  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.
