Artificial Intelligence–Driven Financial Risk Assessment and Investment Decision Support Systems in Modern Banking
Keywords:
Artificial Intelligence, Financial Risk Assessment, Investment Decision Support Systems, Banking, Machine Learning, Predictive Analytics, FinTechAbstract
Artificial Intelligence (AI) has emerged as a revolutionary technology in the banking and financial services sector, enabling organizations to enhance operational efficiency, risk management, and investment decision-making processes. Modern financial institutions increasingly utilize AI-driven techniques such as machine learning, predictive analytics, and data mining to assess financial risks, detect fraudulent activities, evaluate customer creditworthiness, and optimize investment strategies. This study explores the applications of AI in financial risk assessment and investment decision support systems within the banking industry. The research examines how AI-based models improve the accuracy and speed of financial analysis by processing large volumes of structured and unstructured data. Furthermore, the study discusses the benefits of AI adoption, including enhanced decision-making, reduced operational risks, improved customer services, and cost efficiency. It also highlights key challenges such as data privacy concerns, algorithmic bias, regulatory compliance, and implementation costs. The findings indicate that AI-driven systems significantly contribute to more reliable risk assessment and informed investment decisions, thereby strengthening the competitiveness and sustainability of modern banks. The study concludes that the continued integration of AI technologies will play a crucial role in shaping the future of intelligent banking and financial management
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