ARTIFICIAL INTELLIGENCE IN FINANCIAL DECISION-MAKING: OPPORTUNITIES AND CHALLENGES

Abstract

Artificial Intelligence (AI) has emerged as an important technological innovation in the financial sector, transforming the way financial institutions and individuals analyse information, assess risks and make financial decisions. AI-based applications such as machine learning, predictive analytics, automated advisory systems and intelligent fraud-detection tools provide opportunities for improving the speed, accuracy and efficiency of financial decision-making. At the same time, the adoption of AI creates challenges related to data privacy, cybersecurity, algorithmic bias, lack of transparency and dependence on technology. The present study examines the opportunities and challenges associated with Artificial Intelligence in financial decision-making. The study focuses on four major dimensions: AI efficiency and accuracy, predictive capability, risk management and challenges of AI adoption, and examines their influence on the effectiveness of financial decision-making. A descriptive and analytical research design was adopted. Primary data were collected from 277 respondents using a structured questionnaire. Factor analysis was used to identify the underlying dimensions of AI adoption in financial decision-making, while Structural Equation Modelling (SEM) using AMOS was proposed to examine the relationships between AI capabilities, AI-related challenges and financial decision-making effectiveness. The findings indicate that AI capabilities have a positive influence on financial decision-making, while technological and ethical challenges can negatively affect effective AI adoption. The study recommends responsible AI implementation, stronger cybersecurity, employee training, transparent algorithms and appropriate regulatory mechanisms to maximize the benefits of AI in financial decision-making.