CECL: Adapting to Adopt

CECL: Adapting to Adopt Chris Henkel, Senior Director, Advisory Services Anna Krayn, Senior Director, Regulatory & Accounting Solutions April 2018

Speakers Christian Henkel Senior Director Advisory Services Anna Krayn Senior Director Risk & Accounting Solutions Americas» Based in New York City, Chris leads a global team of risk consultants who work closely with banks, insurers, and other financial institutions» Has 20+ years experience in commercial banking including expertise in risk modeling, allowance for credit loss quantification, stress testing, and portfolio management.» Has a BA and an MBA from the University of Texas with concentrations in Finance and Accounting» Graduated valedictorian from the Southwestern Graduate School of Banking at Southern Methodist University, where he also served as a credit risk management instructor» Leads team responsible for solution structuring across Moody s Analytics products and services focusing on impairment, stress testing, and capital planning solutions for financial institutions» Advisory services experience as an engagement manager leading projects with financial institutions across the Americas in loss estimation, enhancements in internal risk rating capabilities, and counterparty credit risk management.» Was a rating analyst with Moody s Investors Service before joining Moody s Analytics in 2008» Holds Bachelor of Science degree in finance and international business and MBA from Stern School of Business at New York University (NYU) Adapting to Adopt, April 2018 2

Agenda 1. State of the Industry 2. Deriving ECL Measures for Community Banks 3. The Ultimate Test of the Approach Adapting to Adopt, April 2018 3

1 State of the Industry

Where are we starting from? A Word on Incurred Loss Approach Today Loss Rate Method Typical ALLL at a Community Bank Reliant on Recent Loss Experience Focus on Individual Impairments No Linkage to Credit Risk Management Adapting to Adopt, April 2018 5

Complexity Scaled to Sophistication. Simplicity is always great until it gives you the wrong answer or someone asks a simple question you can t answer! When the answer drives decisions towards bonuses, dividends, and raising capital, the stakes can be high! Michael Gullette American Bank ers Association Adapting to Adopt, April 2018 6

Emphasizing Simplicity Loss Rate Static Pools Loss Rate Vintage Roll Rate and Migration PD / LGD Credit Risk Management Journey Adapting to Adopt, April 2018 7

2 Deriving ECL Measures for Community Banks

1991Q1 1991Q3 1992Q1 1992Q3 1993Q1 1993Q3 1994Q1 1994Q3 1995Q1 1995Q3 1996Q1 1996Q3 1997Q1 1997Q3 1998Q1 1998Q3 1999Q1 1999Q3 2000Q1 2000Q3 2001Q1 2001Q3 2002Q1 2002Q3 2003Q1 2003Q3 2004Q1 2004Q3 2005Q1 2005Q3 2006Q1 2006Q3 2007Q1 2007Q3 2008Q1 2008Q3 2009Q1 2009Q3 2010Q1 2010Q3 2011Q1 2011Q3 2012Q1 2012Q3 2013Q1 2013Q3 2014Q1 2014Q3 2015Q1 2015Q3 2016Q1 2016Q3 2017Q1 2017Q3 ROA Reserves for credit losses impact profitability 2.50% ROA and Reserves/Loans (1991-2017) 2.00% 1.50% 1.00% 0.50% Reserves/Loans 0.00% -0.50% Source: FDIC -1.00% Quarterly ROA Reserves to Total Loans & Leases Adapting to Adopt, April 2018 9

1991Q1 1991Q3 1992Q1 1992Q3 1993Q1 1993Q3 1994Q1 1994Q3 1995Q1 1995Q3 1996Q1 1996Q3 1997Q1 1997Q3 1998Q1 1998Q3 1999Q1 1999Q3 2000Q1 2000Q3 2001Q1 2001Q3 2002Q1 2002Q3 2003Q1 2003Q3 2004Q1 2004Q3 2005Q1 2005Q3 2006Q1 2006Q3 2007Q1 2007Q3 2008Q1 2008Q3 2009Q1 2009Q3 2010Q1 2010Q3 2011Q1 2011Q3 2012Q1 2012Q3 2013Q1 2013Q3 2014Q1 2014Q3 2015Q1 2015Q3 2016Q1 2016Q3 2017Q1 2017Q3 There is a greater need for operational efficiencies to improve profitability 6.00 5.00 Average Assets Per Employee ($ Millions) $5.3 million 4.00 3.00 $2.2 million 2.00 1.00 0.00 Source: FDIC Adapting to Adopt, April 2018 10

