What’s New with RiskCalc Plus and Private EDFs? Douglas Dwyer, Managing Director, Single Obligor Research Janet Zhao, Associate Director, Single Obligor Research Mehna Raissi , Associate Director, Single Obligor Product Management
2 Agenda 1. RiskCalc Refresher 2. What’s new in RiskCalc Plus? 3. What’s coming in RiskCalc Plus? 4. Polling 5. Question & Answer What’s New in RiskCalc Plus and private EDFs? October 2011
1 RiskCalc Refresher What’s New in RiskCalc Plus and private EDFs? October 2011
4 RiskCalc – An Overview • What is RiskCalc 3.1? » A third generation econometric model for private firm default risk using your company-specific financial statements • What is unique about RiskCalc 3.1? » Extensive explanatory analytics » A well understood, accepted standard » Market driven, industry level credit cycle adjustment » The largest, cleanest private firm default database in the world What’s New in RiskCalc Plus and private EDFs? October 2011
Credit Research Database (CRD) » All RiskCalc models are created using Moody’s Analytics Credit Research Database (CRD) » The CRD is a collection of credit risk data consisting of financial statements, descriptive customer information, and defaults events for 28 countries, covering most of the world’s GDP » The CRD collects data from institutions (banks and non-banks) and vended sources, then runs the data through rigorous analysis and data cleansing steps » The CRD also provides participating institutions with data cleansing and data quality reporting, benchmark reporting, and RiskCalc scoring services What’s New in RiskCalc Plus and private EDFs? October 2011
RiskCalc: 28 Models What’s New in RiskCalc Plus and private EDFs? October 2011
7 Additional RiskCalc Outputs • Relative Contribution & Sensitivity Graphs • Stress Test Graph • Percentile Graphs • Organizational Ratings What’s New in RiskCalc Plus and private EDFs? October 2011
About RiskCalc Plus: Access Options 1. Via Website (over the internet) – one obligor at a time 2. Via Website (over the internet) – multiple obligors in batch mode 3. Via XML Web Service (over the internet – system to system integration) 4. Locally deployed inside on client’s network (behind client’s firewall) 5. Integrated with RiskAnalyst & RiskOrigins 8 What’s New in RiskCalc Plus and private EDFs? October 2011
2 What’s new in RiskCalc? What’s New in RiskCalc Plus and private EDFs? October 2011
10 What’s new in RiskCalc Plus? Integration with RiskAnalyst and Scenario Analyzer - Launch and Load & Peer Analysis -What-if Analysis – change of financial statement inputs New Models & Upgrades -Emerging Markets 3.1, Russia 3.1, China 3.1 -Austria 3.2, South Africa 3.2, Germany 3.2 RiskCalc Scorecard -Combine quantitative and qualitative factor for overall borrower rating -Industry/Market Conditions, Balance sheet factors, Company Profile, Quality of Management German Extended Report -Advanced Peer Analysis including additional financial statement report What’s New in RiskCalc Plus and private EDFs? October 2011
11 Individual Borrower Benchmarking – Peer Analysis What’s New in RiskCalc Plus and private EDFs? October 2011
12 PD Over Time and Peer Group Analysis Example firm’s PD level climbed up before default PD levels of the peer group The Peer Group: Firms in Trade Sector What’s New in RiskCalc Plus and private EDFs? October 2011
13 Peer Comparison at Ratio Level What’s New in RiskCalc Plus and private EDFs? October 2011
3 What’s Coming in RiskCalc Plus? What’s New in RiskCalc Plus and private EDFs? October 2011
15 What’s coming in RiskCalc Plus? Continued Integration with RiskOrigins and Scenario Analyzer Stress Testing -Pre-defined MEDC Macro-economic Scenarios -Compare Base EDF vs. Stress EDF Model Expansion -RC Greece -Asset Class Expansion: Not-For Profits, Real Estate Operators Online Storage & Non-Financial Overlay -Portfolio reporting -Adding qualitative and behavioral component to overall score What’s New in RiskCalc Plus and private EDFs? October 2011
16 RiskCalc Validation & U.S. Model Update » We look at the following aspects when validating a model – Is the model working as intended? – Is the discriminatory power being maintained? – Is the level of the PD appropriate? – Can the model be improved? » The recent validation combines financial statement information with loan accounting system information to track cohorts over time – Data provided by 11 financial institutions – Data runs from 1999 through 2010 » The RiskCalc U.S. model performs well based on the recent data Number RC US v3.1 Z-Score Defaults Firms of Firm-Years 53.6% 37.7% 5,134 81,601 260,959 What’s New in RiskCalc Plus and private EDFs? October 2011
