OPTIMIZATION MODELS FOR TAX COMPUTATION AND PLANNING IN MULTINATIONAL ACCOUNTING PRACTICES

This study explores the role of optimization models in tax computation and planning within multinational accounting practices, aiming to enhance compliance while minimizing liabilities. The research employs a mixed-methods approach, analyzing quantitative data from multinational corporations and qualitative insights from tax professionals. Regression analysis demonstrates a strong correlation (R² = 0.85) between tax optimization and net income growth, with findings indicating that every $1 million in tax savings contributes approximately $2.5 million to net income. A Chi-square test (p-value = 0.003) reveals significant regional variations in tax compliance incidents, emphasizing the need for tailored regulatory strategies. Time series analysis forecasts a 40% increase in tax savings from 2020 to 2024, with projections exceeding $500 million by 2026. The study concludes that AI-driven tax models significantly enhance predictive accuracy and compliance efficiency, while blockchain technology improves transparency. To maximize benefits, corporations should integrate AI, invest in employee training, develop region-specific strategies, and adopt ethical tax practices.