Risk Management Tools


We use a comprehensive range of quantitative tools and metrics for monitoring and managing risks. As a matter of policy, we continually assess the appropriateness and the reliability of our quantitative tools and metrics in light of our changing risk environment. Some of these tools are common to a number of risk categories, while others are tailored to the particular features of specific risk categories. The following are the most important quantitative tools and metrics we currently use to measure, manage and report our risk:

  • Economic capital. Economic capital measures the amount of capital we need to absorb very severe unexpected losses arising from our exposures. “Very severe” in this context means that economic capital is set at a level to cover with a probability of 99.98 % the aggregated unexpected losses within one year. We calculate economic capital for the default risk, transfer risk and settlement risk elements of credit risk, for market risk including traded default risk, for operational risk and for general business risk. We continuously review and enhance our economic capital model as appropriate. Notably during the course of 2009 and 2010 we revised the correlation model underlying our credit risk portfolio model to align it more closely with observable default correlations. In addition, the model is now capable of deriving our loss potential for multiple time steps, which is expected to enable it to also determine the regulatory Incremental Risk Charge going forward. Within our economic capital framework we capture the effects of rating migration as well as profits and losses due to fair value accounting. We use economic capital to show an aggregated view of our risk position from individual business lines up to our consolidated Group level. We also use economic capital (as well as goodwill and unamortized other intangible assets) in order to allocate our book capital among our businesses. This enables us to assess each business unit’s risk-adjusted profitability, which is a key metric in managing our financial resources. In addition, we consider economic capital, in particular for credit risk, when we measure the risk-adjusted profitability of our client relationships. For consolidation purposes Postbank economic capital has been calculated on a basis consistent with Deutsche Bank methodology, however, limitations in data availability may lead to portfolio effects that are not fully estimated and thereby resulting in over or under estimation. See “Overall Risk Position” below for a quantitative summary of our economic capital usage.
  • Following a similar concept, Postbank also quantifies its capital demand arising from severe unexpected losses, referring to it as “risk capital”. In doing so, Postbank uses uniform parameters to measure individual risks that have been classified as material. These parameters are oriented on the value-at-risk approach, using the loss (less the expected gain or loss) that will not be exceeded for a 99.93 % level of probability within the given holding period which is usually one year but for market risk set at 90 days.
  • Expected loss. We use expected loss as a measure of our credit and operational risk. Expected loss is a measurement of the loss we can expect within a one-year period from these risks as of the respective reporting date, based on our historical loss experience. When calculating expected loss for credit risk, we take into account credit risk ratings, collateral, maturities and statistical averaging procedures to reflect the risk characteristics of our different types of exposures and facilities. All parameter assumptions are based on statistical averages of up to seven years based on our internal default and loss history as well as external benchmarks. We use expected loss as a tool of our risk management process and as part of our management reporting systems. We also consider the applicable results of the expected loss calculations as a component of our collectively assessed allowance for credit losses included in our financial statements. For operational risk we determine the expected loss from statistical averages of our internal loss history, recent risk trends as well as forward looking expert estimates.
  • Value-at-Risk. We use the value-at-risk approach to derive quantitative measures for our trading book market risks under normal market conditions. Our value-at-risk figures play a role in both internal and external (regulatory) reporting. For a given portfolio, value-at-risk measures the potential future loss (in terms of market value) that, under normal market conditions, will not be exceeded with a defined confidence level in a defined period. The value-at-risk for a total portfolio represents a measure of our diversified market risk (aggregated, using pre-determined correlations) in that portfolio. At Postbank, the value-at-risk approach is used for both the trading book and the banking book. Postbank has laid down the material foundation to apply the internal market risk model used to measure and manage market risk in order to determine the capital requirements for market risk in accordance with the German Regulation on Solvency (“SolvV”) subsequent to regulatory approval.
  • Stress testing. We supplement our analysis of credit, market, operational and liquidity risk with stress testing. For credit risk management purposes, we perform stress tests to assess the impact of changes in general economic conditions or specific parameters on our credit exposures or parts thereof as well as the impact on the creditworthiness of our portfolio. For market risk management purposes, we perform stress tests because value-at-risk calculations are based on relatively recent historical data, only purport to estimate risk up to a defined confidence level and assume good asset liquidity. Therefore, they only reflect possible losses under relatively normal market conditions. Stress tests help us determine the effects of potentially extreme market developments on the value of our market risk sensitive exposures, both on our highly liquid and less liquid trading positions as well as our investments. The correlations between market risk factors used in our current stress tests are estimated from volatile market conditions in the past using an algorithm, and the estimated correlations proved to be essentially consistent with those observed during recent periods of market stress. We use stress testing to determine the amount of economic capital we need to allocate to cover our market risk exposure under the scenarios of extreme market conditions we select for our simulations. For operational risk management purposes, we perform stress tests on our economic capital model to assess its sensitivity to changes in key model components, which include external losses. For liquidity risk management purposes, we perform stress tests and scenario analysis to evaluate the impact of sudden stress events on our liquidity position. In 2010, we completed the implementation of our group wide stress testing framework across the different risk types, which also comprise reverse stress tests, i.e. an analysis that develops a scenario which makes the business model unviable. At Postbank all material and actively managed risk categories (credit, market, liquidity and operational risks) are subject to defined stress tests.
  • Regulatory risk assessment. German banking regulators assess our capacity to assume risk in several ways, which are described in more detail in Note 36 “Regulatory Capital” of the consolidated financial statements.

 

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