Enhancing Decision-Making Processes in Financial Institutions through Business Analytics Tools and Techniques

This review paper explores the transformative impact of business analytics on decision-making processes in financial institutions. It delves into the various tools and techniques employed in descriptive, predictive, and prescriptive analytics, highlighting their roles in enhancing accuracy, speed, and risk management. The paper also addresses the challenges and limitations faced in data quality, system integration, skill gaps, and regulatory and ethical concerns. Looking ahead, it identifies emerging trends such as AI, big data, and blockchain, as well as innovations like quantum computing and NLP, which promise to revolutionize the industry further. Practical recommendations for the effective implementation of business analytics are provided, emphasizing the importance of robust data infrastructure, a data-driven culture, strategic collaborations, and regulatory compliance. By adopting these best practices, financial institutions can leverage analytics to achieve superior decision-making, operational efficiency, and competitive advantage.

Authors

Publication Details

Journal
World Journal of Engineering and Technology Research
Published
2024-08-23
DOI
https://doi.org/10.53346/wjetr.2024.3.1.0051
Citations
2
Primary Topic
Big Data and Business Intelligence
Type
article
Field-Weighted Citation Impact
1.06
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article

Enhancing Decision-Making Processes in Financial Institutions through Business Analytics Tools and Techniques

Anwuli Nkemchor Obiki-Osafiele, Edith Ebele Agu, Njideka Rita Chiekezie
2 citations
World Journal of Engineering and Technology Research
Big Data and Business Intelligence
1.06
article

Enhancing Decision-Making Processes in Financial Institutions through Business Analytics Tools and Techniques

Anwuli Nkemchor Obiki-Osafiele, Edith Ebele Agu, Njideka Rita Chiekezie
article en
2 citations

Abstract

This review paper explores the transformative impact of business analytics on decision-making processes in financial institutions. It delves into the various tools and techniques employed in descriptive, predictive, and prescriptive analytics, highlighting their roles in enhancing accuracy, speed, and risk management. The paper also addresses the challenges and limitations faced in data quality, system integration, skill gaps, and regulatory and ethical concerns. Looking ahead, it identifies emerging trends such as AI, big data, and blockchain, as well as innovations like quantum computing and NLP, which promise to revolutionize the industry further. Practical recommendations for the effective implementation of business analytics are provided, emphasizing the importance of robust data infrastructure, a data-driven culture, strategic collaborations, and regulatory compliance. By adopting these best practices, financial institutions can leverage analytics to achieve superior decision-making, operational efficiency, and competitive advantage.

World Journal of Engineering and Technology ResearchVol. 3(1)
Industry, innovation and infrastructure
Openalex Percentile: Top 17%
Big Data and Business Intelligence
1.06
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