Private Firm Commercial & Industrial Credit Risk Solutions & Best Practices
 

Private Firm Commercial & Industrial Credit Risk Solutions & Best Practices

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In this webinar, Moody’s Analytics credit risk experts, Christian Henkel and Mehna Raissi, discuss the following topics: Overview of C&I credit risk management challenges; data management and credit ...

In this webinar, Moody’s Analytics credit risk experts, Christian Henkel and Mehna Raissi, discuss the following topics: Overview of C&I credit risk management challenges; data management and credit risk solutions that address the needs of credit risk managers; and private firm stress testing model and approach.

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Private Firm Commercial & Industrial Credit Risk Solutions & Best Practices Private Firm Commercial & Industrial Credit Risk Solutions & Best Practices Presentation Transcript

  • Private Firm Commercial & Industrial (C&I) Credit Risk Solutions & Best Practices JUNE 2014MEHNA RAISSI, DIRECTOR, PRODUCT MANAGEMENT CHRISTIAN HENKEL, DIRECTOR, RISK CONSULTING
  • Private Firm Commercial & Industrial (C&I) Credit Risk Solutions & Best Practices June 2014 Speakers Mehna Raissi is a Director in Product Management in the Enterprise Risk Solutions group with Moody’s Analytics and has been with the firm for nearly six years. She manages the single obligor credit risk products suite which include RiskCalc, Commercial Mortgage Metrics and LossCalc. Mehna is responsible for the management and product innovation of these premier credit risk management tools. Mehna completed her Bachelors in Managerial Economics from University of California, Davis, and her MBA from University of San Francisco. Chris Henkel is a Director in the Enterprise Risk Solutions group with Moody’s Analytics where he leads the risk measurement delivery team throughout the Americas. He has vast experience offering advisory services and custom quantitative risk solutions to clients. Chris has served as a credit risk instructor and is a frequent lecturer in industry conferences and organizations. He received his master’s and undergraduate degree from the University of Texas and graduated Valedictorian form the Southwestern Graduate School of Banking at Southern Methodist University.
  • Private Firm Commercial & Industrial (C&I) Credit Risk Solutions & Best Practices June 2014 Agenda 1. Credit Risk Management Challenges 2. Best Practices 3. Stress Testing Model and Approach 4. Private Firm C&I Risk Tools 5. Questions
  • Private Firm Commercial & Industrial (C&I) Credit Risk Solutions & Best Practices June 2014 C&I Credit Risk Management Challenges1
  • Private Firm Commercial & Industrial (C&I) Credit Risk Solutions & Best Practices June 2014 Challenges in Private Firm C&I Risk Management Data Quality & Availability What is the data quality? Standardized Processes Ongoing Monitoring Other Risk Drivers Credit Risk Models • Limited up to date data and ongoing availability • Data captured at origination may not be complete for ongoing data analysis • Data management is important for historical and forward looking analysis • Storing data in a single system of record for consistency • Improving operational controls by standardizing credit policies • Setting up workflow processes to ensure systematic loan origination processes • Improve credit origination decisions with accurate and predictive risk models • Leveraging risk models for capital allocation and reserve setting • Stress testing models that leverages baseline borrower risk • Early warning indictor of risk deteriorations • Dashboard reports showing borrower risk migration • Setting limits based on risk levels • Understand unexpected shifts that provide additional transparency • Incorporate qualitative factors for a comprehensive analysis How to minimize errors? What are the most effective credit risk tools? How to manage counter-party risk? What other factors should be taken into consideration?
