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CLC number: TP183

On-line Access: 2024-08-27

Received: 2023-10-17

Revision Accepted: 2024-05-08

Crosschecked: 2022-08-03

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Citations:  Bibtex RefMan EndNote GB/T7714

 ORCID:

Jun ZHOU

https://orcid.org/0000-0001-6033-6102

Zhiqiang ZHANG

https://orcid.org/0000-0001-5483-0366

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Frontiers of Information Technology & Electronic Engineering  2022 Vol.23 No.12 P.1747-1764

http://doi.org/10.1631/FITEE.2200039


FinBrain 2.0: when finance meets trustworthy AI


Author(s):  Jun ZHOU, Chaochao CHEN, Longfei LI, Zhiqiang ZHANG, Xiaolin ZHENG

Affiliation(s):  College of Computer Science and Technology, Zhejiang University, Hangzhou 310027, China; more

Corresponding email(s):   jun.zhoujun@antfin.com, zjuccc@zju.edu.cn, longyao.llf@antfin.com, lingyao.zzq@antfin.com, xlzheng@zju.edu.cn

Key Words:  Artificial intelligence in finance, Trustworthy artificial intelligence, Risk management, Fraud detection, Wealth management


Jun ZHOU, Chaochao CHEN, Longfei LI, Zhiqiang ZHANG, Xiaolin ZHENG. FinBrain 2.0: when finance meets trustworthy AI[J]. Frontiers of Information Technology & Electronic Engineering, 2022, 23(12): 1747-1764.

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publisher="Zhejiang University Press & Springer",
doi="10.1631/FITEE.2200039"
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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.

金融大脑 2.0: 当金融遇到可信人工智能

周俊1,2,陈超超1,李龙飞2,张志强2,郑小林1
1浙江大学计算机科学与技术学院,中国杭州市,310027
2蚂蚁科技集团,中国杭州市,310027
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。

关键词:金融智能;可信人工智能;风险管理;欺诈检测;财富管理

Darkslateblue:Affiliate; Royal Blue:Author; Turquoise:Article

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