AI-Powered Analysis of Global Government Accounting Systems: Comparing Accrual and Cash-Based Methods for Enhancing Fiscal Transparency and Accountability Worldwide
Fiscal transparency is necessary to enhance the government institutions’ accountability and public confidence. This paper explores empirically the impact of accrual and cash accounting systems on the fiscal transparency of local governments worldwide. A vast dataset of publicly available financial data from Kaggle, IMF, World Bank BOOST, OECD, and IPSASB was constructed for jurisdictions that have at least five consecutive years of finance reports. A composite Fiscal Transparency Index was built by normalizing and weighting different indicators such as timeliness of reporting, disclosure of contingent liabilities, reconciliation practices, and IPSAS compliance, through Python-based algorithms for data preprocessing and scoring. The study differentiates governments based on cash-based and accrual-based governments, and then applies descriptive statistics, hypothesis testing, and panel regression analysis using Python libraries like Pandas, NumPy, SciPy, and StatsModels to analyze the statistical significance of the fiscal transparency accounting systems. The control variables were population, GDP per capita, audit quality, and governance index. The regression analysis revealed a statistically significant positive association between elevated FTI scores and accrual accounting. Sensitivity analyses with lagged fiscal years and alternative measures of transparency confirmed the robustness of the results. Triangulation with IMF and World Bank country reports and expert interviews also corroborated the empirical results. This research employs AI-driven algorithms to pre-process financial data, automatically normalize and weigh transparency indicators, and make predictions of fiscal transparency outcomes through machine learning models. The study concludes with policy recommendations favoring greater utilization of accrual accounting methods for improved transparency and people’s confidence.
Keywords: Fiscal Transparency, Accrual Accounting, Artificial Intelligence, Cash-Based Accounting, Public Financial Management, Comparative Analysis
