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Looking at ‘Crying Wolf’ from a Different Perspective: An Attempt at Detecting Banks Under- and Over-Reporting of Suspicious Transactions

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  • Mario Gara

    (Bank of Italy)

  • Claudio Pauselli

    (Bank of Italy)

Abstract

This study aims to assess banks’ compliance in reporting suspicious transactions. It does so by estimating an econometric model on the suspicious transaction reports (STRs) filed by individual Italian banks from each of the provincial districts they operate in. Regressors include (1) indicators of banks’ operational activities, (2) measures of money laundering risk and (3) proxies of economic activity, all of which at local level. At an operational level, the model provides a tool that supervisory authorities can use to detect potentially under-reporting intermediaries, thus better targeting off-site controls and on-site inspections. More in general, the results provide some insights on banks’ reporting behavior at large. The main threat to the effectiveness of anti-money laundering systems is considered the asymmetry in the incentives: since sanctions apply only to omitted reports, banks have an incentive to over-report, thus potentially flooding the authorities with noise (‘crying wolf’ syndrome). Results show that the STR-filing strategies adopted by the banks being scrutinized may not necessarily give rise to this scenario.

Suggested Citation

  • Mario Gara & Claudio Pauselli, 2020. "Looking at ‘Crying Wolf’ from a Different Perspective: An Attempt at Detecting Banks Under- and Over-Reporting of Suspicious Transactions," Italian Economic Journal: A Continuation of Rivista Italiana degli Economisti and Giornale degli Economisti, Springer;Società Italiana degli Economisti (Italian Economic Association), vol. 6(2), pages 299-324, July.
  • Handle: RePEc:spr:italej:v:6:y:2020:i:2:d:10.1007_s40797-020-00122-3
    DOI: 10.1007/s40797-020-00122-3
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    References listed on IDEAS

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    1. Cameron,A. Colin & Trivedi,Pravin K., 2013. "Regression Analysis of Count Data," Cambridge Books, Cambridge University Press, number 9781107667273, September.
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    Cited by:

    1. Paolo Pinotti, 2020. "The Credibility Revolution in the Empirical Analysis of Crime," Italian Economic Journal: A Continuation of Rivista Italiana degli Economisti and Giornale degli Economisti, Springer;Società Italiana degli Economisti (Italian Economic Association), vol. 6(2), pages 207-220, July.

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    More about this item

    Keywords

    Anti-money laundering regulation; Financial crime; Count data; Negative binomial;
    All these keywords.

    JEL classification:

    • C25 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions; Probabilities
    • G21 - Financial Economics - - Financial Institutions and Services - - - Banks; Other Depository Institutions; Micro Finance Institutions; Mortgages
    • G28 - Financial Economics - - Financial Institutions and Services - - - Government Policy and Regulation
    • K23 - Law and Economics - - Regulation and Business Law - - - Regulated Industries and Administrative Law

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