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Can you spot a scam? Measuring and improving scam identification ability

Author

Listed:
  • Elif Kubilay

    (University of Essex, IZA - Forschungsinstitut zur Zukunft der Arbeit - Institute of Labor Economics)

  • Eva Raiber

    (AMSE - Aix-Marseille Sciences Economiques - EHESS - École des hautes études en sciences sociales - AMU - Aix Marseille Université - ECM - École Centrale de Marseille - CNRS - Centre National de la Recherche Scientifique, CEPR - Center for Economic Policy Research)

  • Lisa Spantig

    (UKA - Universitätsklinikum RWTH Aachen - University Hospital Aachen [Aachen, Germany] - RWTH Aachen - RWTH Aachen University = Rheinisch-Westfälische Technische Hochschule Aachen, University of Essex)

  • Jana Cahlíková

    (Universität Bonn = University of Bonn)

  • Lucy Kaaria

    (UoN - University of Nairobi)

Abstract

The expansion of digital financial services leads to severe consumer protection issues such as fraud and scams. As these potentially decrease trust in digital services, especially in developing countries, avoiding victimization has become an important policy objective. In an online experiment, we first investigate how well individuals in Kenya identify phone scams using a novel measure of scam identification ability. We then test the effectiveness of scam education, a commonly used approach by organizations for fraud prevention. We find that common tips on how to spot scams do not significantly improve individuals' scam identification ability, i.e., the distinction between scams and genuine messages. This null effect is driven by an increase in correctly identified scams and a decrease in correctly identified genuine messages, indicating overcaution. Additionally, we find suggestive evidence that genuine messages with scam-like features are misclassified more often, highlighting the importance of a careful design of official communication.

Suggested Citation

  • Elif Kubilay & Eva Raiber & Lisa Spantig & Jana Cahlíková & Lucy Kaaria, 2023. "Can you spot a scam? Measuring and improving scam identification ability," Post-Print hal-04168396, HAL.
    • Handle: RePEc:hal:journl:hal-04168396
    DOI: 10.1016/j.jdeveco.2023.103147
    Note: View the original document on HAL open archive server: https://amu.hal.science/hal-04168396v1
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    Cited by:

    1. Elif Kubilay & Eva Raiber & Lisa Spantig & Jana Cahlíková & Lucy Kaaria, 2023. "Financial fraud in developing countries: Common scam detection tips do not help distinguish scam from non-scam messages," ECONtribute Policy Brief Series 056, University of Bonn and University of Cologne, Germany.
    2. Michael King & Daniel Putman & Shane Byrne & Chaning Jang, 2024. "Navigating the Rise in Non-Institutional Digital Fraud: An Experiment with Micro Enterprises in Nigeria," Trinity Economics Papers tep1124, Trinity College Dublin, Department of Economics, revised Jan 2025.

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    More about this item

    Keywords

    Consumer protection; consumer fraud; digital financial services; scam susceptibility; scam education; Kenya;
    All these keywords.

    JEL classification:

    • D14 - Microeconomics - - Household Behavior - - - Household Saving; Personal Finance
    • D18 - Microeconomics - - Household Behavior - - - Consumer Protection
    • G53 - Financial Economics - - Household Finance - - - Financial Literacy
    • O12 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - Microeconomic Analyses of Economic Development

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