Increasing the effectiveness of counterparty risk analysis
Increasing the effectiveness of counterparty risk analysis at ING Bank
ING uses Monte Carlo-based credit risk simulations of counterparty transactions. The transactions between ING and counterparties may involve agreements to exchange different sequences of payments over a period of time. Credit risk is the potential that the counterparty will fail to meet its obligations in accordance with agreed terms. Credit risk simulations are usually used to calculate the credit exposure over a period of time. The problem is that these simulations take a long time and often compromises have to be made between the time taken to get results and the quality of these results. In a collaboration between the Distributed Systems Research Group at Brunel University led by Dr Simon J E Taylor, researchers implemented a desktop grid computing system at ING Bank.
The system used multiple desktop PCs to share the workload and enabled analysts to both reduce the time taken to get results and to increase the quality of those results. This had led to better and faster risk analysis and exposure.