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Industry Summary Articles

Thursday, October 20, 2016

MathWorks Introduces Risk Management Toolbox

MathWorks today announced Risk Management Toolbox, which offers risk managers a set of functions and apps in MATLAB to develop and validate risk models and perform risk simulation. By supporting the development of models and helping to simulate scenarios, Risk Management Toolbox allows for accurate assessment of risk factors when performing credit and market risk analysis, modeling, and simulation.

Financial, quant, and risk professionals can now model probabilities of default, create credit scorecards, perform credit portfolio analysis, and backtest models to assess potential for financial loss. Risk Management Toolbox offers an open and customizable platform for mathematical modeling, visualization, and integrated risk analysis, modeling, and simulation across risk domains, helping to assess corporate and consumer credit risk, as well as market risk models. The toolbox runs within MATLAB, which provides an environment for mathematical exploration with royalty-free options for production deployment.

Key features of the toolbox include a Binning Explorer app for automatic and manual binning for credit scorecards, credit portfolio simulation tools to analyze credit portfolio risk, and backtesting tools for value-at-risk (VaR) models. Risk Management Toolbox, when combined with additional MATLAB products, provides a scalable solution that meets research and production applications needs across varied projects and timeframes, and offers interactive customized apps and detailed reports.

“In today's rapidly changing and volatile markets, risk modeling, validation, and stress testing are integral to financial services firms. Success depends on the accuracy of the models used and the velocity at which these organizations can innovate, while maintaining low risk exposure,” says Stuart Kozola, computational finance product manager, MathWorks. “With Risk Management Toolbox, these companies can now speed creation, validation, and performance of what-if scenarios on credit and market models to satisfy regulatory and compliance needs, and to navigate market movements.”

To view the original press release, please click here.

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