Full Text:   <69>

Suppl. Mater.: 

CLC number: 

On-line Access: 2022-08-18

Received: 2022-01-30

Revision Accepted: 2022-08-03

Crosschecked: 0000-00-00

Cited: 0

Clicked: 133

Citations:  Bibtex RefMan EndNote GB/T7714

-   Go to

Article info.
Open peer comments

Journal of Zhejiang University SCIENCE C 1998 Vol.-1 No.-1 P.


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, Zhejiang University, Hangzhou 310027, China; more

Corresponding email(s):   jun.zhoujun@antfin.com, longyao.llf@antfin.com, lingyao.zzq@antfin.com, zjuccc@zju.edu.cn, 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, 1998, -1(-1): .

@article{title="FinBrain 2.0: when finance meets trustworthy AI",
author="Jun ZHOU, Chaochao CHEN, Longfei LI, Zhiqiang ZHANG, Xiaolin ZHENG",
journal="Frontiers of Information Technology & Electronic Engineering",
publisher="Zhejiang University Press & Springer",

%0 Journal Article
%T FinBrain 2.0: when finance meets trustworthy AI
%A Chaochao CHEN
%A Longfei LI
%A Zhiqiang ZHANG
%A Xiaolin ZHENG
%J Journal of Zhejiang University SCIENCE C
%V -1
%N -1
%@ 2095-9184
%D 1998
%I Zhejiang University Press & Springer
%DOI 10.1631/FITEE.2200039

T1 - FinBrain 2.0: when finance meets trustworthy AI
A1 - Jun ZHOU
A1 - Chaochao CHEN
A1 - Longfei LI
A1 - Zhiqiang ZHANG
A1 - Xiaolin ZHENG
J0 - Journal of Zhejiang University Science C
VL - -1
IS - -1
SP -
EP -
%@ 2095-9184
Y1 - 1998
PB - Zhejiang University Press & Springer
ER -
DOI - 10.1631/FITEE.2200039

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 yet 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.

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

Open peer comments: Debate/Discuss/Question/Opinion


Please provide your name, email address and a comment

Journal of Zhejiang University-SCIENCE, 38 Zheda Road, Hangzhou 310027, China
Tel: +86-571-87952783; E-mail: cjzhang@zju.edu.cn
Copyright © 2000 - 2022 Journal of Zhejiang University-SCIENCE