AI-Powered Financial Forecasting: Enhancing Risk Assessment and Decision-Making Through Predictive Analytics

EasyChair Preprint 14665

Abstract

The integration of Artificial Intelligence (AI) in financial forecasting has revolutionized risk assessment and decision-making processes, offering unprecedented precision and efficiency. This paper explores the application of AI-powered predictive analytics in the financial sector, focusing on its impact on enhancing risk assessment and supporting more informed decision-making. By leveraging machine learning algorithms, neural networks, and big data analytics, AI models can process vast amounts of financial data in real-time, identifying patterns, trends, and potential risks that traditional methods may overlook. These advanced predictive capabilities enable financial institutions to anticipate market fluctuations, assess credit risks, and optimize investment strategies with greater accuracy. Additionally, the adaptability of AI models allows for continuous learning and improvement, making them increasingly reliable in dynamic market conditions. However, the paper also addresses the challenges associated with AI-driven financial forecasting, including data privacy concerns, model interpretability, and the ethical implications of automated decision-making. Ultimately, this research highlights the transformative potential of AI in financial forecasting and its role in fostering a more resilient and informed financial ecosystem.

Keyphrases: Artificial Intelligence (AI), Financial Forecasting, automated decision-making, machine learning, risk assessment

@booklet{EasyChair:14665,
  author    = {Adeoye Ibrahim},
  title     = {AI-Powered Financial Forecasting: Enhancing Risk Assessment and Decision-Making Through Predictive Analytics},
  howpublished = {EasyChair Preprint 14665},
  year      = {EasyChair, 2024}}