Author(s)

RongHua Li^*, HongFan Li

Affiliation(s)

School of Finance and Economics, Hainan Vocational University of Science and Technology, Haikou 571126, Hainan, China.

Corresponding Author

RongHua Li

ABSTRACT

Big data technology is profoundly transforming the business models and value creation methods of financial services. This paper employs a systematic literature review methodology to investigate the applications and value mechanisms of big data across key financial domains. The study identifies four primary value creation pathways: First, in credit scoring and risk management, integration of alternative data sources enhances model accuracy and extends financial access to underserved populations. Second, in fraud detection, machine learning-based real-time analytics reduce false positive rates by approximately 30% while improving detection precision. Third, personalized services enabled by multi-dimensional customer profiling generate revenue increases of 10-15% for institutions implementing data-driven strategies. Fourth, process automation and real-time decision support enhance operational efficiency, reducing costs and improving service quality. This research demonstrates that big data has become a strategic asset for financial institutions, while acknowledging ongoing challenges in data governance, model interpretability, and regulatory compliance.

KEYWORDS

Big data; Financial services; Credit scoring; Fraud detection

CITE THIS PAPER

RongHua Li, HongFan Li. Big data in financial services: a survey of applications and value creation. World Journal of Management Science.  2025, 3(4): 1-4. DOI: https://doi.org/10.61784/wms3083.

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