individual financial institutions contribute to overall systemic risk. these measures have been used in the reserve bank to measure the systemic importance of our banks through three different, yet, complementary perspectives ; viz., ( i ) common distress of the financial institutions in a system, ( ii ) distress between specific institutions, and ( iii ) distress in the system associated by distress in a specific institution. a banking stability index ( bsi ) is calculated, which captures the expected number of banks to become distressed given that at least one bank has become distressed. separate toxicity and vulnerability indices capture distress between specific institutions while the cascade effect attempts to measure the distress in the system associated with the distress of a specific institutions. this method is also being used for estimation of expected shortfall of assets of banking system, in a bid to assess what would happen to a bank in an environment of a large negative shock. network analysis the intertwined nature of modern financial systems was amply revealed by the recent financial crisis. such interconnected and complex financial systems make it particularly hard to predict the manner in which the cookie will crumble when distress situations emerge. network models attempt to capture the intricate structure of linkages between financial institutions by depicting the causal chains between nodes. the contractual obligations between financial institutions comprise the bilateral flows of payoffs and determine the extant network structures. an actual crisis with default of counterparties engenders system wide feedback loops and can trigger further contingent claims such as on derivatives obligations and also large losses at default due to collapse in asset markets. the techniques of network modelling have been used to develop a bespoke financial network analysis and contagion stress testing platform for the indian financial system. the analysis primarily looks into the interconnections that exists between different institutions in the financial system and tries to identify build up of systemic risk. graphical network representations have been developed which are being used to assess the degree of system level interconnectedness and the stability of the system. a contagion simulator helps in assessing the possible loss of capital to the financial system due to a random failure of one or more financial institutions. macro financial stress tests during the recent financial crisis, macro financial stress tests were used by some central banks as a policy tool to restore market confidence and improve market functioning. such stress testing addresses the need to assess the impact of the system wide nature of risk drivers. macrofinancial stress testing, quantifies the link between macroeconomic variables and the health of financial institutions and the financial system, to measure the

both the forest and trees ” 7 effectively ; there is a need to have a wide range of measures and tools covering different aspects of systemic risks. the objective is to develop a diagnostic tool that simultaneously traces the development of macro - financial conditions which pose risks to financial stability and identifies point in time risk conditions, while also assessing the joint impact of all these risk factors on systemic stability. a host of quantitative models attempting to incorporate one or more of these elements have emerged in the policy and the academic arena since the crisis. the models variously attempt to quantify the contagion risks in the financial system, to capture distress dependencies amongst financial institutions or to measure the systemic importance of financial institutions. others attempt to develop early warning indicators while yet another class of models aim to utilize aggregate information from segments of the financial system to develop coincident indicators of systemic stress. yet another set of models – the macro stress tests – try to measure the resilience of the financial system or its key components to various stress factors by quantifying the link between macroeconomic variables and the health of either individual financial institutions or the financial sector as a whole. the emerging models vary in statistical techniques used as well as in the type of available information used. they range from general equilibrium to game - theoretic models and can be either comparative static models or dynamic models. some models attempt to assess systemic risks using credit risk conditions while others rely on data from financial markets. the development of these models is in a nascent stage and the learning curve is very steep. identifying and assessing systemic risks requires a broad and deep information basis and a wide range of tools to process the relevant information as well as analytical tools and techniques. while fertile research on these issues is underway, especially since the crisis, the progress has been slow given the large mass of uncertainties – both “ known ” and “ unknown ”. let me briefly highlight some of these. first, while the notion of systemic risks is clear, there is, as yet, as elucidated earlier, no universally accepted definition of systemic risk. further, there is little agreement amongst regulators and academicians about the best way to operationalise a framework for the identification and measurement of systemic risks. the associated issues are further complicated by the fact that systemic risks are inherently unobservable. the main factors resulting in systemic risks – contagion risks, imbalances, etc., are also difficult to observe and / or quantify. adding to the difficulties are the