  • Private Firm Commercial & Industrial (C&I) Credit Risk Solutions & Best Practices June 2014 Managing the multiple dimensions to stress testing Stress Testing Regulatory Requirements Firm Goals Primary, Challenger & Benchmark Model Customization Methodology “Bottom-up vs. Top-down” Asset Classes Data Availability & Quality 6
  • Private Firm Commercial & Industrial (C&I) Credit Risk Solutions & Best Practices June 2014 C&I Best Practices 2
  • Private Firm Commercial & Industrial (C&I) Credit Risk Solutions & Best Practices June 2014 » Combine financial spreading and credit analysis in one platform » Stores all data in a single system of record » Improves credit origination decisions across all asset classes » Improves operational controls by standardizing credit policies » Utilize credit risk models for underwriting and monitoring » Incorporate internal rating models Importance of statement spreading & dual risk rating
  • Private Firm Commercial & Industrial (C&I) Credit Risk Solutions & Best Practices June 2014 Identify issues before they arise thru ongoing monitoring » Understand risks in your portfolio within specific segments – View a single borrower’s performance for specific groups across your portfolio – Monitor over time for an early warning indicator and an effective approach toward risk rating – Identify outliers in a portfolio and identify key trends and insights within important segments
  • Private Firm Commercial & Industrial (C&I) Credit Risk Solutions & Best Practices June 2014 Risk monitoring and dashboards to pinpoint outliers » Probability of Default » Implied Rating » % Change » Peer Comparison » Risk Rating – high to low » Credit Committee Review Company Name 1-YearEDF Implied Rating - Moody's Previous 1-Year EDF 1-YearEDF Change Primary Industry Above 25th pctl Above Median Above 75th pctl Above 90th pctl company_name ann_edf_1yr edf_1yr_ir_mdy ann_edf_1yr primary_industry ma_id-N07067 ma_id-N04797 ma_id-N04938 ma_id-43906 ma_id-346091 ma_id-89614J ma_id-N05717 ma_id-985515 ma_id-579489 ma_id-09776J ma_id-708160 Enter Identifiers Below: Current EDF EDF Change PeerComparison - Current EDF
  • Private Firm Commercial & Industrial (C&I) Credit Risk Solutions & Best Practices June 2014 Setting risk sensitive limits » Include credit risk in the management of business limits – Pre-qualification module – Additional due diligence requirements – Pricing determination – Collateral requirements » Streamlines the decision process with clear limits and action plan – Clear approval vs. decline limits » Provide transparency behind every decision across the organization – Set limits by industry or region . Zero Limits Low Limits Medium Limits High Limits 0.02% 35.00% 0.50% 10.00% 2.00% 5.00% 1.00% 0.20% EDF 0.05% 0.10% Exposure
  • June 2014 Incorporating qualitative factors in your credit assessment Industry/Market Management Customer Power Experience in Industry Diversification of Products Financial Reporting and Formal Planning Risk Management Company Balance Sheet Factors Years in Relationship Audit Method Conduct of Account Debtor Risk/Accounts Receivable Risk Supplier Power Pro-forma Liquidity Pro-forma interest coverage
  • June 2014 Comprehensive qualitative overlay structure Qualitative Overlay Category 1 Category 2 Category n… Question 1 Question 2 Question n… Question 1 Question 2 Question n… • Option 1 • Option 2 • Option n • Option 1 • Option 2 • Option n • Option 1 • Option 2 • Option n • Option 1 • Option 2 • Option n • Option 1 • Option 2 • Option n • Option 1 • Option 2 • Option n Qualitative Score Quantitative Score Combined PD
  • Private Firm Commercial & Industrial (C&I) Credit Risk Solutions & Best Practices June 2014 Different modelling approaches to meet stress testing needs Top-Down » Inputs: — Initial PD & LGD — Sector — Debt type — Outstanding Loan Balance — Total Commitment — Macro scenarios » Modeling: — Forecasting future change based on PD level — Predict recovery rates based on debt type — Outputs: Stressed PD & LGD, expected loss, charge offs, EAD, portfolio balance, usage Bottom-Up » Inputs: — Income Statement & Balance Sheet Inputs — Linking to Macro scenarios » Modeling: — Financial ratios are linked to macroeconomic variables — Proforma Financials — Outputs: Baseline PDs vs. Stressed PDs
