The Role of AI in Revolutionizing Finance Data Warehouses for Predictive Financial Modeling

Authors

  • Srinivasa Chakravarthy Seethala   Lead Developer, Buffalo, New York, USA

DOI:

https://doi.org/10.32628/IJSRSET229471

Keywords:

Artificial Intelligence (AI), payments fraud prevention, financial security, machine learning, transaction monitoring, fraud detection algorithms, digital payments, financial services, cybersecurity, risk management, real-time analytics, behavioral analysis in finance, payment systems

Abstract

In the fast-evolving financial industry, predictive modeling has emerged as an essential tool for strategic decision-making and risk assessment. Traditional data warehouses, however, often lack the agility required to support these complex, data-intensive predictive processes. With the integration of Artificial Intelligence (AI), finance data warehouses are undergoing a paradigm shift. This paper examines how AI-driven approaches are enhancing the predictive modeling capabilities of finance data warehouses, focusing on advanced data processing, machine learning algorithms, and real-time data analytics. By analyzing AI's role in this transformation, the article provides insights into how finance organizations can leverage AI-powered data warehouses to improve accuracy in predictions, streamline data handling, and accelerate decision-making processes. This work contributes to the ongoing discussion on AI's transformative potential in the financial sector, aiming to inform and guide future innovations.

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International Journal of Scientific Research in Science, Engineering and Technology

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Published

2020-07-20

Issue

Volume 7, Issue 4, July-August-2020

Section

Research Articles

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This work is licensed under a Creative Commons Attribution 4.0 International License.

How to Cite

[1]
Srinivasa Chakravarthy Seethala "The Role of AI in Revolutionizing Finance Data Warehouses for Predictive Financial Modeling" International Journal of Scientific Research in Science, Engineering and Technology (IJSRSET), Print ISSN : 2395-1990, Online ISSN : 2394-4099, Volume 7, Issue 4, pp.370-374, July-August-2020. Available at doi : https://doi.org/10.32628/IJSRSET229471