Assessment reveals regulatory concerns in digital banking, suggesting improved risk management and compliance strategies are needed.
This study employs a combination of quantitative and qualitative methodologies to conduct a deep analysis of digital banking regulation. Statistical analysis is used to evaluate numerical data on regulatory effectiveness, financial security, and consumer behavior in digital banking. A comparative analysis is conducted to evaluate Azerbaijani digital banking laws and best practices in international countries, and to identify gaps and areas for improvement. A survey study seeks primary information from banking professionals, fintech professionals, and consumers to evaluate perceptions of regulatory concerns and the impact of financial services. Linear regression (multiregression) analysis is conducted to evaluate the impact of regulatory policies and key financial performance indicators, and to conclude on the impact on financial market stability and the use of digital banking. Correlation analysis helps identify potential relationships among cybersecurity controls, regulatory compliance, and financial fraud events in digital banking. Document analysis examines legal, financial, and policy documents to understand the development and effectiveness of supervision in digital banking. SPSS software is used to process and analyze survey data, producing accurate statistics and reliable outputs.
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Lala Balajayeva (2025) studied this question.
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