On Factors Affecting the Year-on-Year Growth of Bank Operating Revenue
DOI:
https://doi.org/10.54691/x6hapk09Keywords:
Banks; Year-on-year growth in operating revenue; Multiple linear regression; Influencing factors.Abstract
This study focuses on the influencing factors of year-on-year growth in bank operating revenue, aiming to construct a multiple linear regression model for in-depth analysis. At the theoretical level, the core viewpoints of financial intermediation theory are detailed. Traditional theory emphasizes transaction costs and information asymmetry, while modern theory extends this to risk management and participation cost functions. As a financial intermediary, the bank's credit intermediation, payment intermediation, and financial service functions significantly impact operating revenue growth. For example, credit intermediation drives revenue growth through interest rate spreads, payment intermediation through fees, and financial services through service charges. In terms of data analysis, various methods are employed. Descriptive statistical analysis calculates statistics such as the mean and median to demonstrate the distribution characteristics of each variable. Correlation analysis calculates the Pearson correlation coefficient and performs significance tests to determine the degree of linear association between variables. Based on this, a multiple linear regression model is constructed. The regression coefficients are estimated using the least squares method, and goodness-of-fit and significance tests are conducted to quantify the impact of each factor on operating revenue growth, providing a scientific basis for bank management decisions.
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