A financial fraud detection indicator for investors: an IDeA

Philippe Bernard (), Najat El Mekkaoui () and Bertrand B. Maillet ()
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Philippe Bernard: LEDa (Université Paris-Dauphine, PSL University)
Bertrand B. Maillet: CEFRA (emlyon business school), CEMOI (University of La Reunion) and Variances

Annals of Operations Research, 2022, vol. 313, issue 2, No 10, 809-832

Abstract: Abstract Fraud detection is a key issue for investors and financial authorities. The Ponzi scheme organized by Bernard Madoff is a magnified example of a financial fraud, always possible when well-orchestrated. Traditional methods to detect fraud require costly and lengthy investigations that involve complex financial and legal knowledge, as well as highly skilled analysts. Based on the motto “too good to be true” that should be adopted by any rational investor, we propose herein the use of a robust performance measure (named GUN*) to construct an Index for detection of anomalies (called IDeA). This index is based on the basic intuition that it is not possible to properly evaluate a fund as “good” regardless the characteristics and risk aversion of investors. After defining the intuition behind such an index and its economic theoretical background, we illustrate our innovative operations research methodology for fraud detection and demonstrate its usefulness studying the emblematic case of the fraud by Madoff.

Keywords: Performance measurement; Fraud detection; Robust statistics; Hedge funds (search for similar items in EconPapers)
Date: 2022
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DOI: 10.1007/s10479-019-03360-6

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