Risk Analysis Model in Digital Banking and Its Impact on the Investment Portfolio of Financial Institutions

Abstract

The present study aims to develop a risk analysis model in digital banking and examine its impact on the investment portfolio of financial institutions. This research is applied in nature, as it addresses a real-world issue and its findings can provide effective solutions for financial institution managers to enhance and optimize their investment portfolios. In terms of data collection methods, this study is descriptive and employs a survey-analytical approach. The statistical population includes experts, managers, and elites in the banking industry in Tehran. The sample size was determined using the sampling formula for an unlimited population and Morgan's table, resulting in a selection of 384 participants. The data collection tool was a questionnaire based on a five-point Likert scale. The collected data were analyzed using descriptive statistical indices such as mean, standard deviation, and range of variation. To examine conceptual relationships, structural equation modeling (SEM) was employed based on the partial least squares (PLS) method using SmartPLS3 software. This method was chosen due to its compatibility with specific conditions, such as non-normal data distribution and small sample sizes. The results of structural equation modeling were presented and analyzed through the software outputs. The findings of the study indicate that effective risk management associated with digital transformation has a direct impact on improving and optimizing investment portfolios. These findings can assist financial institution managers in designing sustainable strategies and mitigating risks arising from the digitalization process.