one data set which is harmonised but lacks coverage. and there is another one which reflects high coverage but lacks harmonisation. iii feasibility constraints i think we have to tackle these and other harmonisation gaps. furthermore, there is no doubt that the availability of reliable statistical data for financial stability purposes is not yet complete. we are faced with data gaps. there are, however, practical difficulties with regard to gathering additional, and more detailed, statistical data. one possibility to reduce these difficulties is to consider whether more data from commercial data providers could be purchased. however, the scope may not be sufficient as the focus of private providers is on financial market data. in addition, this option could turn out to be quite costly. another option might be to consider extending the statistics produced under the stewardship of the escb in the field of money and banking statistics. however, a good sense of proportion is necessary when deciding on new harmonised statistical requirements. there is a common understanding that producing statistics is a costly matter, in particular from the viewpoint of the data suppliers. any new statistical reporting will place an increased burden on the reporters and strain their resources. and let ’ s not forget that central bank statisticians and data reporters anyway have to cope with a whole bunch of new challenges. examples are the enlargement of the european union, any potential enlargement of the european monetary union, the change in accounting rules, and, last but not least, the requirement of calculating new indices and indicators for banking supervision purposes under the basle ii regime. given all these tasks, it is absolutely essential to set priorities. the highest priority should be attributed to closing data gaps with regard to essential indicators for financial stability such as statistics on the securitisation of bank loans. in order to narrow the data gap in this area we should use existing data with sufficient coverage from other sources. an obvious example is the biannual information by the bis on derivative instruments which is collected from a small number of leading market players, which covers still 80 % of the overall market volume. at the same time, we have to check whether existing statistical surveys could be discontinued in exchange for any new data requirements. for example, regionally disaggregated balance sheet data of banks in germany no longer have analytical relevance because of euro - area membership. in order to keep the costs within strict limits, statisticians may find it helpful to determine the extent to which one and the same data source might serve different analytical purposes

be able to cushion such shocks as much as possible rather than amplifying them. this year, the german financial stability committee ( fsc ) thus recommended raising the countercyclical capital buffer to 0. 25 % on account of increased cyclical systemic risks. allow me to explain in more detail how we assess these risks and what action needs to be taken. 1 underestimation of credit risk overall, the credit scores of german enterprises have been exceedingly good and insolvencies correspondingly low over the past few years. hence, it follows that the number of non - performing loans has declined. however, there are mounting signs that future credit risks are being underestimated : • banks ’ risk provisioning remains exceptionally low, reflecting the low number of insolvencies. • economic downturns coupled with steeply increasing credit risks are likely to be underrepresented in many banks ’ risk assessments. this is indicated, for instance, by the low risk weights of banks which use internal ratings - based models. • in addition to this, at around 5 % over the past year, lending to the private sector reached a 15 - year high. large, systemically important financial institutions have recently expanded their lending in this area to a greater degree than small and medium - sized institutions. allocation risks may thus emerge for the entire loan portfolio that appear paradoxical at first glance : even if the creditworthiness of all enterprises has improved following a long upswing, making each individual loan appear sound, the structure of the loan portfolio may shift to enterprises that are riskier in relative terms. allocation risks, then, are not themselves a new risk, but rather a further indication that credit risks are being underestimated. • creditworthiness varies between enterprises. most enterprises have a fair credit score, although there are some which are rated particularly highly, and others which are weaker. • this distribution is broadly reflected in banks ’ portfolios, too, although some enterprises also obtain funding via the capital market, whilst others draw on equity capital. • now, what happens during a cyclical upswing? in such an event, all enterprises see an improvement in their creditworthiness. strong enterprises increasingly turn to retained earnings or the capital market as sources of funding. even relatively riskier enterprises are able to take out more loans from banks on the strength of an overall improvement in creditworthiness. these are merely initial theoretical considerations which serve to illustrate the mechanism. but what concrete developments are