very costly. finally, information on money and credit aggregates can be made more useful in the formulation of monetary policy. up to now, a widely shared so - called “ best practice ” in monetary policy did not pay enough attention to monetary aggregates partly because of the belief that there exists no stable relationship between quantity of money and economic activity. as a result, prior to the crisis there was no attempt to counteract the rapid credit growth even though, in most if not all cases, asset price bubble was a direct result of sustained excessive credit expansion. this issue in my view is most relevant for emerging markets where the financial sector is typically bank - based, with credit being the major source of funding for businesses, and credit risk being the most important risk to banks. such factors make the credit channel an important transmission mechanism of monetary policy in emerging markets. therefore, information content provided in key banking data such as loan demand, rate of loans approval, lending standards adopted by banks, delinquency ratio, and npl could be useful in helping to assess how risk and activities are evolving in the macroeconomy, and whether the information point to the need for monetary policy to react over and above what the usual price and output data imply, either by an interest rate action or by a macroprudential action. my final observation is on the relevance of inflation - targeting as a monetary policy framework in the post - crisis era. recently, inflation - targeting has come under a close scrutiny whether the framework is useful given its narrow focus on inflation whereas risk to economic and financial stability can come from many sources other than inflation. in this crisis, the performance of the inflation - targeting economies does differ widely, but the majority are those that have been more successful in weathering the crisis. examples here include australia, new zealand, canada and a large number of emerging market economies as opposed to a more difficult experience elsewhere. my view is that inflation - targeting remains useful as a framework for monetary policy, and experience of many inflation - targeting emerging markets in this crisis demonstrates clearly that price stability and financial stability can be preserved even under extreme financial circumstances. but the framework could be further strengthened so that the need to pay attention to financial stability concerns can be more formally addressed through a flexible inflation - targeting regime. combining macroprudential measures with inflation - targeting is one area that flexibility can be added. the bank of thailand is one central bank that has pursued this line of flexibility since 2004. another approach is

the macro - prudential supervisors. 4. 2 strategic decisions should be guided by a two pillar analytical approach : a toolbox of statistical risk models and a comprehensive stress - testing programme in order that these four core principles can be followed, the tools used within the risk control framework need to be capable of evaluating the totality of the risk the institution faces. furthermore, it should be possible to communicate this evaluation in a concise but comprehensive way to all stakeholders in the institution. in order to achieve this, a comprehensive risk evaluation toolbox needs to be put in place. this toolbox should comprise of a suite of complementary statistical risk models and a comprehensive stress testing programme. first let me highlight some considerations regarding the statistical risk models before turning my attention to the concept of stress - testing. a toolbox of complementary statistical risk models we use statistical risk measures such as value - at - risk, expected loss or expected shortfall to assess the risk facing an institution. however, as i ’ m sure you are aware, statistical risk models have been subject to strong criticism in recent times since the crisis has brought the shortcomings of some of these models to light. nevertheless, this does not signal the death toll for such models. on the contrary, statistical models, properly used, will be an important component of the risk control framework since they allow us to compress the myriad of risks facing an institution into a few easy - to - understand figures. there are some common - sense guiding principles which will ensure that this toolbox is used in a constructive manner to evaluate and control the risks faced by an institution : eu banking structures, ecb ( september 2010 ). bis central bankers ’ speeches 1. first, and perhaps most importantly, risk models are a tool : they are created to help aid our understanding of risk but are not there to replace the intellect of a risk manager who must interpret their output in a meaningful way. 2. second, risk models should not be used in isolation : every model encapsulates a different version of reality therefore using different models helps to build a more representative picture of the risks facing an institution. 3. third, risk models by their nature make simplifying assumptions regarding reality. therefore limitations of individual models should be clearly signalled. if the limitations of the model are not properly understood then this can lead to misinterpretations of the output. for example, statistical models may work well under normal market conditions but not under stressed market conditions where access