Summary of Analysis Of Financial Risk Behavior Prediction Using Deep Learning and Big Data Algorithms, by Haowei Yang et al.
Analysis of Financial Risk Behavior Prediction Using Deep Learning and Big Data Algorithms
by Haowei Yang, Zhan Cheng, Zhaoyang Zhang, Yuanshuai Luo, Shuaishuai Huang, Ao Xiang
First submitted to arxiv on: 25 Oct 2024
Categories
- Main: Machine Learning (cs.LG)
- Secondary: Artificial Intelligence (cs.AI)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary This paper investigates the effectiveness of using deep learning and big data algorithms to predict financial risk behavior. The authors analyze the applications and advantages of these methods in finance, then design a deep learning-based framework for risk prediction and validate it on real-world datasets. The results show significant improvements in accuracy, providing valuable support for risk management. Challenges and potential future directions are also discussed. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary This paper looks at how to better predict financial risks using big data and machine learning. Right now, traditional methods struggle with large amounts of complex data. The authors try out a new way of doing things that uses deep learning and big data algorithms. They test it on real-world data and find that it works really well. This could help financial institutions make better decisions about risk. |
Keywords
* Artificial intelligence * Deep learning * Machine learning
