Advanced International Journal of Multidisciplinary Research

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Big Data for Predictive Financial Analytics: Moving Away from Wall Street and Into Main Street for U.S. Corporations and Small Businesses

Author(s) Md Ashraful Islam Nayem, Md.Tauhid Hossain Rubel, Syed Kamrul Hasan, Md Kamrul Islam, A K M Emran
Country United States
Abstract Finding out why big companies aren't using big data as much as smaller ones is a major goal of the study. Big companies usually have all the resources—financial, infrastructural, and technical—needed to make full use of analytics ecosystems. On the other hand, many SMEs encounter substantial challenges, such as constrained IT spending, a lack of qualified technical staff, and worries about data security and compliance. Despite all these obstacles, the study indicates that cloud-native platforms and low-code/no-code analytics tools are gradually closing the gap. This means that smaller enterprises can compete better in data-driven marketplaces, and more people can have access to advanced financial analytics.

Also, this article takes a close look at the technical, operational, ethical, legal, and regulatory aspects of using structured and unstructured financial data in real time. Specifically, the study looks at how laws like the California Consumer Privacy Act (CCPA) and the Sarbanes-Oxley Act (SOX) influence the use of predictive analytics in the public and private sectors, respectively. SOX and CCPA both impose stringent controls over financial reporting and corporate accountability. In addition to posing difficulties in terms of compliance, these legal frameworks provide chances to build confidence and honesty in financial data practices by means of open leadership and algorithmic responsibility.
Keywords Big Data, Predictive Analytics, Financial Forecasting, U.S. Corporations, Small Businesses, SOX, CCPA, Real-Time Data, Data Governance, Algorithmic Fairness
Discipline Computer > Big Data / Data Science
Published In Volume 3, Issue 5, September-October 2025
Published On 2025-09-06
DOI https://doi.org/10.62127/aijmr.2025.v03i05.1138
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