# FinBrain: When Finance Meets AI 2.0

arXiv: https://arxiv.org/abs/1808.08497 · HTML: https://mlsanity.com/paper/1808.08497/

## Key facts

- Cited by 10 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 26 Aug 2018.

## Built on by (most cited first, 10 of 10)

- [Time Travel is Cheating: Going Live with DeepFund for Real-Time Fund Investment Benchmarking](https://mlsanity.com/paper/2505.11065/) (2025)
- [A Survey of Explainable Artificial Intelligence (XAI) in Financial Time Series Forecasting](https://mlsanity.com/paper/2407.15909/) (2024)
- [The AI Revolution: Opportunities and Challenges for the Finance Sector](https://mlsanity.com/paper/2308.16538/) (2023)
- [Towards Responsible AI for Financial Transactions](https://mlsanity.com/paper/2206.02419/) (2022)
- [Developing A Multi-Agent and Self-Adaptive Framework with Deep Reinforcement Learning for Dynamic Portfolio Risk Management](https://mlsanity.com/paper/2402.00515/) (2024)
- [Will LLMs be Professional at Fund Investment? DeepFund: A Live Arena Perspective](https://mlsanity.com/paper/2503.18313/) (2025)
- [The Art of Deception: Robust Backdoor Attack using Dynamic Stacking of Triggers](https://mlsanity.com/paper/2401.01537/) (2024)
- [An Interpretable Loan Credit Evaluation Method Based on Rule Representation Learner](https://mlsanity.com/paper/2304.00731/) (2023)
- [A Survey of Blockchain, Artificial Intelligence, and Edge Computing for Web 3.0](https://mlsanity.com/paper/2311.13731/) (2023)
- [Wormhole Dynamics in Deep Neural Networks](https://mlsanity.com/paper/2508.15086/) (2025)

## Abstract (arXiv)

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 work, 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.