discounted cash flow methodology for banks and credit unions

Sageworksanalyst.com

Discounted Cash Flow (DCF) Modelingfor Credit Loss Reserves and Other Applications

Garver MoorePrincipal - Advisory Services


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Disclaimer

This presentation may include statements that constitute “forward-looking statements” relative to publicly available industry data. Forward-looking statements often contain words such as “believe,” “expect,” “plans,” “project,” “target,” “anticipate,” “will,” “should,” “see,” “guidance,” “confident” and similar terms. There can be no assurance that any of the future events discussed will occur as anticipated, if at all, or that actual results on the industry will be as expected. Sageworks is not responsible for the accuracy or validity of this publicly available industry data, or the outcome of the use of this data relative to business or investment decisions made by the recipients of this data. Sageworks disclaims all representations and warranties, express or implied. Risks and uncertainties include risks related to the effect of economic conditions and financial market conditions; fluctuation in commodity prices, interest rates and foreign currency exchange rates. No Sageworks employee is authorized to make recommendations or give advice as to any course of action that should be made as an outcome of this data. The forward-looking statements and data speak only as of the date of this presentation and we undertake no obligation to update or revise this information as of a later date.

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P O R T F O L I O M A N A G E M E N T S E R V I C E S

Services Include

• Model Transition and Validation

Services

• CECL Transition Services

• Prepayment, Curtailment, Funding,

and Cash Flow modeling

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End in Mind

At the conclusion of this discussion, participants should:

• Understand the unique considerations of a discounted cash flow (DCF) analysis

• Understand the limitations of a sampling approach

• Believe DCF can be a solution when life-of-loan data is not available

• Understand the unique timing and component nature of DCF analysis

• Be able to speak to the elections required in a DCF analysis

• Understand the inferential approaches used in producing a DCF analysis

• Understand open areas of uncertainty

• Consider cross-applicability of measurement methodology


Poll Question


Agenda

• “Generative” v. “Look-Back” models

• Discounted cash flow principles

• Sampling vs. Bottom-Up

• Timing and Component Estimations

• Volatility in Measurement

• Current Conditions and Forecasting

• Individual Analysis

• Policy Considerations

• Other Applications


Warning: Software Ahead

Computationally Intensive

Data IntensiveMore Less

MoreLess





MoreLess

Closed Pool Analysis





MoreLess

Closed Pool Analysis Vintage Analysis





MoreLess

Closed Pool Analysis Vintage Analysis Markov/Transition





MoreLess

Closed Pool Analysis Vintage Analysis DCFMarkov/Transition


Generative vs. Look-Back



MoreLess

Closed Pool Analysis Vintage Analysis DCFMarkov


Generative vs. Look-Back



MoreLess

Closed Pool Analysis Vintage Analysis DCFMarkov

Retrospective Generative

Longer history of data Shorter history of data

Period-driven Parameter-driven

Requires adjusting to current conditions “Snaps” to current conditions

Computationally straightforward Computationally complex

Include/exclude periods to adjust Adjust parameters directly


DCF Principles I

• Model cashflows in the future on a per-loan (bottom up) basis• Include credit assumptions (defaulted principal, unrecovered principal)• Use periodic, not lifetime parameters in estimation• Parameters can be time-bound

• Vintage/seasoning sensitive• Model date-sensitive

• Key Parameters:• Periodic default tendency• Recovery delay• Loss given default• Prepayment rate (Amortizing)• Curtailment rate (Revolving)

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DCF Principles I


• Vintage/seasoning sensitive• Model date sensitive


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DCF Principles I


• Vintage/seasoning sensitive• Model date sensitive


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DCF Principles II

• Model takes into account:• Seasoning / blend of loan maturities

• Structure

• Adjustments for current conditions

• Prepayments

• Discount Rate(s):• If available, effective yield

• Coupon rate

• Should not be forecast for variable-rate assets

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DCF Principles III

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Parameter Description Lines/Revolvers Amortizing

Curtailment Rate Periodic tendency of an extended principal dollar to be returned to you.

