Private Firm Probability of Default Models for Community Banks

CREDIT RESEARCH & RISK MEASUREMENT

Private Firm Probability of Default Models for Community Banks RiskCalc™ Plus probability of default (PD) models are the premier tools to enhance your risk management processes for measuring private firm risk. RiskCalc models enable greater accuracy, consistency and efficiency when quantifying new and existing bank relationships. They also provide flexibility to assess businesses of all sizes and industries, including corporations, car dealerships, non- profits and real estate operators. These “off-the-shelf” models produce a forward-looking probability of default and other key metrics for a highly predictive measurement of standalone credit risk.

Key Credit Risk Challenges Faced by Community Banks »» Making better lending decisions by assessing loans based on credible, quantitative analytics »» Enhancing business performance by maintaining competitive pricing »» Addressing evolving regulatory requirements with transparent risk decision-making processes »» Establishing an early warning system and a rank-ordering process to forecast future risk

With Moody’s Analytics RiskCalc Plus, Community Banks can: »» Accurately price credit risk and reduce origination costs »» Monitor and benchmark commercial & small business loans »» Identify early warning indicators to inform necessary loan covenants »» Improve and standardize origination processes by differentiating risk before underwriting the loan »» Mitigate long-term risks by managing portfolio outliers »» Develop a systematic approach to allowance for loan and lease losses (ALLL) calculations for performing loans »» Implement scalable risk management practices for evolving regulatory needs »» Enhance the bank audit process This graph shows the relative contributions of the financial ratios used to calculate the EDF credit measures for a privately held firm.

Gain Global Insight into the Private Firm Credit Market The predictive power of RiskCalc models is based on Moody’s Analytics Credit Research Database (CRD™). Built in partnership with over 75 leading financial institutions around the world, the CRD contains 60 million financial statements on over 14 million borrowers and over 900,000 private company defaults, yielding unique insight into private firm default probability. Our models are developed and tested on localprivate firm data to capture local default risk factors specific to each state. Risk managers can integrate PD models built from this extensive dataset into credit risk practices at community banks to effectively manage loan portfolios and underwriting processes. RiskCalc Plus for Community Banks

RiskCalc Plus for Stress Testing The RiskCalc Plus solution offers the unique ability to provide both detailed and aggregate views incorporating sound assumptions and validation results, which can serve as primary, benchmark, or challenger models when stress testing credit portfolios. RiskCalc models generate credible outcomes and measure the change in risk profile under different stress scenarios, including CCAR supervisory scenarios, other broad economic scenarios, and organization-specific scenarios.

The ratio-based model uses fundamental analysis to link RiskCalc ratios derived from the balance sheet and income statement to macroeconomic scenarios. It calculates nine quarters of stressed expected default frequency (EDF), two years of forward looking pro-forma financials, and provides optimal transparency into the change in financial ratios under various stressed environments. The model also offers analytical insight to the overall drivers and contributions to risk in your portfolio. The PD and LGD model aggregates exposures by credit quality and industry, with the ability to leverage an organization’s internal ratings. The model forecasts stressed EDF, loss given default (LGD), expected loss (EL), and charge-offs based on macroeconomic scenarios, debt type, loan balance and commitment, starting PD and LGD levels. It also forecasts losses, net charge offs, allowance for loan and lease losses (ALLL), exposure at default (EAD) and provisions for 20 quarters.

Key RiskCalc Plus Features »» Comprised of a network of models developed and tested on local private-firm data to capture local default risk factors »» Used as a standalone probability of default (PD) model, an input to an internal PD model or as a benchmarking tool »» Accessed easily via the RiskCalc Plus website, through XML, or Moody’s Analytics’ integrated spreading platform; RiskCalc Plus software can also be stored behind your company’s firewall for added security »» Produces EDF credit measures from one through five years and allows time series charting of PDs for up to five years »» Compares obligors against industry peer groups using Peer Analysis functionality »» Consider qualitative factors specific to the industry, management, balance sheet and market of the company with Qualitative Overlay »» Maps EDF credit measures to agency ratings »» Adjusts for unique industry differences »» Captures the impact of credit cycle changes from month-to-month in the period between two financial statements »» Displays valuable ratio diagnostics and their individual contributions and sensitivities to risk About Moody’s Analytics Moody’s Analytics, a unit of Moody’s Corporation, helps capital markets and credit 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 offering leading-edge software and advisory services, as well as the proprietary credit research produced by Moody’s Investors Service, Moody’s Analytics integrates and customizes its offerings to address specific business challenges.

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SP31945/101215/IND-102A