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On-line Access: 2022-12-14

Received: 2022-01-30

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Crosschecked: 2022-08-03

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Zhiqiang ZHANG


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


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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A1 - Jun ZHOU
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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



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


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