  • Private Firm Commercial & Industrial (C&I) Credit Risk Solutions & Best Practices June 2014 C&I Stress Testing Model and Approach3
  • Private Firm Commercial & Industrial (C&I) Credit Risk Solutions & Best Practices June 2014 Items Commonly Stressed » Income (revenues) » Expenses » Rates on interest earning assets » Rates on interest bearing liabilities » Provisions for loan losses » Balances and volumes » Non-performing loans » Charge-offs » RWAs » Capital levels (regulatory and economic) » Capital ratios Our focus for today is on the loss forecasting components of stress testing 0.00% 0.50% 1.00% 1.50% 2.00% 2.50% 3.00% Quarterly Charge-Off Rates: C&I Loans (1985-2014) Source: Federal Reserve, All Banks, NSA; NBER
  • Private Firm Commercial & Industrial (C&I) Credit Risk Solutions & Best Practices June 2014 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% LLP/NOR* LLP/PPNR** During stressed economic times, the provisions for loan losses consumes a considerable amount of revenues 37.9% 99.1% Source: FDIC (all insured institutions); NOR = Net Interest Margin + Noninterest Income. PPNR = Net Interest Margin + Noninterest Income – Non Interest Expense
  • Private Firm Commercial & Industrial (C&I) Credit Risk Solutions & Best Practices June 2014 Top-down approaches to loss estimation seek to estimate the level of NCOs for an aggregated portfolio 0.00 0.50 1.00 1.50 2.00 2.50 3.00 Quarterly Charge-Off Rates for C&I Loans (1991 – 2014) Source: Federal Reserve
  • Private Firm Commercial & Industrial (C&I) Credit Risk Solutions & Best Practices June 2014 Underwriting standards tend to be a good predictor of charge-offs, at an industry level 0.00 0.50 1.00 1.50 2.00 2.50 3.00 -40 -20 0 20 40 60 80 100 Underwriting Standards Charge-Off Rate (1 yr lag) Adj R-Squared =80% Comparison of Industry Underwriting Standards and Charge-Off Rates for C&I Loans Source: Federal Reserve
  • Private Firm Commercial & Industrial (C&I) Credit Risk Solutions & Best Practices June 2014 A credit transition matrix can be used to estimate stressed PDs from ratings linked to scenarios
  • Private Firm Commercial & Industrial (C&I) Credit Risk Solutions & Best Practices June 2014 Ultimately, our goal is to translate the relationship between scenario conditions into obligor credit risk Scenario Δ in Expected Loss Δin10-yr TreasuryYield Δin1-yearFed FundsTarget ΔinCoreGoods CPI ΔinConsumer Confidence ΔinSpecGrade Spreads ΔinNon-Farm BizProductivity Others… S1 ?        S2 ?        S3 ?        S4 ?        S5 ?        Scenario Conditions External Impacts Internal Impacts Financial Impacts Capital Impacts Δ in Probability of Default Δin10-yr TreasuryYield ΔinCorporate TaxRate Δin1-yearFed FundsTarget ΔinCoreGoods CPI ΔinWagesand Salaries ΔinConsumer Confidence ΔinSpecGrade Spreads ΔinNon-Farm BizProductivity Others…                                                             --- … … … … … … … … … • The macroeconomic variables are often drawn from those specified by the Federal Reserve in the CCAR process • Banks and the Fed alike use PD, LGD, and EAD models are used to calculate the EL – and translate those to charge-offs at the segment level • The PD for a C&I loan is projected over the planning horizon by first calculating the PD at the beginning and projecting it forward • The output is a forecast of obligor-level PDs at each quarter of the forecast horizon under a given scenario • The CCA EDF (or internal rating) is the starting point for the forecast horizon HISTORICAL DATA PREDICTIONS (Via regression model) Independent “explanatory” variables (macroeconomic factors) Regression modeled Predictions Values of macro factors from forecast scenarios ii i i XFactor εβα +∆×+=∆ ∑ ]%[% Dependent variables (credit risk measures, such as PD) FOR ILLUSTRATION
