Artificial Intelligence and FinTech Innovations for Smart Commerce, Financial Management and Digital Economic Growth

Abstract

Artificial Intelligence and FinTech innovations are transforming commerce, financial services, and digital economic participation by enabling faster decisions, personalized services, secure transactions, and data-driven growth. This research proposes a Machine Learning-Based Predictive Analytics Method developed using Python to examine how AI-enabled FinTech supports smart commerce, financial management, and digital economic growth. The study integrates transaction data, customer behavior, digital payment usage, credit indicators, SME performance measures, and economic variables to predict adoption, fraud risk, financial efficiency, and growth potential. Python-based models such as XGBoost, Random Forest, Logistic Regression, and LSTM are used for prediction, evaluation, and interpretation. The proposed framework addresses gaps in earlier studies that treated AI, FinTech, e-commerce, and economic growth separately. Expected outcomes show improved prediction accuracy, better financial decision support, stronger fraud detection, and enhanced digital inclusion for businesses, customers, and policymakers. Thus, the study offers a practical pathway for inclusive and intelligent transformation across markets.