From innovation to stability: Evaluating the ripple influence of digital payment systems and capital adequacy ratio on a bank’s Z-score

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This study investigated the influence of digital payment systems on banks’ stability by exploring their effect on the Z-score of the Jordanian banking sector during the period from 2004 until 2022. It specifically focused on liquidity risks generated from e-payment transactions and how sufficient capital adequacy ratios enhance banking sector stability over both short-term and long-term periods by standing against sudden volatilities yielded from large amounts of transactions executed through digital payment systems. To achieve this objective, the study utilizes time series dual regression analyses of vector autoregression and vector error correction models on E-views 12 to cover the time variation influences of digital payment on the banking sector Z-score. The regression results indicate varied effects between the benefits and risks of digital payment systems on a bank’s Z-score that influence the immediate sector’s stability, indicating that while digital payment systems can initially hold liquidity risks, leading to short-term instability; the strategic implementation of robust capital adequacy ratio stands as a protective buffer by fostering long-term banking sector resilience. The results also suggest future predictions and insights for financial sector legislators and regulators emphasizing the need for monitoring strategies that stimulate continuous innovations in the digital payment infrastructure while constantly ensuring the stability and resilience of the banking sector. Thus, prudent liquidity management and the reinforcement of capital buffers are encouraged to pilot the dual challenges and opportunities that appeared at the stages of the digital payment process, ultimately guiding the sector toward continuous growth and sustainability.

Acknowledgment
The author is grateful to the Middle East University, Amman, Jordan for the financial support granted to cover the publication fee of this research.

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    • Figure 1. Evolution of profitability indicators in the banking sector (2000–2022)
    • Figure 2. ADF test result
    • Table 1. Research metrics
    • Table 2. Summary statistics
    • Table 3. Correlation matrix
    • Table 4. ADF test results
    • Table 5. Engle-Granger two-step method results
    • Table 6. VAR regression analysis results
    • Table 7. VECM regression analysis results
    • Conceptualization
      Jamileh Ali Mustafa
    • Data curation
      Jamileh Ali Mustafa
    • Formal Analysis
      Jamileh Ali Mustafa
    • Funding acquisition
      Jamileh Ali Mustafa
    • Investigation
      Jamileh Ali Mustafa
    • Methodology
      Jamileh Ali Mustafa
    • Project administration
      Jamileh Ali Mustafa
    • Resources
      Jamileh Ali Mustafa
    • Software
      Jamileh Ali Mustafa
    • Supervision
      Jamileh Ali Mustafa
    • Validation
      Jamileh Ali Mustafa
    • Visualization
      Jamileh Ali Mustafa
    • Writing – original draft
      Jamileh Ali Mustafa
    • Writing – review & editing
      Jamileh Ali Mustafa
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Banks and Bank Systems
Banks and Bank Systems