CLC number: TP391
On-line Access: 2024-08-27
Received: 2023-10-17
Revision Accepted: 2024-05-08
Crosschecked: 2019-07-22
Cited: 0
Clicked: 7176
Xiao-lin Zheng, Meng-ying Zhu, Qi-bing Li, Chao-chao Chen, Yan-chao Tan. FinBrain: when finance meets AI 2.0[J]. Frontiers of Information Technology & Electronic Engineering, 2019, 20(7): 914-924.
@article{title="FinBrain: when finance meets AI 2.0",
author="Xiao-lin Zheng, Meng-ying Zhu, Qi-bing Li, Chao-chao Chen, Yan-chao Tan",
journal="Frontiers of Information Technology & Electronic Engineering",
volume="20",
number="7",
pages="914-924",
year="2019",
publisher="Zhejiang University Press & Springer",
doi="10.1631/FITEE.1700822"
}
%0 Journal Article
%T FinBrain: when finance meets AI 2.0
%A Xiao-lin Zheng
%A Meng-ying Zhu
%A Qi-bing Li
%A Chao-chao Chen
%A Yan-chao Tan
%J Frontiers of Information Technology & Electronic Engineering
%V 20
%N 7
%P 914-924
%@ 2095-9184
%D 2019
%I Zhejiang University Press & Springer
%DOI 10.1631/FITEE.1700822
TY - JOUR
T1 - FinBrain: when finance meets AI 2.0
A1 - Xiao-lin Zheng
A1 - Meng-ying Zhu
A1 - Qi-bing Li
A1 - Chao-chao Chen
A1 - Yan-chao Tan
J0 - Frontiers of Information Technology & Electronic Engineering
VL - 20
IS - 7
SP - 914
EP - 924
%@ 2095-9184
Y1 - 2019
PB - Zhejiang University Press & Springer
ER -
DOI - 10.1631/FITEE.1700822
Abstract: artificial intelligence (AI) is the core technology of technological revolution and industrial transformation. As one of the new intelligent needs in the AI 2.0 era, financial intelligence has elicited much attention from the academia and industry. In our current dynamic capital market, financial intelligence demonstrates a fast and accurate machine learning capability to handle complex data and has gradually acquired the potential to become a “financial brain.” In this paper, we survey existing studies on financial intelligence. First, we describe the concept of financial intelligence and elaborate on its position in the financial technology field. Second, we introduce the development of financial intelligence and review state-of-the-art techniques in wealth management, risk management, financial security, financial consulting, and blockchain. Finally, we propose a research framework called FinBrain and summarize four open issues, namely, explainable financial agents and causality, perception and prediction under uncertainty, risk-sensitive and robust decision-making, and multi-agent game and mechanism design. We believe that these research directions can lay the foundation for the development of AI 2.0 in the finance field.
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