Applicable Not Applicable

Funding Rate Periodic tendency of an undrawn dollar to be drawn


Prepayment Speed

Periodic tendency to receive unexpected principal payments

Not Applicable Applicable

Default Rate Periodic tendency of a loan to enter default state.

Applicable Applicable

Loss Given Default

Static loss on a loan, conditional to default event.


Recovery Delay Static time between default event and resolution (recovery or loss)



DCF Principles III

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Parameter Description Lines/Revolvers Amortizing

Curtailment Rate Periodic tendency of an extended principal dollar to be returned to you.


Funding Rate Periodic tendency of an undrawn dollar to be drawn


Prepayment Speed

Periodic tendency to receive unexpected principal payments

Not Applicable Applicable

Default Rate Periodic tendency of a loan to enter default state.


Loss Given Default

Static loss on a loan, conditional to default event.


Recovery Delay Static time between default event and resolution (recovery or loss)



Curtailment Rate Measurement Example (or funding)

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Curtailment Rate Measurement Example

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Generative vs. Look Back (Redux)

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We obtain this distribution with 4 quarters of loan detail


Sampling vs. Bottom-Up

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• Sampling:• Cash-flow some subset (~10%) of randomly sampled loans in a segment

• Churn sample period-to-period

• Arrive at a sampled rate

• Bottom-Up:• Cash-flow portfolio at loan level

• Arrive at population rate



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• Sampling:• Cash-flow some subset (~10%) of randomly sampled loans in a

segment





Volatility Issues



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• Sampling:• Cash-flow some subset (~10%) of randomly sampled loans in a segment





Volatility Reflects Portfolio


Timing and Component Estimation

• Cash from Expected Principal• Contract Payments (Amortizing)

• Curtailment (Lines)

• Cash from Interest• Contract Interest (Amortizing and Lines)

• Unexpected Principal (Prepayments)

• Cash from Recovered Defaults (Principal)

• Defaulted Principal• Defaulted Interest Not Received

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Sageworksanalyst.com 30

Timing and Component Estimation

DCF analysis produces a time-sensitive projection of component

cashflows


Volatility in the Allowance

• Depends on: methodology• Look-back versus Look-forward

• Trivially, look-forward more volatile

• Emergent vs. Intrinsic Volatility:• Emergent: Due to mathematical properties of the model

• Intrinsic: Due to mathematical properties of the subject being modeled (credit loss expectations)

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Volatility in the Allowance

• Depends on: methodology• Look-back versus Look-forward

• Trivially, look-forward more volatile

• Emergent vs. Intrinsic Volatility:• Emergent: Due to mathematical properties of the model

• Example: High-impact quarter rolls off analysis

• Intrinsic: Due to mathematical properties of the subject being modeled (credit loss expectations)

• Example: Uptick in prepayment activity

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Example: Rocket Bank CRE NOO Organic

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Example: Present versus elevated LGD

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Present Conditions



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Present Conditions



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Elevated LGD Conditions



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38

Elevated LGD Conditions



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Example: Elevated LGD, elevated curtailment

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42Elevated Curtailment Conditions



43Elevated Curtailment Conditions


Example: Elevated LGD, Elevated Curtailment

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Elevated Curtailment Conditions


Example: Moderate to Severe PD climb

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46



47



48

+1 %



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+1 % +2 %



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Poll Question

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Q&A

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The Roll-Forward of a NPV Estimation

• We have timed, componentized estimations.

• Immediately sensitive to:• Loan maturities/terms

• Parameter estimates

• These are projections

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• Periodic changes in NPV due to:• Timing

• Credit

• New Loans

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• Periodic changes in NPV due to:• Timing

• May disclose and recognize as interest

income

• Credit• Provision expense

• New Loans• Provision expense

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• When projections are long (short):• Tune parameter?

