An Empirical Analysis of the Impact of Robotic Process Automation and Continuous Auditing on the Timeliness And Accuracy Of Financial Reporting Assurance

Abstract

This study empirically examined the impact of Robotic Process Automation (RPA) and Continuous Auditing (CA) on the timeliness and accuracy of financial reporting assurance within digitally transformed organizations. A quantitative cross-sectional research design was employed using a structured questionnaire administered to accounting, auditing, finance, compliance, and governance professionals. A total of 450 questionnaires were distributed, 421 were returned (93.56% response rate), and after duplicate screening, missing data assessment, and response consistency evaluation, 392 valid questionnaires (87.11%) were retained for statistical analysis. Data were analyzed using SPSS 29 and SmartPLS 4 through descriptive statistics, reliability and validity assessment, Pearson correlation analysis, multiple regression analysis, and Partial Least Squares Structural Equation Modeling (PLS-SEM). Descriptive statistics indicated high organizational implementation of Robotic Process Automation (M = 4.07, SD = 0.59) and Continuous Auditing (M = 4.12, SD = 0.56), accompanied by favorable Reporting Timeliness (M = 4.10, SD = 0.53) and Reporting Accuracy (M = 4.18, SD = 0.50). The measurement model demonstrated excellent reliability, with Cronbach's alpha values ranging from 0.891 to 0.927, Composite Reliability values between 0.915 and 0.941, and Average Variance Extracted values ranging from 0.641 to 0.761. Pearson correlation analysis revealed significant positive relationships among all constructs, with the strongest correlation observed between Reporting Timeliness and Reporting Accuracy (r = 0.756, p < .001). Structural model analysis demonstrated that Robotic Process Automation significantly influenced Reporting Timeliness (β = 0.361, t = 8.02, p < .001) and Reporting Accuracy (β = 0.334, t = 7.11, p < .001), whereas Continuous Auditing exerted stronger effects on Reporting Timeliness (β = 0.421, t = 9.79, p < .001) and Reporting Accuracy (β = 0.442, t = 10.83, p < .001). The proposed model explained 70.4% of the variance in Reporting Timeliness (R² = 0.704) and 74.6% of the variance in Reporting Accuracy (R² = 0.746), while predictive relevance values (Q² = 0.486 and 0.521) confirmed strong predictive capability. Effect size analysis further indicated that Continuous Auditing produced the largest practical influence (f² = 0.366) compared with Robotic Process Automation (f² = 0.209). Overall, the findings established that the integrated implementation of Robotic Process Automation and Continuous Auditing significantly enhanced reporting efficiency, reporting reliability, governance effectiveness, and financial reporting assurance within digitally transformed organizational environments.