17 U.S. Model Asset Class Expansion » Extend the model to cover: non-for-profit organizations, real estate operators, and potentially dealership firms – Unique accounting standards, especially for non-for-profit organizations – Key risk drivers behave differently from those of a typical corporate – Central default tendency differs from that of the US corporate model » Non-for-profit model uses inputs specific for this asset class » Models built specifically for the three asset classes improve the accuracy ratio » Non-for-profit firms have lower default rate, while real estate operators and dealership firms have higher default rate New Models Improve Accuracy Ratio New Model US 3.1 Non For Profit 59% 53% Real Estate 56% 44% 58% Dealership 48% What’s New in RiskCalc Plus and private EDFs? October 2011
18 New Research Innovations » Stress Testing » Credit line usage and exposure at default » Behavioral Overlay » Accounting Quality What’s New in RiskCalc Plus and private EDFs? October 2011
19 Stress Testing Moody’s Economy.com Estimate Other Score Estimated SalesGrowth RiskCalc Inputs Inputs Through =F(GDP, based on the RiskCalc interest rate, Sales Estimation …) Next Period Input Computation Sales(t+1) Sales(t)* (1+ b 0 + b 1 *X(t)), X(t) are macroeconomic variables Net Income(t+1) Net Income(t) + g 1 *(Sales(t+1)-Sales(t)) Retained Earnings(t+1) Retained Earnings(t) +Income(t+1) Total Assets(t+1) Total Assets(t)+Income(t+1) Cash(t+1) Max(0,Cash(t)+Income(t+1)) EBITDA(t)+ ∆ Net Income EBITDA(t+1) What’s New in RiskCalc Plus and private EDFs? October 2011
20 Credit Line Usage and Exposure at Default Study » We pool credit line usage data together from eight financial institutions in the U.S. » The sample covers approximately 7,600 defaulters and 134,000 non-defaulters with valid usage information, 2000–2010 » The credit line usage of defaulted firms are indeed higher than that of non-defaulted firms 100% 90% 80% Usage Ratio mean - Defaulters 70% median - Defaulters mean - NonDefaulters 60% median - NonDefaulters 50% 40% -8 -7 -6 -5 -4 -3 -2 -1 0 Quarter Prior to Default What’s New in RiskCalc Plus and private EDFs? October 2011
21 Credit Line Usage and Exposure at Default Study » Usage increases with default probability measured by RiskCalc EDF » Evidence shows that banks do monitor credit lines. Usage relates to collateral types, bank internal rating and commitment size » Both commitment and balance amount declined during the recession times 6% 4% Change in Commitment or Balance 2% 0% Sep-01 Mar-02 Sep-02 Mar-03 Sep-03 Mar-04 Sep-04 Mar-05 Sep-05 Mar-06 Sep-06 Mar-07 Sep-07 Mar-08 Sep-08 Mar-09 Sep-09 Mar-10 -2% -4% -6% -8% Commitment Change Balance Change What’s New in RiskCalc Plus and private EDFs? October 2011
Adding a Behavioral Layer to RiskCalc » RiskCalc is based on financial statement fields » Behavior factors may also add to default prediction: credit line drawdown, age of lending relationship, freshness of financial statement… » We can potentially add a behavioral layer to RiskCalc models » Credit line drawdown add to the power of default prediction; more so for small firms, firms with Pass internal rating, firms with stale financial statements Combining Credit Line Usage with EDF Improves Accuracy Ratio Variable AR EDF only 53% Usage only 39% 70% weight on EDF, 30% on Usage 57% What’s New in RiskCalc Plus and private EDFs? October 2011
23 Accounting Quality - Identify “Abnormal” Financial Statements » RiskCalc is based on financial statement items. Financial quality metrics can potentially help RiskCalc users to identify problematic financial statement for further review » For public firms, researchers validate financial quality measurement with restatement event, SEC enforcement, or accounting-related lawsuit » For private firms, how can we validate the accounting quality measurements? » We construct a set of variables, and examine whether the identified “abnormal” statements are – Less useful in predicting defaults – Less predictive of future cash flows and earnings – Less likely to be audited – Less likely to be associated with loan accounting records What’s New in RiskCalc Plus and private EDFs? October 2011
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