• Evaluate market changes since parameter

was estimated

• Evaluate confidence in projection

• Evaluate statistical confidence in

parameter

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Time Sensitivity II: Forecasting

• Our projection is time-sensitive

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• Our model inputs can be time-sensitive, too

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• Immediately clarifies how to apply reasonable and supportable forecasts

• Even how to “Revert” for periods beyond our forecastable window

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• Immediately clarifies how to apply reasonable and supportable forecasts

• Even how to “Revert” for periods beyond our forecastable window

• We can also include other time-bound elements in our projection, for example:

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Origination Year 1 2 3 4 5 6 Total Loss Remaining Loss

12/31/2010 0.40% 1.10% 0.60% 0.25% 0.01% 0.03% 2.39% 0.00%

12/31/2011 0.25% 0.85% 1.25% 0.40% 0.06% 0.03% 2.84% 0.03%

12/31/2012 1.25% 0.95% 0.75% 0.06% 0.04% 0.03% 3.08% 0.07%

12/31/2013 0.75% 0.65% 0.40% 0.24% 0.04% 0.03% 2.10% 0.30%

12/31/2014 0.20% 0.60% 0.75% 0.24% 0.04% 0.03% 1.85% 1.05%

12/31/2015 0.30% 0.83% 0.75% 0.24% 0.04% 0.03% 2.18% 1.88%

Average 0.53% 0.83% 0.75% 0.24% 0.04% 0.03% 2.41%

Loss Rate – Year Subsequent to Origination

Loss curve

Vintage Analysis


We can map indicators to losses…

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5 Factors Unemployment


And source forecasts…

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2010 Federal Reserve Forecast

2016 Federal Reserve Forecast

Adjustment Indicated

Current Conditions?


… and thereby apply them to our parameters

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Individual Analysis

• Standard does not require specific impairment expectation

• Different credit characteristics:• Past Due Mature / Administrative Past Due• Exotic payment streams


Considerations

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• “Balloon at maturity” assumptions

• Reliability of P&I expectations from reporting systems• Use of inferential systems to model P&I behavior

• Amortization of fees, etc.


Considerations

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• “Balloon at maturity” assumptions

• Reliability of P&I expectations from reporting systems• Use of inferential systems to model P&I behavior

• Amortization of fees, etc.

• What to do with all that data?


Loan-Level Results

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Loan-Level Results

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Loan-Level Results

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Other Applications

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• We have a schedule of cashflows, adjusted for credit and timing behavior

• We are discounting by e.g. coupon in our expected loss analysis.

• What if we discount buildup by• Cost of Funds + ROA/ROE Target?• Opportunity cost?


Other Applications

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Loan Number GL Balance Cash Flow NPV (CECL) NPV (Pricing) NPV (Exit Price) IRR PD LGD

12137713 250,000 281,292 (4,074) (0) (5,679) 3.87% 3.00% 15.00%

Beginning Balance Principal Interest Prepayment Defaulted Principal Estimated Loss Estimated RecoveryEnd of Month

Balance Fees/(Expenses) Cash Flow

250,000 146,631 34,804 79,955 23,414 3,512 19,902 (342) 281,292

(250,000) 1,700.00 (250,000)

250,000 975 942 2,180 634 95 - 246,212 - 4,097

246,212 989 928 2,147 624 94 - 242,452 - 4,064

242,452 1,003 914 2,114 615 92 - 238,720 - 4,031

238,720 1,017 900 2,082 605 91 - 235,016 - 3,998

235,016 1,031 886 2,049 596 89 - 231,340 - 3,966

231,340 1,045 872 2,017 586 88 - 227,691 - 3,934

227,691 1,059 858 1,985 577 87 - 224,070 - 3,902

224,070 1,072 844 1,954 568 85 - 220,476 - 3,871

220,476 1,086 831 1,922 559 84 - 216,908 - 3,839

216,908 1,099 817 1,891 550 82 - 213,368 - 3,808


Other Applications

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12137713 250,000 281,292 (4,074) (0) (5,679) 3.87% 3.00% 15.00%

Beginning Balance Principal Interest Prepayment Defaulted Principal Estimated Loss Estimated Recovery End of Month Balance Fees/(Expenses) Cash Flow

250,000 146,631 34,804 79,955 23,414 3,512 19,902 (342) 281,292

(250,000) 1,700.00 (250,000)

