RiskCalc Plus consists of a global network of 29 private firm models specific to different regions and industries and covering most of the world’s GDP. RiskCalc Plus produces a forward-looking EDF™(expected default frequency) credit measure by combining financial statement data and equity market based information. EDF credit measures reflect a forward-looking assessment of credit risk. The predictive analytics are based on Moody’s Analytics Credit Research Database (CRD™). Built in partnership with leading global financial institutions, the database incorporates the latest financial statements and also default data from the recent recession. The database yields unique insight into private-firm default probability. Such information has proven to be a significant challenge for financial institutions to access due to data limitations and constraints on internal resources.Financial institutions around the world use RiskCalc Plus to efficiently screen obligors at origination, detect credit deterioration early, and comply with regulatory requirements such as Dodd-Frank and Basel. These institutions include commercial banks, corporations, asset managers, investment banks and insurers. For more information, please visit http://www.moodysanalytics.com/riskcalc2013. About Moody’s Analytics Moody’s Analytics helps capital markets and risk management professionals worldwide respond to an evolving marketplace with confidence. The company offers unique tools and best practices for measuring and managing risk through expertise and experience in credit analysis, economic research and financial risk management. By providing leading-edge software, advisory services and research, including proprietary analyses from Moody’s Investors Service, Moody’s Analytics integrates and customizes its offerings to address specific business challenges. Moody's Analytics is a subsidiary of Moody's Corporation (NYSE: MCO), which reported revenue of $2.7 billion in 2012, employs approximately 7,000 people worldwide and has a presence in 29 countries. Further information is available at www.moodysanalytics.com.
Moody’s Analytics, a leader in risk measurement and management, today announced the release of an enhanced version of RiskCalc™ Plus, its private-firm probability of default model for credit risk management. New features include stress testing models for the US, ratio-driven global banking models for assessing financial institutions and a qualitative overlay module that combines the quantitative probability of default measure from RiskCalc with qualitative risk drivers into a single measure. “Many risk practitioners are struggling to build, validate, and integrate credit analytics into their stress-testing platforms,” said Thomas Day, Senior Director at Moody’s Analytics. “RiskCalc Plus streamlines the process by allowing firms to focus less on process and more on risk analysis. As an established product, based on comprehensive data, granular analytical capabilities and flexible platform delivery choices, it is an ideal tool in any stress-testing process, as a primary, challenger, or benchmark model.” Regulators are prescribing different modeling approaches and requirements, and are requesting transparency around stress testing modeling. RiskCalc Plus now offers two stress testing modeling approaches for evaluating US private-firm commercial and industrial loan portfolios. The first, a ratio-based approach, incorporates fundamental analysis that links financial statement-based ratios to macroeconomic variables developed by Moody’s Analytics’ leading team of economists. The model forecasts pro-forma financials and provides transparency into financial ratio risk drivers under various stressed environments. Detailed economic scenarios for the US in the model include those of the Federal Reserve’s Comprehensive and Capital Analysis and Review (CCAR). The second approach for modeling the portfolios of US private firms uses probability of default (PD) and loss given default (LGD) to provide an aggregated and pooled method for stress testing. The model aggregates exposures by credit quality and industry, leveraging an organization’s internal ratings. It forecasts expected loss (EL) and charge-offs based on macroeconomic scenarios, debt type, industry, and stressed PD and LGD levels. This model also leverages organization-specific scenarios to meet the firm’s specific modeling and software needs.