Integrated and scalable from the desk top to the full enterprise in three-tiered client server mode, Kamakura's operational risk management solution can process millions of transactions using Kamakura Risk Manager's (KRM) distributed processing features.
Kamakura believes that clients should have total control over the analytical methods used, whether they are basic industry standard calculations that are decades old or the latest state of the art credit models from leading risk management researcher Dr. Robert Jarrow.
In Kamakura Risk Manager, the recovery rate for a Operation Risk Event can be modeled either as a constant proportion of loss or as a random event using one of four probability distributions in KRM. The recovery rate options for operational risk are identical to those that are available for modeling credit risk:
The recovery rate can be driven by some or all of the same factors that drive the probability of the operational risk event. The operational risk gross losses depend on the nature of the loss event. These losses are user supplied in the Kamakura Risk Manager implementation. For a comprehensive implementation of operational risk events, a full multiperiod simulation with macro factors driving operational risk probabilities and recoveries up and down. Loss severity ,loss frequency etc are also considered in OR modeling
Kamakura's operational risk solution offers distinct advantages in measuring Variance-Covariance Value-At-Risk, Historical Value-At-Risk, Credit-adjusted and Option-adjusted Value-At-Risk.
The Kamakura Risk Manager framework is based on a "multiple models" orientation, not just for operational risk but for the full range of enterprise wide risk management calculations: yield curve fitting, yield curve and spread simulation, options valuation, default modeling, prepayment modeling and other insurance event modeling.
Advanced Macro Factor and Interest Rate Modeling
KRM OR takes full advantage of the advanced interest rate modeling functionality available in the KRM solution. This is important, for example, because some operational risks are a function of the value of selected assets and liabilities, like the probability of a "rogue trader" incident. "Rogue traders" are classified as rogues because their position has moved against them to such a large extent that they seek to hide it. No one with a profit is considered a "rogue," although they may have violated trading limits. Other operational risk, like the bank robbery example above, may have no dependence at all on securities valuation. For those operational risk events where securities values matter, KRM OR uses the KRM valuation yield curves to determine the economic value of those securities at different points in time, and it uses the randomness of simulated securities values to drive both the probability of an operational risk event and the recovery rate on that event if it occurs. Operational risk-related securities valuation in KRM OR depends on high quality yield curves with discounting functionality at any possible cash flow date.
The yield curve smoothing functions in KRM define the relationship between a specified tenor and the yield, discount rate, or forward rate corresponding to that tenor on the valuation date. KRM OR provides several different forms of yield curve smoothing methods that can be employed in transfer pricing. There are six methods in KRM for smoothing the yield curve itself, and an additional six methods for smoothing the credit spread relative to a "risk free" yield curve. For more on these smoothing techniques, please see Chapters 8 and 18 of Advanced Financial Risk Management. KRM OR can also calibrate the parameters of the yield curve for a given operational risk valuation date to observed market yields or bond prices with similar risk characteristics on that date. These features assure that the calculated operational risk cash flows and valuations are consistent with market interest rates. Securities associated with operational risk often contain embedded options, such as a call option on the remaining cash flows of the instrument or a prepayment option. Additionally, operational risk-related floating-rate instruments have future cash flows that are contingent upon future interest rates, and these instruments may also have embedded rate options, such as caps or floors. The value of these embedded interest rate options depends upon the dynamics of the underlying interest rates and the yield curve from which they are obtained.
KRM OR models these interest rate dynamics for a given yield curve using one of several forms of parameterized N-factor (i.e. arbitrary number of yield curve drivers) dynamic yield curve (term structure) models, such as the Hull White (extended Vasicek) model. KRM OR can also calibrate the parameters of the dynamic yield curve models using a sample of historical yield curves or a set of implied swaption volatilities. These features provide the underlying interest rate models required for valuation of complex interest rate options.
Dynamic Multi-Period Profitability Measurement
KRM OR extends the powerful multi-period portfolio simulation functionality available in the KRM solution to support profitability measurement based on both traditional sources of risk (credit risk, market risk, asset and liability management, etc.) and operational risks. The multi-period simulation functionality produces projected cash flows associated with operational risks plus interest cash flow, income and expense, accrued interest and market value results for each transaction on and off balance sheet during a specified sequence of accounting periods based on simulated yield curves and other factors during those periods. The periods in the accounting calendar are fully customizable to allow results to be calculated with the time granularity required for profitability measurement.