Recent economic crises like the 2008 financial tsunami has demonstrated a critical need for better understanding of the topologies and various economic, social, and technical mechanisms of the increasingly interconnected global financial system. Such a system largely relies on the interconnectedness of various financial entities such as banks, firms, and investors through complex financial relationships such as interbank payment networks, investment relations, or supply chains. A network-based perspective or approach is needed to study various financial networks in order to improve or extend financial theories, as well as develop business applications. Moreover, with the advance of big data related technologies, and the availability of huge amounts of financial and economic network data, advanced computing technologies and data analytics that can comprehend such big data are also needed. We referred this approach as financial network analytics. We suggest that it will enable stakeholders better understand the network dynamics within the interconnected global financial system and help designing financial policies such as managing and monitoring banking systemic risk, as well as developing intelligent business applications like banking advisory systems. In this paper, we review the existing research about financial network analytics and then discuss its main research challenges from the economic, social, and technological perspectives.