It is often too late to take recovery action when a firm drops below minimum standards. And because firms approaching the minimum often have to deleverage sharply which can have a very adverse impact on the real economy. So we have created incentives for firms to run with a substantial buffer of capital above the hard minimum. Where common equity capital is less than 7% of risk-weighted assets, firms now face restrictions on bonuses and dividends. For systemically important banks, the required buffers are higher still. These buffers should give banks more room to use their capital to absorb losses rather than hitting the brakes on lending. On the other side of the equation, some action has been taken to tighten up the calculation of firms’ risk-weighted assets. And work is also underway to examine whether we can improve the “standardised approach” to risk-weighting – an approach in which banks use a riskweight prescribed by the regulators. As a result, the amount of capital in the system has increased substantially. Globally, the large banks now hold some $ of additional equity capital. Major UK banks have raised their equity capital by £ Their leverage has broadly halved. On average, the Major UK banks are now running with an end-point Basel 3 common equity capital ratio of 10%. Roughly speaking, that is more than double the equivalent pre-crisis ratio.
However, while the risk-weighted approach has been through wholesale reform, it still depends on mathematical models – and for the largest firms, their own models to determine  2  BIS central bankers’ speeches  riskiness. So the risk-weighted approach is itself subject to what in the trade is called “model risk”. This may sound like some arcane technical curiosity. It is not. It is a fundamental weakness of the risk based approach. Mathematical modelling is a hugely useful tool. Models are probably the best way we have of forecasting what will happen. But in the end, a model – as the Bank of England economic forecasters will tell you with a wry smile – is only a crude and simplified representation of the real world. Models have to be built and calibrated on past experience. When events occur that have no clear historical precedent – such as large falls in house prices across US states – models based on past data will struggle to accurately predict what may follow. In the early days of the crisis, an investment bank CFO is reported to have said, following hitherto unprecedented moves in market prices: “We were seeing things that were 25 standard deviation moves, several days in a row”. Well, a 25 standard deviation event would not be expected to occur more than once in the history of the universe let alone several days in a row – the lesson was that the models that the bank was using were simply wrong.