fraud, Investment fraud, Operational risk, SEC",

author = "Dimmock, {Stephen G.} and Gerken, {William C.}",

note = "Funding Information: We are grateful for comments from: one anonymous referee, James Angel, Devraj Basu, Ranadeb Chaudhuri, Elroy Dimson, Will Goetzmann, Philip Hamill, Chuan-Yang Hwang, Dusan Isakov, Zoran Ivkovic, Jun-Koo Kang, Ayla Kayhan, Naveen Khanna, Clive Lennox, Jonathan Karpoff (referee), Antonio Macias, Dinah McNichols, Jay Patel, Josh Pollet, Melvyn Teo, Fan Yu, Lei Zhang, seminar participants at West Virginia University, Singapore Monetary Authority, 2010 Asian FMA, 2010 CRSP Forum, Current Topics in Securities Regulation Conference, Emerging Scholars in Banking and Finance, 2010 EFA, 2010 FMA, Fourth Singapore International Conference, One-Day Conference on Professional Asset Management, and Oklahoma Risk Management conferences. We are especially grateful to Scott Weisbenner for helpful discussions. We acknowledge the financial support of Networks Financial Institute and its award for best paper in Financial Services Regulatory Reform. ",

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doi = "10.1016/j.jfineco.2012.01.002",

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N2 - We test the predictability of investment fraud using a panel of mandatory disclosures filed with the SEC. We find that disclosures related to past regulatory and legal violations, conflicts of interest, and monitoring have significant power to predict fraud. Avoiding the 5% of firms with the highest ex ante predicted fraud risk would allow an investor to avoid 29% of fraud cases and over 40% of the total dollar losses from fraud. We find no evidence that investors receive compensation for fraud risk through superior performance or lower fees. We examine the barriers to implementing fraud prediction models and suggest changes to the SEC's data access policies that could benefit investors.

AB - We test the predictability of investment fraud using a panel of mandatory disclosures filed with the SEC. We find that disclosures related to past regulatory and legal violations, conflicts of interest, and monitoring have significant power to predict fraud. Avoiding the 5% of firms with the highest ex ante predicted fraud risk would allow an investor to avoid 29% of fraud cases and over 40% of the total dollar losses from fraud. We find no evidence that investors receive compensation for fraud risk through superior performance or lower fees. We examine the barriers to implementing fraud prediction models and suggest changes to the SEC's data access policies that could benefit investors.

KW - Disclosure

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KW - Fraud

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KW - Operational risk

KW - SEC

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Predicting fraud by investment managers

Abstract

Bibliographical note

Keywords

ASJC Scopus subject areas

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