ARTIFICIAL INTELLIGENCE IN GLOBAL FINTECH: TRANSFORMING INVESTMENT STRATEGIES ACROSS BORDERS

Abstract

This study explores the revolutionary impact of AI on investment strategies on a global level, the sphere of FinTech in detail, and cross-border dynamics, in particular. The study implements sentiment analysis and machine-learning classification across panel regression using 40 countries of panel data during the period of 2021-2023 to analyse the effect AI has on curbing the impact of investment outcomes. Gradient Boosting and Random Forest algorithms are used to estimate investment fortune, and event research approach is used to assess short reactions of the market. The statistical results show that the AI sentiment scores can significantly predict investment returns (b = 0.27, p < 0.01) whereas, relative to Random Forest, Gradient Boosting achieves a better performance of 84.2 percentage. More developed markets demonstrate both the higher average returns (North America: 12.5%) and the more effective response to the AI signals which is backed by the analysis of sentiment trends and cumulative abnormal returns of 3.6 % on Day +2 after announcement. The evidence indicates that the investment tools powered by AI perform better within the digital mature and policy-aligned environment. The paper provides a refined insight into the AI in the global FinTech investing strategy and presents evidence-based conclusions which might be used by investors and policymakers.