  • Private Firm Commercial & Industrial (C&I) Credit Risk Solutions & Best Practices June 2014 » The dataset was divided (CRD EDF data) into homogenous risk pools » Sector and credit risk (current EDF bucket) are identified as two main factors which have different exposures and sensitivities to macro variable shocks » The model is built by assessing impact of macro variables across each sector and EDF bucket » The model is calibrated across different PD levels using a continuous distribution of PD values Model Coefficients (Sensitivity to Macroeconomic Variables) Credit risk (EDF Bucket) Sector risk We’ve developed a “granular” stress testing methodology built upon our CRD and EDF data
  • Private Firm Commercial & Industrial (C&I) Credit Risk Solutions & Best Practices June 2014 The EDF data was divided into sectors and also rating buckets, based upon equally spaced deciles EDF Rating Buckets RiskCalc Sectors
  • Private Firm Commercial & Industrial (C&I) Credit Risk Solutions & Best Practices June 2014 Macrovariables were selected following the sector and rating segmentation process 1) Group the macroeconomic variables into similar categories (i.e., market, economic, interest rate, RE prices) 2) Univariate estimation (after transformation) 3) For each variable from #2, add a 2nd variable. Repeat with same criteria for all combinations 4) Proceed to the three-variable model (same logic) 5) Stop once the R-Squared cannot be improved, or becomes counterintuitive 6) Test candidate models (sub-sample) 7) Pick the final set Domestic CCAR Variables
  • Private Firm Commercial & Industrial (C&I) Credit Risk Solutions & Best Practices June 2014 The model’s predicted PD (four-quarter ahead) is closely aligned with the actual mean PD
  • Private Firm Commercial & Industrial (C&I) Credit Risk Solutions & Best Practices June 2014 Similarly, the predicted 9-quarter EDFs were closely aligned with the actual EDFs during the crisis period Aggregate Sector Level
  • Private Firm Commercial & Industrial (C&I) Credit Risk Solutions & Best Practices June 2014 A “ratio-based” approach is an alternative that links macroeconomic variables and financial ratiosObserveddefaultrate Low High Low High Liquidity Ratio Observeddefaultrate Low High Low High Leverage • Each level of a ratio is associated with a different default rate • If the ratio level changes, so does its PD Percentile Score Percentile Score
  • Private Firm Commercial & Industrial (C&I) Credit Risk Solutions & Best Practices June 2014 » Similar to the “granular” approach, the model is built using domestic Fed CCAR variables, the CRD, and EDFs » The model can also be applied to the additional scenarios » Different financial statement inputs behave different under different stress scenarios, which translate into a wide variation in EDFs » Income statement items (more responsive) are linked to macrovariables and used to generate pro forma financial statements » The median for each ratio is derived for each year, state, and sector - which is evaluated to assess which are most responsive to key macrovariables (i.e., GDP, Unemployment, etc.) - Sales Growth - Cost of Goods Sold (“COGS”) - SG&A Expenses - Interest Expense/Total Liabilities The “ratio-based” model follows a bottom-up approach at the financial statement ratio level Changes in macrovariables flow to the balance sheet through line items in the income statement
  • Private Firm Commercial & Industrial (C&I) Credit Risk Solutions & Best Practices June 2014 Once the relationship with economic variables is established, a pro-forma income statement is created Income Statement Sales/Revenue -Cost of Goods Sold (COGS) -Selling, General and Administrative Expense (SGA) -Depreciation/Amortization (AMORT) -Other Operating Expense (OthrExp) Total Operating Profit +Financial Income -Interest Expenses Profit before Tax -Tax Net Income Responds to the Cycle Responds to Interest Rates Variable costs such as Cost of Goods Sold move together with changes in Sales. Fixed costs, such as Depreciation/Amortization move slowly when Sales decrease. Sales Growth COGS Changes SGA Changes Interest Expense Changes
