ARTIFICIAL INTELLIGENCE IN FINANCIAL DECISION MAKING: APPLICATIONS, ECONOMIC IMPLICATIONS, AND GOVERNANCE CHALLENGES

Abstract

This article presents a systematic literature review examining the applications of artificial intelligence (AI) in financial decision making, their economic implications, and associated governance challenges. Publications from 2015 to 2024 indexed in Scopus, Web of Science, SSRN, and financial industry databases were analysed. The review covers AI applications in credit risk assessment, algorithmic trading, fraud detection, regulatory compliance, and personal finance management, as well as macroeconomic effects of AI-driven financial automation, risks including algorithmic bias and systemic fragility, and regulatory frameworks for responsible AI in finance. The analysis demonstrates that AI adoption in financial services generates substantial efficiency gains — reducing credit assessment time by 60–80% and fraud detection error rates by 40–60% — while simultaneously creating novel systemic risks and equity concerns that require proactive governance responses. The implications for financial sector development in Uzbekistan are examined.