Factors influencing the effectiveness of credit card fraud prevention in Indonesian issuing banks

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The increase in online credit card transactions in the digital era has caused an increase in credit card cyber incidents. This is happening globally, including in Indonesia. Thus, it will affect a bank’s reputation as well as its financial losses. Therefore, optimal fraud risk management is needed in a banking effort to prevent credit card fraud. In response, this article intended to study credit card fraud prevention by examining the relationship between digital security required for customer data security; fraud brainstorming to identify process weaknesses; and compliance management to manage regulatory compliance. The next step was to test whether the anti-fraud specialist is competent to moderate this relationship. This study used a quantitative approach. This study included 27 Indonesian card issuers. Primary sources were used to collect data for this study. The primary data were analyzed using a structural equation model (SEM). The results of the study show that digital security, fraud brainstorming, and compliance management were positively and significantly related to the prevention of credit card fraud, at a significance level of 5%, the t-statistic has a numerical value of 6.161, 5.079, and 5.98 each. Furthermore, testing the moderating effect obtained t-statistic values of 7.330, 4.161, and 7.694. Competency results obtained with positive and significant influence moderate the relationship between these factors and credit card fraud prevention. These findings have policy implications for banking and government objectives in fighting credit card fraud through implementing prevention strategies.

Acknowledgments
This research was conducted as part of the process of study completion at the Padjadjaran University, Bandung, Indonesia. We would like to express our sincere gratitude to the respondents who participated in this research.

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    • Table 1. Convergent validity test
    • Table 2. Reliability test
    • Table 3. R-square
    • Table 4. Estimates based on the structural model
    • Table A1. Variable description of Digital Security
    • Table A2. Variable description of Compliance Management
    • Table A3. Variable description of Fraud Brainstorming
    • Table A4. Variable description of Competence
    • Conceptualization
      Yuli Dewi, Harry Suharman, Poppy Sofia Koeswayo, Nanny Dewi Tanzil
    • Data curation
      Yuli Dewi, Harry Suharman, Poppy Sofia Koeswayo, Nanny Dewi Tanzil
    • Formal Analysis
      Yuli Dewi, Harry Suharman, Poppy Sofia Koeswayo, Nanny Dewi Tanzil
    • Investigation
      Yuli Dewi, Harry Suharman, Poppy Sofia Koeswayo, Nanny Dewi Tanzil
    • Methodology
      Yuli Dewi, Harry Suharman, Poppy Sofia Koeswayo, Nanny Dewi Tanzil
    • Project administration
      Yuli Dewi, Harry Suharman, Poppy Sofia Koeswayo, Nanny Dewi Tanzil
    • Resources
      Yuli Dewi, Harry Suharman, Poppy Sofia Koeswayo, Nanny Dewi Tanzil
    • Software
      Yuli Dewi, Harry Suharman, Poppy Sofia Koeswayo, Nanny Dewi Tanzil
    • Supervision
      Yuli Dewi, Harry Suharman, Poppy Sofia Koeswayo, Nanny Dewi Tanzil
    • Validation
      Yuli Dewi, Harry Suharman, Poppy Sofia Koeswayo, Nanny Dewi Tanzil
    • Visualization
      Yuli Dewi, Harry Suharman, Poppy Sofia Koeswayo, Nanny Dewi Tanzil
    • Writing – original draft
      Yuli Dewi, Harry Suharman, Poppy Sofia Koeswayo, Nanny Dewi Tanzil
    • Writing – review & editing
      Yuli Dewi, Harry Suharman, Poppy Sofia Koeswayo, Nanny Dewi Tanzil