  • Private Firm Commercial & Industrial (C&I) Credit Risk Solutions & Best Practices June 2014 » To be consistent across the four dependent variable models, we selected macrovariables that are uniform and also statistically significant for the dependent variables (i.e., financial ratios) » Separate models are fit for each sector, resulting in three groups - Group 1 (11): Agriculture, Business Products, Business Services, Communication, Consumer Products, HiTech, Mining, Services, Trade, Transportation, and Unassigned - Group 2 (2): Healthcare and Utilities - Group 3 (1): Construction The model starts with the four financial ratios to build the pro forma FSO EDF, then adjusts for the credit cycle Final Set of Macroeconomic Variables Stressed EDF = F(Pro Forma FSO EDF x CCA Factor)
  • Private Firm Commercial & Industrial (C&I) Credit Risk Solutions & Best Practices June 2014 The response to changes in macroeconomic variables varies by sector Final Set of Macroeconomic Variables (CCA Factor) Agriculture & Transportation are sensitive to the WTI Index Construction is sensitive to the HPI Unemployment affects all sectors, - albeit differently
  • Private Firm Commercial & Industrial (C&I) Credit Risk Solutions & Best Practices June 2014 The aggregate and predicted Stressed EDF closely follows the time series of the Actual EDF Example of Sector Level Validation
  • Private Firm Commercial & Industrial (C&I) Credit Risk Solutions & Best Practices June 2014 Forecasting stressed LGDs often involves incorporating macrovariables directly into an LGD model » Primary data source was Moody’s Default & Recovery Database (“DRD”), which grew out of the Moody’s Annual Default Studies, used to assess ratings’ performance » We use the DRD to obtain recovery data, sector classifications, loan types. We also supplement the DRD data with PDs from our Public Firm model and a time series of macroeconomic variables (e.g., DJ Index, VIX) » The macro variables consist of stationary transformations of domestic CCAR variables. These are the same variables used in the PD stress testing model 0 10 20 30 40 50 60 70 80 RecoveryPrice Actual vs Predicted Avg. Recovery (365-Day Rolling Window) Recovery Price Model Predicted Recovery Price
  • Private Firm Commercial & Industrial (C&I) Credit Risk Solutions & Best Practices June 2014 The loss emergence period is the time from when default occurs until the time when the loss is realized • The appropriate level of ALLL at the end of a given quarter is generally assumed to be the amount needed to cover projected loan losses over the next four quarters. • LLPs will equal the projected NCOs for the quarter plus the amount needed for the ALLL to be at an appropriate level at the end of the quarter, which is a function of projected future NCOs.Source: Moody’s The Fed models project losses in the accrual using detailed loan portfolio data provided by the BHCs on the FR Y-14 report.
  • Private Firm Commercial & Industrial (C&I) Credit Risk Solutions & Best Practices June 2014 With a forecast of quarterly NCOs, we can quantify the provisions to the ALLL and the impact on capital
  • Private Firm Commercial & Industrial (C&I) Credit Risk Solutions & Best Practices June 2014 C&I Risk Tools 4
  • Private Firm Commercial & Industrial (C&I) Credit Risk Solutions & Best Practices June 2014 RiskAnalyst™ software has wide industry coverage for financial statement data collection needs » Minimize data entry errors by using industry specific data templates » Meet your specific business objectives with the flexibility to change templates or add new templates » Integrate with credit risk assessment models » Utilize off the shelf or customized internal rating models Data
  • Private Firm Commercial & Industrial (C&I) Credit Risk Solutions & Best Practices June 2014 RiskCalc Plus Global Presence: Network of 29 World-Class Models The RiskCalc Plus network is comprised of unique models covering: Americas: USA, Canada and Mexico country models, plus U.S. Insurance, U.S. Banks and North America Large Firm Europe, Middle East and Africa: Austria, France, Netherlands, Nordic (Denmark, Norway, Sweden, Finland), Portugal, Spain, UK, Germany, Belgium, Italy, South Africa, Switzerland, Russia, Banks Asia Pacific: Japan, Korea, Australia, Singapore, China, Banks Other: Emerging Markets 12 Million Unique Private Firms 50 Million Financial Statements 800,000 Defaults Worldwide RiskCalc™: Credit Research Database (CRD™) The largest financial statement and default database in the world
