Within this network, systemically important banks provide essential services for other banks. For example, they play a key role in system-wide liquidity provision and adjustment between banks. Normally, this takes the form of short-term interbank lending. If a key player in this network gets into difficulty, this interbank market can seize up, causing problems for other, otherwise sound banks, too. c) The result is false incentives and high risks for society as a whole  A systemically important bank can expect to be bailed out because the cost of failure for the real economy would be extremely high. In other words: the bank benefits from an implicit state guarantee. The consequence of this are far-reaching, as it provides significant false incentives for a bank’s shareholders, management and creditors. On the one hand, shareholders and management of a ‘too big to fail’ bank benefit from unjustifiably low capital borrowing costs, compared to other banks. The state guarantee is tantamount to a subsidy worth billions. 2 It allows shareholders and managements to take on more debt and greater risk. 3 On the other hand, the state guarantee means that creditors have less incentive to make sure that the bank does not take on excessive risk. If all goes well, they will benefit from virtually risk-free interest income. If, however, things do go wrong, the state will have to intervene and the creditors will not be held liable for any losses that may arise.
Allied to this underestimation of the significance of systemic interlinkages was an excessive faith in modelling, to which the supervisory authorities also subscribed. 11 There was a general conviction that the commonly used quantitative models for measuring risk captured the actual risks in the banking system fully and reliably – a dangerous misapprehension. For instance, these models’ risk calculations were based on correlations of price trends in the recent past, while often disregarding the fact that such correlations can change rapidly and significantly, for reasons that are not directly apparent from the data. Moreover, the models simply did not 9  The ‘too big to fail’ issue had been discussed in detail in a number of academic studies and textbooks before 2008; for example, cf. Stern and Feldman (2004). 10 Cf. Moosa (2010). 11 For example, cf. Bernanke (2006). Page 6/14  sufficiently replicate certain risks which grew to major proportions over the course of the crisis, such as the default risk of positions which the banks were holding on the assumption that they could easily sell them at short notice. 12 Since the regulatory capital requirements largely relied on these model-based calculations, they did not adequately take account of the actual risk exposure. Against this background, the resilience of many banks proved to be insufficient overall during the crisis. Relative to their risk exposure, the banks simply did not have large enough liquidity and capital cushions. They were unable to absorb large outflows of funds and losses.