When the credit markets tightened two years ago and difficulties arose for many companies in quantifying their credit risks, Adobe Systems developed a novel modeling tool that evaluates its exposure to counterparty credit risks. Consequently, the software systems and services provider was able to reduce its default losses and overall credit risk exposure. Best of all, Adobe was able to stop trading with Lehman Brothers, previously one of its largest FX trading counterparties, months before the firm went belly up in September 2008.
Adobe is exposed to financial counterparty credit risk through traditional treasury activities like investing, hedging, share repurchase, cash management, insurance and debt management. “My predecessor wanted a way to get a better grip on quantifying the exposure in our transactions with counterparties,” explains Keith San Felipe, who joined Adobe as its vice president and corporate treasurer in July. “She also sought a more robust reporting system to proactively mitigate potential losses.” The first step in this journey was the development of models to quantify and aggregate the credit risk inherent in Adobe’s financial transactions. Treasury wanted the models to have a consistent methodology that could be applied across a variety of derivative and cash transactions. The primary risk metric calculated in the models was “expected loss due to default” from the various transactions. “We were concerned about the financial health of most of our counterparties,” explains Dave Smith, Adobe director of financial risk management. “We were seeing some large exposures, and we wanted to have a bigger picture of how much risk we were actually extending. We wanted to quantify our aggregate exposures so we could analyze and compare them to see if our risks were increasing or decreasing.” To calculate the potential exposure for each transaction based upon current market conditions, the model applies Monte Carlo simulations calibrated to current spot rates, interest rates and market-implied volatilities. “Another goal was for our default expectations to be derived from a forward-looking, market-based metric that would be more responsive than credit ratings to changes in a counterparty’s financial condition,” Smith adds. The absence of a forward-looking credit risk metric makes comparisons across different risk categories difficult, he says. “We use credit default swap spreads as the proxy for expected loss due to default,” Smith adds. “Exposures are then aggregated to determine the aggregated risk profile for each counterparty. Expected loss is then calculated on a portfolio basis.” The modeling tool monitors Adobe’s counterparty exposures, looking at worst case scenarios to properly quantify the risk. No sooner had it been deployed in the summer of of 2008 than Lehman Brothers popped up. “The most immediate and important value demonstrated by the tool was that it caused us to get out of all activity with Lehman ahead of their bankruptcy,” Smith says. “Had we been trading on a normal course with them we would have absorbed a $4 million to $5 million loss.” Since developing the modeling tool, Treasury has attached a reporting system to it. The system generated a variety of reports, such as changes in a counterparty’s financial condition, a time series of the counterparty’s credit default swap spreads and share price, and a report that describes in full the portfolio of derivative transactions between Adobe and the counterparty. The reports are “helpful in determining how to allocate trades to each counterparty,” Smith notes. “They’re also being used as the starting point to look at risk adjusted pricing.” The modeling tool is now being leveraged to analyze and quantify Adobe’s FAS 157 derivative pricing, says San Felipe. Since coming on board, he adds, “I’m trying to extend it anywhere we see fit.”