01546nas a2200229   4500000000100000000000100001008004100002260001200043653001200055653001100067653001300078653001300091653000900104653002000113100002400133245008800157856009800245300001000343490000600353520094300359022001401302       2016                            d  c03/201610aNetwork10aSocial10aAnalysis10aBig Data10aRisk10aOTC Derivatives1 aMari-Carmen Mochón00aSocial Network Analysis and Big Data tools applied to the Systemic Risk supervision  uhttp://www.ijimai.org/journal/sites/default/files/files/2016/02/ijimai20163_6_5_pdf_14449.pdf  a34-370 v33 aAfter the financial crisis initiated in 2008, international market supervisors of the G20 agreed to reinforce their systemic risk supervisory duties. For this purpose, several regulatory reporting obligations were imposed to the market participants. As a consequence, millions of trade details are now available to National Competent Authorities on a daily basis. Traditional monitoring tools may not be capable of analyzing such volumes of data and extracting the relevant information, in order to identify the potential risks hidden behind the market. Big Data solutions currently applied to the Social Network Analysis (SNA), can be successfully applied the systemic risk supervision. This case of study proposes how relations established between the financial market participants could be analyzed, in order to identify risk of propagation and market behavior, without the necessity of expensive and demanding technical architectures.  a1989-1660