The merit of this regulation is that it introduces incentives for better risk management by banks, while at the same time attenuating the cyclicality of the financial sector and, thereby, swings in the real economy. In my concluding remarks I will try to summarise the main lessons we have learned in discussing, designing and implementing the new system, with an emphasis on the broader economic view rather than on the purely supervisory one. Let me bring forward my main conclusion: there are regulatory mechanisms, like dynamic provisioning, that provide incentives for sound risk management and are anti-cyclical by nature and can therefore moderate cyclical swings. ***** Recent experience in a number of countries shows that credit expansion and asset price increases - and bubbles - are mutually reinforcing processes (see Graph 1). Asset prices may start to rise in an economy because new investment opportunities appear or simply because of overly lax financial conditions. When asset prices rise so does the value of collateral, which makes financing easier, increasing the demand for assets. That in turn pushes asset prices upward. In the downturn, as the value of collateral drops, financing possibilities decline, as does thus credit growth, a process often reinforced by financial institutions pursuing much more cautious credit policies as they are incurring losses or making smaller profits in this phase of the cycle. Tighter credit policies reinforce recessionary forces and provoke additional reductions in asset prices.
However, in a slowdown, as the impaired assets rise, the specific provision requirements increase and the statistical provision becomes negative. This means that the statistical fund (accumulated in previous years) starts being used, its proceeds (the difference between the latent risk and the specific provision) being credited to the profit and loss account. Therefore, thanks to the mechanism of the statistical provision, the burden of credit risk on the profits of banking institutions is better spread over the cycle and more in accordance with the evolution of expected losses. The new scheme offers banks two options. First, to use their own internal measurements of the statistical credit risk and second, to use a standard method. The Bank of Spain expects that in the future an increasing number of institutions will be able to show robust computations, in the framework of an integrated credit risk management system. However, probably in the next year or two, most banks will use the standard method. In the standard system the supervisor sets the parameters. The portfolio is distributed in six blocks, according to the relative riskiness of the different assets, or off-balance sheet items with credit risk. A vector of coefficients (ranging from 0 to 1.5%) is applied to the exposures contained in the six blocks. The resulting figure is the estimated expected loss for the bank portfolio. The computation produces an aggregate annual gross burden (i.e.