Abstract
Artificial intelligence (AI) has accelerated the advancement of financial services by identifying hidden patterns from data to improve the quality of financial decisions. However, in addition to commonly desired attributes, such as model accuracy, financial services demand trustworthy AI with properties that have not been adequately realized. These properties of trustworthy AI are interpretability, fairness and inclusiveness, robustness and security, and privacy protection. Here, we review the recent progress and limitations of applying AI to various areas of financial services, including risk management, fraud detection, wealth management, personalized services, and regulatory technology. Based on these progress and limitations, we introduce FinBrain 2.0, a research framework toward trustworthy AI. We argue that we are still a long way from having a truly trustworthy AI in financial services and call for the communities of AI and financial industry to join in this effort.
摘要
人工智能通过从数据中识别隐藏模式以提高金融决策质量，从而加速金融服务的发展。然而，除了通常需要的属性，如模型准确性，金融服务还需要可信赖的人工智能，但其属性尚未充分实现。这些可信人工智能的属性是可解释性、公平性和包容性、稳健性和安全性，以及隐私保护。在本文中，我们回顾人工智能应用于金融服务各领域的最新进展和局限性，包括风险管理、欺诈检测、财富管理、个性化服务和监管技术。基于这些进展和局限性，介绍了金融大脑2.0，一个走向可信人工智能的研究框架。我们认为，在金融服务中，我们离真正可信人工智能还有很长的路要走，并呼吁人工智能和金融业的社区一同努力。
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Project supported by the National Natural Science Foundation of China (Nos. 62172362 and 72192823)
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Jun ZHOU, Chaochao CHEN, and Xiaolin ZHENG initiated the work. Jun ZHOU, Longfei LI, and Zhiqiang ZHANG conducted literature research and drafted the paper. Chaochao CHEN and Xiaolin ZHENG helped organize the paper. Jun ZHOU, Longfei LI, and Zhiqiang ZHANG revised and finalized the paper.
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Jun ZHOU, Chaochao CHEN, Longfei LI, Zhiqiang ZHANG, and Xiaolin ZHENG declare that they have no conflict of interest.
List of supplementary materials
1. Credit scoring
2. Financial distress prediction
3. Bankruptcy prediction
4. Portfolio management
5. Algorithmic trading (or quantitative trading)
6. Recommendation
7. Marketing
8. Customer services
9. Know your customer (KYC)
10. Anti-money laundering (AML)
11. Representative financial AI practices
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Zhou, J., Chen, C., Li, L. et al. FinBrain 2.0: when finance meets trustworthy AI. Front Inform Technol Electron Eng 23, 1747–1764 (2022). https://doi.org/10.1631/FITEE.2200039
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DOI: https://doi.org/10.1631/FITEE.2200039
Key words
- Artificial intelligence in finance
- Trustworthy artificial intelligence
- Risk management
- Fraud detection
- Wealth management