title: Discovering SIFIs in Interbank Communities.
abstract: This paper proposes a new methodology based on non-negative matrix factorization to detect communities and to identify central nodes in a network as well as within communities. The method is specifically designed for directed weighted networks and, consequently, it has been applied to the interbank network derived from the e-MID interbank market. In an interbank network indeed links are directed, representing flows of funds between lenders and borrowers. Besides distinguishing between Systemically Important Borrowers and Lenders, the technique complements the detection of systemically important banks, revealing the community structure of the network, that proxies the most plausible areas of contagion of institutions' distress.
authors.affiliation: Dept. of Economics and Social Sciences, Catholic University, Piacenza, Italy.
authors.forename: Nicolò
authors.initials: N
authors.lastname: Pecora
authors.affiliation: National Bank of Belgium, Brussels, Belgium.
authors.forename: Pablo
authors.initials: P
authors.lastname: Rovira Kaltwasser
authors.affiliation: Dept. of Economic and Business Sciences, University of Pavia, Pavia, Italy.
authors.forename: Alessandro
authors.initials: A
authors.lastname: Spelta
mesh_terms: D000465:Algorithms; D000067012:Banking, Personal / Q000191:economics*; D019058:Community Networks / Q000191:economics; D020407:Internet