250,000 975 942 2,180 634 95 - 246,212 - 4,097

246,212 989 928 2,147 624 94 - 242,452 - 4,064

242,452 1,003 914 2,114 615 92 - 238,720 - 4,031

238,720 1,017 900 2,082 605 91 - 235,016 - 3,998

235,016 1,031 886 2,049 596 89 - 231,340 - 3,966

231,340 1,045 872 2,017 586 88 - 227,691 - 3,934

227,691 1,059 858 1,985 577 87 - 224,070 - 3,902

224,070 1,072 844 1,954 568 85 - 220,476 - 3,871

220,476 1,086 831 1,922 559 84 - 216,908 - 3,839

216,908 1,099 817 1,891 550 82 - 213,368 - 3,808


Example – NPV (Discounted Cash Flow)

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12137713 250,000 281,292 (4,074) (0) (5,679) 3.87% 3.00% 15.00%


12137713 250,000 283,118 (4,300) (122) (6,113) 3.86% 3.00% 15.00%

• Prepayment behavior or expectation can have a significant impact on the profitability of a loan

• In the above example, a simple reduction in prepayment behavior from 10% CPR to 8% CPR would result in under-performance relative to institutional targets

• This relationship is not linear. Interest rates exceeding x% will experience an improvement in performance as prepayments slow, while interest rates below x% will experience declining profitability

• There is a certain period of time that is required in order to recover origination costs and overhead allocation


Example – NPV (Discounted Cash Flow)

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12137713 250,000 281,292 (4,074) (0) (5,679) 3.87% 3.00% 15.00%

• Although both scenarios include a 45bps loss rate, the relationship between default (lost interest) and realized loss certainly matters from a pricing decision under an NPV approach.


12137713 250,000 279,562 (4,565) (536) (6,034) 3.80% 5.00% 9.00%


Segment GL Balance PV Reserve Reserve % NPV (Effective Yield) NPV (Pricing) NPV (Exit Price)

Real Estate Other 365 - 365 - Fixed 6,764,709 6,718,898 45,811 0.68% (45,600) 43,155 (89,417)

RE 1-4 Family (Amort) Fixed 2,522,876 2,508,479 14,397 0.57% (14,336) (53,747) (162,600)

TOTAL 9,287,585 9,227,377 60,208 0.65% (59,936) (10,592) (252,017)

Example – NPV (DCF) – Portfolio Level

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• Portfolio level analysis contains valuable insight into the profitability of various product lines under current market conditions.

• .65% Reserve (CECL)

• -$10M below ROA objective given all assumptions; cost of funds, PD, LGD, CPR, fees, and expenses

• 2% FMV discount


(1,000,000)

-

1,000,000

2,000,000

3,000,000

4,000,000

5,000,000

6,000,000

7,000,000

8,000,000

Real Estate Other 365 - 365 - Fixed RE 1-4 Family (Amort) Fixed

(200,000)

(150,000)

(100,000)

(50,000)

-

50,000

100,000

NPV (EffectiveYield)

NPV (Pricing) NPV (Exit Price)

Real Estate Other 365 - 365 - Fixed RE 1-4 Family (Amort) Fixed

Example – NPV (DCF) – Portfolio Level

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NPV (DCF): Cross Application + CECL

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CECL

CECL

SEC Filer

Non-SEC Filer


IMP

LEM

ENT

NPV (DCF): Cross Application + CECL + Exit Price

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Classification and Measurement

IMP

LEM

ENT


CECL

CECL

SEC Filer

Non-SEC Filer


IMP

LEM

ENT

NPV (DCF): Cross Application + CECL + Exit Price + Pricing

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IMP

LEM

ENT


CECL

CECL

IMP

LEM

ENT

IMP

LEM

ENT

Valuation, Day 2, and Pricing

Valuation, Day 2, and Pricing

SEC Filer

Non-SEC Filer


Poll Question


Sageworks ALLLCECL Demonstration – DCF Modeling

• Learn: » See how software can make

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Thursday, May 25th from 11:00am to 12:00pm ET


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Question & Answer

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Garver MoorePrincipal - Advisory Services

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discounted cash flow methodology for banks and credit unions

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