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Automated teller machine fraud in south-west Nigeria: Victim typologies, victimisation strategies and fraud prevention

Author

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  • Tade, Oludayo
  • Adeniyi, Oluwatosin

Abstract

Extant studies have not examined the unintended consequences of automated teller machine (ATM) subscription, particularly factors making individuals susceptible to fraud. To address this gap in the literature, this study investigated ATM fraud victims in south-west Nigeria. Using the in-depth interview method, data were collected from 20 victims of ATM fraud in the states of Lagos and Oyo. The results showed that victims were young, elderly and included both males and females. Fraudsters were typically lovers, friends, relatives and sometimes the children of the victims. Card cloning, card swapping and physical attacks at ATMs were reported tactics for defrauding. Vulnerability factors included illiteracy, ill health, routine activity and time of withdrawal. As means of mitigating fraud, it was found that banks employed an assortment of strategies including, but not limited to, improvements in staff welfare, stringent penalties for culpable staff and enhanced fraud awareness through customer alerts. The paper reveals the limits of trust in cashless policy. It raises salient policy issues concerning the need for the governance of trust to engender adoption and ensure victim compensation.

Suggested Citation

  • Tade, Oludayo & Adeniyi, Oluwatosin, 2017. "Automated teller machine fraud in south-west Nigeria: Victim typologies, victimisation strategies and fraud prevention," Journal of Payments Strategy & Systems, Henry Stewart Publications, vol. 11(1), pages 86-92, March.
  • Handle: RePEc:aza:jpss00:y:2017:v:11:i:1:p:86-92
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    More about this item

    Keywords

    fraud; victimisation; cashless policy;
    All these keywords.

    JEL classification:

    • G2 - Financial Economics - - Financial Institutions and Services
    • E5 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit

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