New challenges facing today's financial and regulatory institutions requires multidisciplinary problem-solving that leverages methodologies from both complex network analysis and data science. Quantitative analysis has equipped financial companies to make smarter decisions and to more accurately predict future returns on their investments; however, innovative methodologies are required to tackle complex finance problems such as systematic risks, the impact of financial contagions, evaluating the resilience of these systems and predicting, quantifying and controlling the inter-related or second-order effects during a crisis. Networks constitute a formidable tool for the analysis of these kinds of issues. Economic and financial systems are examples of networked systems, being characterized by the interaction of many heterogeneous units (the ​nodes​), through more or less complex interconnection patterns (the links​): examples are provided by networks of banks, stocks, companies, countries, industries, products.

This satellite aims at bridging the gap between the fields of complex networks theory and finance by bringing together experienced researchers and young scholars interested in interdisciplinary research to discuss state-of-the-art work, share knowledge and create opportunities for novel and fruitful collaborations. Further, we intend to bring cutting-edge academic research in contact with industry experience and impact. From a purely methodological perspective, instead, the approach pursued by applying the tools rooted into theoretical physics seems to represent the most promising avenue to gain insight into the behavior of economic and financial systems: for this reason, this satellite seeks abstracts employing methods developed into statistical mechanics, information theory and, more in general, complex systems.