Big data-driven financial analysis: A new paradigm for strategic insights and decision-making
1 Independent Researcher, Canada.
2 Independent Researcher, Toronto, Ontario, Canada.
3 Independent Researcher, NJ, United States of America.
International Journal of Frontiers in Science and Technology Research, 2023, 04(02), 033-054.
Article DOI: 10.53294/ijfstr.2023.4.2.0060
Publication history:
Received on 08 June 2023; revised on 16 August 2023; accepted on 19 August 2023
Abstract:
Big Data has revolutionized financial analysis, offering unprecedented opportunities for strategic insights and informed decision-making. This study explores a new paradigm where Big Data-driven approaches transform traditional financial analysis into a dynamic, predictive, and strategic tool. By leveraging advanced analytics, artificial intelligence (AI), and machine learning (ML), organizations can derive actionable insights from vast, diverse datasets to enhance financial performance, risk management, and market competitiveness. The proposed framework emphasizes the integration of Big Data with financial analytics to address key challenges such as data volume, velocity, and variety. It underscores the role of predictive modeling in forecasting trends, optimizing resource allocation, and identifying market opportunities. Additionally, real-time analytics is highlighted as a critical factor in improving agility and responsiveness to changing market conditions. The study also discusses the importance of data governance and quality in ensuring accurate and reliable financial insights. Ethical considerations, including data privacy and security, are central to the framework, promoting trust and compliance in data-driven financial strategies. Advanced tools like Natural Language Processing (NLP) and sentiment analysis are examined for their role in evaluating market sentiment and consumer behavior, offering a competitive edge in decision-making. Case studies across industries illustrate the successful application of Big Data in financial analysis, including its impact on investment strategies, credit risk assessment, and fraud detection. The findings demonstrate that a Big Data-driven approach fosters innovation, enhances financial forecasting, and supports strategic decision-making processes. This paradigm shift requires organizations to build robust infrastructure, invest in skilled talent, and adopt a culture of data-driven innovation. The research concludes by emphasizing the transformative potential of Big Data in redefining financial analysis and advancing organizational success in a rapidly evolving economic landscape.
Keywords:
Machine learning; Artificial intelligence; Case studies; Natural Language Processing
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Copyright © 2023 Author(s) retain the copyright of this article. This article is published under the terms of the Creative Commons Attribution Liscense 4.0