The recent complex dynamics observed in financial and commodity markets require continuous updates, implementation and backtesting of mathematical models aimed to provide an efficient representation of a real world situation.The aim of the scholars who attended the 50th Meeting of the Euro Working Group for Financial Modelling is to provide "new" tools for, and answers to, the challenges issued by more complex markets dynamics and interactions.Financial modelling may mean different things to different users; we usually refer either to accounting and corporate finance applications, or to quantitative finance applications.Recent complex modelling tools have been developed to translate a set of hypotheses about the behaviour of markets or agents into numerical predictions in order to provide effective risk management strategies. The financial crisis which followed the Lehman crash highlighted the need to provide accurate measures of market, credit, operational, liquidity and funding risk measurement and management, for the practitioner and academic world.Traditional market, credit, operational, liquidity and funding risk measures (including the interplay between them) have to be adequately estimated and monitored by firms, banks and financial intermediaries using proper mathematical models. These models must allow the user to assess the correlated risks and risk concentrations, to implement statistical models for the identification of risks or to run stress-based measures.Although mathematical modelling and the quantitative approach are clearly important, common sense and an appreciation of a wide range of potential outcomes, includ-