Abstract: In the era of big data, the financial industry faces enormous challenges from voluminous, dynamic and multi-source heterogeneous information sources. It is very important to utilize the theories, methods and techniques of knowledge acquisition to extract valuable knowledge for financial decision-making support from massive data resources, and form various financial knowledge bases. These knowledge bases make it orderly converge to efficient financial knowledge service, which is of great significance for financial decision-making support processes such as investment decision-making, risk management and financial supervision. This paper systematically reviews the related research on knowledge acquisition for financial decision-making support, and comprehensively investigates the research status of the field from the two dimensions of factual financial knowledge acquisition and regular financial knowledge acquisition, and focuses on the research progress on fine-grained factual financial knowledge acquisition. Combined with the existing research results at home and abroad, future research should focus on the efficient acquisition and mining of large-scale financial knowledge, the fusion and integration of multi-source financial knowledge, and the personalized and intelligent services of financial decision-making support.

Key words: Financial decision-making support, Financial knowledge base, Knowledge acquisition, Knowledge service, Data mining