  • Private Firm Commercial & Industrial (C&I) Credit Risk Solutions & Best Practices June 2014 Collect Financials and Default Data Select Relevant Ratios Compute the Model Output Calibrate the Model Output to Actual Defaults: Financial Statement Only (FSO) EDF™ (Expected Default Frequency) Incorporate a market signal to determine the Credit Cycle Adjusted (CCA) EDF 1 2 3 4 5 RiskCalc Modeling Process
  • Private Firm Commercial & Industrial (C&I) Credit Risk Solutions & Best Practices June 2014 Expected Default Frequency (EDF) - Output 40 EDF Credit Measure is in the highest percentile and mapped to the most risky implied rating
  • Private Firm Commercial & Industrial (C&I) Credit Risk Solutions & Best Practices June 2014 Relative Contributions depict risk drivers 41 Ratio drivers point out many weaknesses firms financials
  • Compare a borrower against a peer group for additional transparency Private Firm Commercial & Industrial (C&I) Credit Risk Solutions & Best Practices June 2014
  • Private Firm Commercial & Industrial (C&I) Credit Risk Solutions & Best Practices June 2014 Incorporating Qualitative Overlay Assessment
  • June 2014 RiskCalc Stress testing – Two different approaches RiskCalc PD&LGD Based Approach (Granular Modeling) » Access: — Via Scenario Analyzer or Custom Delivery » Data: — Credit Research Database (CRD) — Default & Recovery Database (DRD) » Inputs: — Initial PD & LGD — Sector — Debt type (secured loans, unsecured loans or revolvers) — Macro scenarios — Outstanding Loan Balance — Total Commitment » Modeling: » Calibrated on RiskCalc US 4.0 — PD: Forecasting future change based on PD level, sector and forecasted macro scenarios — LGD: Predict recovery rates based on debt type, sector, stressed PD levels and macro scenarios » Output: — Stressed PD & LGD, expected loss, charge offs, EAD, portfolio balance, usage RiskCalc Ratio Based Approach (Obligor-Level Modeling) » Access: — Via RiskCalc Plus website single, batch & XML » Data: — Credit Research Database (CRD) » Inputs: — RiskCalc US 4.0 Corporate Income Statement & Balance Sheet Inputs — Macro scenarios » Modeling: — Financial ratios are linked to macroeconomic variables — CCA “credit cycle adjusted” view for forecasted EDFs under stressed scenarios » Output: — Two years of pro-forma financials — Baseline EDF and Stressed EDF Private Firm Commercial & Industrial (C&I) Credit Risk Solutions & Best Practices
  • Spread, Store, Score, Origination & Stress Testing Needs Financial Analysis  Data Templates in RiskAnalyst & RiskOrigins software Data Collection  Consistent  Single Source spreading software – RiskAnalyst™ & RiskOrigins™ software Scorecards  Dual Risk Rating including PD, LGD & EL  Credit risk scores combined with qualitative factors producing ratings C&I & CRE Scoring  RiskCalc™ Private Firms  CreditEdge™ Public Firms Stress Testing Solutions  Dashboard  Portfolio Reports  Stress Testing Models by Asset Class Private Firm Commercial & Industrial (C&I) Credit Risk Solutions & Best Practices June 2014
  • Private Firm Commercial & Industrial (C&I) Credit Risk Solutions & Best Practices June 2014 Questions 5
  • Private Firm Commercial & Industrial (C&I) Credit Risk Solutions & Best Practices June 2014 Thank you
  • Private Firm Commercial & Industrial (C&I) Credit Risk Solutions & Best Practices June 2014 © 2014 Moody’s Corporation, Moody’s Investors Service, Inc., Moody’s Analytics, Inc. and/or their licensors and affiliates (collectively, “MOODY’S”). All rights reserved. CREDIT RATINGS ISSUED BY MOODY'S INVESTORS SERVICE, INC. (“MIS”) AND ITS AFFILIATES ARE MOODY’S CURRENT OPINIONS OF THE RELATIVE FUTURE CREDIT RISK OF ENTITIES, CREDIT COMMITMENTS, OR DEBT OR DEBT-LIKE SECURITIES, AND CREDIT RATINGS AND RESEARCH PUBLICATIONS PUBLISHED BY MOODY’S (“MOODY’S PUBLICATIONS”) MAY INCLUDE MOODY’S CURRENT OPINIONS OF THE RELATIVE FUTURE CREDIT RISK OF ENTITIES, CREDIT COMMITMENTS, OR DEBT OR DEBT-LIKE SECURITIES. MOODY’S DEFINES CREDIT RISK AS THE RISK THAT AN ENTITY MAY NOT MEET ITS CONTRACTUAL, FINANCIAL OBLIGATIONS AS THEY COME DUE AND ANY ESTIMATED FINANCIAL LOSS IN THE EVENT OF DEFAULT. 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