The Transformative Role of Data Mining in Financial Analysis and Risk Management
- 1 Shenzhen CIMC Industry & City Development Group Co., Ltd.
- 2 The University of Manchester
- 3 University of Leeds
* Author to whom correspondence should be addressed.
Abstract
This paper investigates the profound impact of Data Mining in the analysis and forecasting of financial performances for listed companies. The technology of Data Mining is an interdisciplinary one, mastering the combination of computer science, statistics and artificial intelligence to extract deep and actionable insights from massive datasets. The paper's main focus is on how Data Mining contributes to the decision making in finance sector by analyzing the financial ratios and financial reports in detail, as well as predictive forecasting using deep learning models such as LSTM and GRU. Moreover, this paper is detailed with data mining's application in financial risk management strategies, especially in fraud detection. Case studies and empirical data were introduced to demonstrate the Data Mining's impact on improving the accuracy, efficiency and integrity of the analyses in financial markets. Data Mining has evidently transformed the financial analysis, making finance professionals and investors more soothsayers than fortune tellers. The conclusion emphasizes that utilizing these techniques could greatly benefit from financial strategists and investors by providing them with a more nuanced understanding of financial conditions and future trends.
Keywords
data mining, financial analysis, LSTM, GRU, risk management
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Cite this article
Leng,R.;Tang,N.;Zhao,L. (2024). The Transformative Role of Data Mining in Financial Analysis and Risk Management. Journal of Fintech and Business Analysis,1,72-76.
Data availability
The datasets used and/or analyzed during the current study will be available from the authors upon reasonable request.
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Journal：Journal of Fintech and Business Analysis
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