Derivative risk compliance tools can be used to both ensure compliance with the growing number of regulations, and, at the same time, be a negotiating tool to reduce or optimize the cost of hedging. Bloomberg’s Multi-Asset Risk System (MARS) is being used to do both, as corporate treasury departments struggle to comply with the IFRS13 requirement to incorporate the credit risk adjustment on fair value measurement of over-the-counter (OTC) derivative contracts. 

Credit risk evaluation

The Credit Valuation Adjustment (CVA) is the cost of the loss that the investor will incur if the counterparty defaults. The Debit Valuation Adjustment (DVA) is the cost of the loss that the counterparty will incur if the investor defaults - this is the CVA exposure from the counterparty’s perspective. 

For derivative contracts, credit risk is a two-way risk of loss when its fair value could move from an asset to a liability position over its life (or vice versa).  

The bilateral CVA is the adjustment to the risk free market value that takes into account the losses to each party if the other party defaults first. This is increasingly becoming the prevalent practice for both banks and corporates, and also the market standard for compliance reporting purposes.

Bloomberg’s MARS bilateral CVA tool, which assesses the bank’s and counterparty’s expected loss, provides:

• impact of the trade to portfolio and/or credit risk profile
• ability to compare or benchmark prices as a basis to negotiate
• identification of the most credit-heavy or volatile fair value trades and/or counterparty
• identification of the cost saving novation opportunities with a simulation of the portfolio impact if a trade is “novated” or transferred to another counterparty 
• potential future negative and positive exposure (including maximum exposure) at prescribed confidence levels
• potential Hedge Accounting impacts (trade by trade).

This assessment is complicated enough at a trade level, assessing the credit risk impact on a portfolio basis is much more difficult and model intensive, requiring a range of market data (such as rates, credit spreads), volatility and correlation between market risk factors and the use of simulation methodologies. This is especially true as the CVA for a portfolio is not additive (i.e. portfolio CVA is equal or less than the sum of the individual trade CVAs).

Keeping up with banks (and IFRS 13)

IFRS 13 did not prescribe a specific method for incorporating credit risk.  

Most financial institutions already have existing and advanced credit risk systems which required significant investment in technology and capabilities to cope with new data and calculation requirements. With the new IFRS 13 requirements, there is added pressure for corporates to keep their credit risk management practices up-to-date and on-par with the banks, otherwise they could loose out in some derivative deals.

Dealer Banks’ quality of data

Corporate Treasury’s ability to properly assess credit risks not only relies heavily on modelling and system capability, but, most importantly, also on access to reliable market data (such as interest and volatility curves) to feed into the calculations.

Bloomberg provides a wide range of premium market data (including CDS curves, interest rate and foreign exchange curves).  Corporate treasurers can readily use Bloomberg tools such as MARS CVA tool as and when needed using market data that is comparable to the bank’s data quality.  This is a key strength to Bloomberg’s valuation tool and, they believe, is their unique offering – access to reliable industry standard market data.

Pre-trade analysis

A typical use of MARS, which covers most types of instrument, in pre-trade analysis would be to assess the possible CVA impact of a new deal or impact if a deal moved from Bank A to Bank B.  MARS assesses the incremental CVA impact of the new deal or of such a move based on the:

• current and future exposures
• collateral arrangements which limit the potential future exposures
• bilateral nature of each derivative.

Price discovery

Using MARS corporates can price CVA on a similar basis to banks (who often use the Bloomberg tools and market data).  For example a corporate who has 1) determined the need to hedge its risk with a particular swap, and also 2) needs to assess independently the lowest overall cost, can use MARS to benchmark prices as well as perform what-if scenarios.   Corporates would be in a better position to compare bank’s quotes and quantitatively factor in the credit risk in their evaluation.  

Regulatory compliance

Complying with IFRS13 requirements to incorporate credit risk in its fair value measurement of OTC derivative contract will not just impact the fair values of outstanding positions, but also the related hedge accounting.  

Bloomberg’s MARS CVA and its hedge accounting tool (HEFF) can support a corporates reporting requirements under IFRS 13, as well as providing the capability to apply credit adjustment (including on a bilateral basis) to hedge accounting.  

These functionalities allow corporates to:

• align their reporting and accounting reports to reflect their credit risk management practices
• have access to powerful tools to help them manage their credit risk profile
• report the numbers for compliance purposes and also for management reporting.

Recent new user

Recently Toyota Finance Australia Limited (Toyota Finance), the Australian financial services arm of Toyota - who offer a range of finance, insurance and warranty products and services for individuals, business, fleet and wholesale customers - installed Bloomberg’s multi asset risk solution (MARS) for derivatives risk management and reporting. MARS has been integrated with Toyota Finance’s treasury management system. The company is now able to apply credit adjustments to their derivative positions, perform scenario analysis and generate risk reports on a single platform.

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CTMfile take: The IFRS13 regulatory compliance requirements to calculate the credit value adjustment on over-the-counter (OTC) derivative contracts, and other regulations require bank quality data and complex algorithmic portfolio analysis to ensure compliance and accurate reporting. However, this example also shows that tools, such as Bloomberg’s MARS, can do much more. They can be used to optimize cost of hedging in pre-trade analysis and in price discovery. Don’t settle just for compliance.