alone will never be enough to get a complete picture, especially since the financial system evolves rapidly. intelligence gathered from discussions with the financial sector, as well as information shared with other policy - makers and supervisors here in canada and in the international community, will always be critical to the overall assessment of the risks. while we are making progress, it is important to remember that financial system modelling is still in its infancy. the goal – understanding, preventing, and reducing systemic | risk – deserves our attention, diligent research and hard work. it has been my pleasure to share some of the bank ’ s efforts with you today. thank you very much. bis central bankers ’ speeches bis central bankers ’ speeches bis central bankers ’ speeches

calculate the probability of a crisis. bis central bankers ’ speeches another strength of the model is that it provides a flexible tool for simulating the impact on household solvency of a wide range of potential shocks, such as an increase in unemployment. hram indicates that household loans in arrears would more than double under a severe labour market shock similar to that observed in the recession of the early 1990s. despite the model ’ s strengths, we continue to enhance our analysis by improving hram. expanding the behavioural aspects of the model is one way to do this. for instance, the model currently allows distressed households to pay their debts by selling their liquid assets, but not their homes. work is also under way to improve the design of the shock scenarios. results of stress tests using hram are regularly reported in the bank ’ s financial system review and constitute an important element of our overall assessment of the risks associated with household finances. assessing contagion effects in the banking system hram provides invaluable information on vulnerabilities in the household sector, but the bank is also interested in assessing risks more broadly within the canadian financial system. to this end, we have been working for several years on developing a macrofinancial risk assessment framework ( or mfraf ). 5 drawing on detailed data from bank balance sheets, mfraf is a quantitative model that tracks the contribution of individual banks to systemic risk. traditional stress - testing models focus exclusively on solvency risk, and estimate the overall risk to the financial system by simply aggregating credit ( or other asset ) losses that would materialize at individual banks in the event of a severe shock. mfraf goes beyond this traditional approach by taking into account linkages among banks arising from counterparty exposures – or network spillover effects – as well as funding liquidity risk, that is, the risk of market - based runs on banks. the financial crisis illustrated the significant risks associated with a deterioration of funding liquidity. the collective reactions of market participants led to mutually reinforcing solvency and liquidity problems at banks around the world. as funding liquidity evaporated, many well - capitalized institutions had to take writedowns on illiquid assets, or sell them at a loss, creating uncertainty in the market about their solvency and adding to the downward pressure on asset prices. mfraf has been built to integrate funding liquidity risk as an endogenous outcome of the interactions between solvency