THE IMPACT OF ARTIFICIAL INTELLIGENCE ON THE TRANSFORMATION OF THE GLOBAL FINANCIAL MARKET MODELS

The relevance of the study is determined by the need for institutionalized rethinking of financial models under the influence of artificial intelligence (AI), which radically transform the architecture of decision-making, personalization, compliance, and sustainability mechanisms in the global FinTech environment. The aim of the study is to formalize and quantify the transformative impact of AI on financial market models by building a validation framework with stratified AI metrics. Research methodology: critical analysis of the implementation of AI technologies in FinTech, econometric modelling of process transformative AI technologies, structural decomposition analysis, Unified Modelling Language (UML) modelling of a stratified framework, econometric validation of an optimized AI architecture. An optimized FinTech AI reengineering framework with a cognitively stratified architecture was formed, which provides increased explainability (+19.3%), traceability (+22.1%), RLHF-adaptability adaptability (+16.7%), and resistance (+18.5%) while reducing latency (–14.2%) and achieving Compliance Automation Ratio (CAR) = 1.0. The academic novelty of the research is the developed AI architecture with the first-ever introduced transformation metrics (Automation Index, AI-Personalization Score, XAI Index, AITCI), which formalize the levels of algorithmization, personalization, explainability, and sustainability of FinTech models. The prospects for further research include a controlled testing with empirical stratification of each AI module of the FinTech architecture for a formal assessment of cognitive adaptability, regulatory traceability, and metric resilience in the real financial cycle.