2006Q1 2006Q2 2006Q3 2006Q4 2007Q1 2007Q2 2007Q3 2007Q4 2008Q1 2008Q2 2008Q3 2008Q4 2009Q1 2009Q2 2009Q3 2009Q4 2010Q1 2010Q2 2010Q3 2010Q4 2011Q1 2011Q2 2011Q3 2011Q4 2012Q1 2012Q2 2012Q3 2012Q4 2013Q1 2013Q2 2013Q3 2013Q4 2014Q1 2014Q2 2014Q3 2014Q4 2015Q1 2015Q2 2015Q3 2015Q4 2016Q1 2016Q2 2016Q3 2016Q4 2017Q1 2017Q2 2017Q3 2017Q4 One-third of community bank assets have maturities greater than five years 40% Long-Term (> 5 Years) Assets to Total Assets 35% 30% 33% 25% 20% 15% 19% 10% 5% 0% Source: FDIC Adapting to Adopt, April 2018 11

Projected Annual Net Charge-Offs and you need hold reserves over the remaining contractual life of each loan/segment Consideration of Horizon in Assessing Expected Credit Losses ( ECL ) Life of Loan ECL Visibility into Future 2.10% 3.50% 1.25% 0.60% 0.25% 2018 2019 2020 2021 2022 How you get there can take a variety of paths, and it will likely vary by asset class/segment Adapting to Adopt, April 2018 12

For most community banks, using a loss rate approach is the most sensible option Segment-Level ECL Illustration ECL Historical Segment-level Loss Experience Current Conditions and Forecast Variables = +/- x NCO Rate Qualitative Adjustment Outstanding Loan Balance / Amortized Cost Exposure Expected Credit Loss ($) Net Charge Offs (%) Add / Subt.(%) Exposure Amount ($) Calculating Lifetime NCOs, methods:» Annual NCO x Remaining Life» Cumulative NCO / Portfolio Balance (total NCO from of a snapshot of the portfolio until disposition)» Cumulative NCO / Portfolio Balance (total NCO from loans originated in each year) Qualitative Adjustment Factors, examples» Predictive economic variables (e.g., commodity prices, rents, unemployment rate)» Use past experience and judgment to quantify the impact» Basis points (%) are added or subtracted to reflect current conditions and forecasts» A comprehensive narrative is essential for disclosure requirements Adapting to Adopt, April 2018 13

For many community banks, using a loss rate approach is the most sensible option Segment-Level ECL Illustration ECL Historical Segment-level Loss Experience Current Conditions and Forecast Variables = +/- x NCOs Qualitative Adjustment Outstanding Loan Balance / Amortized Cost Exposure Expected Credit Loss ($) $30 thousand Net Charge Offs (%) Annual: 0.75% Add / Subt.(%) Current Conditions: - 0.25% Forecast Conditions: - 0.25% Qual. Adjustment: - 0.50% Exposure Amount ($) $1 million ($1MM x 3.00%) Lifetime: 3.50% ECL %: 3.00% Adapting to Adopt, April 2018 14

Data requirements depend upon segmentation and ECL methodology; will vary by segment EXAMPLES» Segmentation criteria/identifier (e.g., borrower NAICS code, Call Report code)» Segment-level historical losses (own, peer, 3 rd party)» Origination date and maturity» Exposure amount for each loan/segment (including paydowns and pre-payment assumptions)» Loan product type (e.g., RLOC for ABL facilities)» Collateral/asset type» Credit risk metrics (usually scorecard/risk rating factors)» Economic variables (segment-specific) and forecasts» Risk ratings (if and accurate and providing risk differentiation) Adapting to Adopt, April 2018 15

% of loans A quick word on risk ratings 45 40 35 Risk Rating Distribution (10-point scale) Good Not Good 30 25 20 15 10 5 0 1 2 3 4 5 6 7 8 9 10 Risk Rating Adapting to Adopt, April 2018 16

Thinking about dual risk ratings? Then a PD/LGD approach might be right for you Adapting to Adopt, April 2018 17

Illustration of a PD Scorecard Risk Rating Scorecard Internal PD Rating Scale Financial Ratios Qualitative Factors Quantitative Risk Measures Qualitative Score (0 100) Rating Year 1 Year 2 Year 3 Year 4 Year 5 1 0.15 0.49 0.91 1.32 1.75 2 0.43 1.11 1.95 2.81 3.56 3 0.89 2.49 4.39 6.45 8.17 Total Score Borrower Rating 4 1.54 4.12 6.93 9.59 12.28 5 2.67 6.78 10.88 14.66 17.86 6 4.10 8.90 13.67 17.70 21.46In this example, a 5 7 6.85 15.87 24.26 31.37 37.45rated loan has a ~15% cumulative probability 8 10.84 19.53 27.03 33.74 39.01of default ( PD ) 9 35.00 54.98 68.30 76.69 84.57 10 100.00 100.00 100.00 100.00 100.00 Adapting to Adopt, April 2018 18

