Impact of internal fintech on bank profitability

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This research investigates the relationship between the adoption of internal fintech solutions and the profitability of banks in Kosovo, leveraging the Technology Acceptance Model and Innovation Theory. The study analyzes the impact of mobile banking, e-banking, electronic payment systems, and data analytics on profitability using net interest margin (NIM) and return on assets (ROA) as key metrics. A mixed-method approach was adopted, combining audited financial report data from Kosovo’s commercial banks with survey data to ensure comprehensive analysis. To explore this relationship, a structured questionnaire was administered to 169 bank employees across 10 commercial banks in Kosovo. The sample included professionals from finance, technology, credit analysis, and customer service departments, chosen for their direct involvement in fintech adoption and its implementation. This selection ensured insights from individuals who actively engage with fintech tools and their impact on bank operations. Findings reveal that fintech adoption impacts profitability based on focus. Investments in operational efficiency negatively affect ROA (β = –0.079, p < 0.001), while fintech adoption targeting business opportunities, credit cost reduction, and customer understanding improves ROA and NIM. Business opportunities enhance ROA (β = 0.053, p < 0.01) and NIM (β = 0.098, p < 0.001), while customer understanding increases ROA (β = 0.143, p < 0.001). Mobile banking, digital lending, and bank age also show positive effects.

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    • Table 1. Questionary items and construct IFA
    • Table 2. Summary of variables used in the analysis of a bank’s profitability
    • Table 3. Study sample
    • Table 4. Financial technologies already adopted or being adopted by banks
    • Table 5. Cronbach’s Alpha for fintech adoption and profitability constructs
    • Table 6. Descriptive statistics for perceived usefulness of fintech adoption
    • Table 7. Multifactorial regression analysis (Model 1 and Model 2)
    • Table 8. ROA and M-banking
    • Table 9. T-test. ROA and Digital lending
    • Table 10. Principal component analysis
    • Table 11. Principal component analysis (PCA)
    • Table 12. Rotated component matrix
    • Table 13. Multifactorial regression analysis (Model 3 and Model 4)
    • Table A1. List of commercial banks in Kosovo and their characteristics
    • Table B1. Summary of existing literature in fintech and banks’ profitability
    • Formal Analysis
      Vlora Berisha
    • Methodology
      Vlora Berisha
    • Validation
      Vlora Berisha
    • Writing – original draft
      Vlora Berisha
    • Conceptualization
      Blake Rayfield
    • Project administration
      Blake Rayfield
    • Supervision
      Blake Rayfield
    • Visualization
      Blake Rayfield
    • Writing – review & editing
      Blake Rayfield