The Use of Deep Learning for Predictive Analytics in Financial Management

Predictive analytics using Deep Learning (DL) is a hot new field in the field of financial management. This paper explores how DL may be used in many contexts to better economic prediction and decision-making. The advantages of using DL for predictive analytics are first discussed in the article. Th...

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Bibliographic Details
Published in2023 3rd International Conference on Advance Computing and Innovative Technologies in Engineering (ICACITE) pp. 286 - 290
Main Authors Krishna, Somanchi Hari, Singh, Navdeep, Ramola, Bharti, Reddy, G. Swamy, Al-Taee, Mustafa, Alazzam, Malik Bader
Format Conference Proceeding
LanguageEnglish
Published IEEE 12.05.2023
Subjects
Decision making
Deep learning
Financial management
Predictive models
Q-learning
Recurrent neural networks
Reinforcement Learning
SARSA algorithm
Statistical Analysis
Training
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Summary:Predictive analytics using Deep Learning (DL) is a hot new field in the field of financial management. This paper explores how DL may be used in many contexts to better economic prediction and decision-making. The advantages of using DL for predictive analytics are first discussed in the article. These include the ability to handle large amounts of data, discover patterns and trends, and make precise predictions. Credit risk analysis, portfolio management, and fraud detection are just a few of the many specific applications of DL that are explored in this research. The study concludes with a look at the challenges and limitations associated with using DL for predictive analytics in financial management, as well as the goals of future studies in this area. This research paper shows how DL may improve financial management by providing new methods of making sound, timely decisions.
DOI:10.1109/ICACITE57410.2023.10182935