On average, the amount we could potentially lose depends on four things ECL how likely the borrower is to go into default the estimate of loss (1-recovery) should default occur = x x the exposure amount at the time of default PD LGD Exposure rate used to discount future cash flows x Discount Factor Expected Credit Loss ($) Probability of Default (%) Loss Given Default (%) Exposure Amount ($) Discount Rate (%)» Lifetime: present value of all cash shortfalls expected over the remaining life of instrument» 12-month: portion of lifetime ECL associated with probability of a default occurring in next 12 months Adapting to Adopt, April 2018 19

» Point-in-Time PD required» PDs needs to be extrapolated over the remaining expected lifetime of the asset» Must consider reasonable and supportable forwardlooking information On average, the amount we could potentially lose depends on four things ECL how likely the borrower is to go into default the estimate of loss (1-recovery) should default occur = x x the exposure amount at the time of default PD LGD Exposure rate used to discount future cash flows x Discount Factor Expected Credit Loss ($) Probability of Default (%) Loss Given Default (%) Exposure Amount ($) Discount Rate (%) Adapting to Adopt, April 2018 20

On average, the amount we could potentially lose depends on four things ECL how likely the borrower is to go into default the estimate of loss (1-recovery) should default occur = x x the exposure amount at the time of default PD LGD Exposure rate used to discount future cash flows x Discount Factor Expected Credit Loss ($) Probability of Default (%) Loss Given Default (%) Exposure Amount ($) Discount Rate (%)» Point-in-time LGD required; not downturn LGD» Only costs directly attributable to the collection of recoveries (remove the collective cost in BASEL LGD)» Must consider reasonable and supportable forwardlooking information Adapting to Adopt, April 2018 21

» Cash-flows through the lifetime of the asset» Consider all contractual terms (e.g. prepayment, usage, call and similar options) over the lifetime On average, the amount we could potentially lose depends on four things ECL how likely the borrower is to go into default the estimate of loss (1-recovery) should default occur = x x the exposure amount at the time of default PD LGD Exposure rate used to discount future cash flows x Discount Factor Expected Credit Loss ($) Probability of Default (%) Loss Given Default (%) Exposure Amount ($) Discount Rate (%) Adapting to Adopt, April 2018 22

On average, the amount we could potentially lose depends on four things ECL how likely the borrower is to go into default the estimate of loss (1-recovery) should default occur = x x the exposure amount at the time of default PD LGD Exposure rate used to discount future cash flows x Discount Factor Expected Credit Loss ($) Probability of Default (%) Loss Given Default (%) Exposure Amount ($) Discount Rate (%)» Discount factor calculated through current market rate or Effective interest rate (EIR) method Adapting to Adopt, April 2018 23

Spectrum of risk rating methodologies (for the ACL) General observations of commercial credit practices at US banks Community Banks Regional Banks National Banks Global Banks Total Assets: < $1 billion $5 billion $10 billion $50 billion $100 billion $500 billion > $1 trillion Pass / Non-Pass Subjective Ratings (e.g.,1-10 scale) Expert driven PDs and LGD scorecards Vended models as statistical input into PD/LGD scorecards (also includes judgmentallyderived risk factors) PD and LGD models using internal data/experience (also includes judgmentallyderived risk factors) PD and LGD models using internal data/experience Adapting to Adopt, April 2018 24

3 The Ultimate Test

Text Can You Explain Your Results? Questions CECL Solution Needs to Answer Initial Implementation How? Ongoing Process What? Why?» Data Management» Estimation Methodology» Critical Assumptions» Reporting» Controls and Governance» Execution» Qtr over Qtr Change» Impact on Reserves» Drivers of ECL» Market Conditions» Portfolio Composition» Underwriting Changes Text» Forecasts» Volume» Activity» Originations» Migrations Adapting to Adopt, April 2018 26

Banker s CECL Implementation Modus Operandi 1 2 3 Improve already lean operations. Adopt a holistic approach to implementation. Comply, communicate, compete Identify and institutionalize factors that drive risk in your portfolio. CECL helps to manage and communicate credit risk inherent in the portfolio Apply modern technology. Analyze the various aspects of lifetime credit risks within the current reporting timeframes Adapting to Adopt, April 2018 27

How to Get Compliant Now Get an estimate of an Estimate now Wrap an estimate into ICFR framework Compare different approaches Produce disclosures Execute multiple period parallel runs Adapting to Adopt, April 2018 28

Allowance Calculation as an Advantage Banks that can demonstrate how certain borrowers present lower credit risk will record less ALLL at origination, increasing the relative amount of deployable capital. Banks that are able to better monitor loss expectations by credit rating and term may be able to better price these factors into their products over time. American Bank ers Association Backgrounder: CECL June 2016 Adapting to Adopt, April 2018 29

Christian Henkel Senior Director Christian.Henkel@moodys.com +1 (212) 553-4679 Robby Holditch Director Robby.Holditch@moodys.com +1 (212) 553-2119 Anna Krayn Senior Director Anna.Krayn@moodys.com +1 (212) 553-3705 moodysanalytics.com

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