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MEMBER OF ALLINIAL GLOBAL, AN ASSOCIATION OF LEGALLY INDEPENDENT FIRMS © 2017 Wolf & Company, P.C.
CECL Workshop
Discounted Cash Flow Method
Martin M. Caine, CPA
Alan D. Lloyd, CPA
2
Introduction
www.wolfandco.com
Alan Lloyd, CPA
Senior Audit Manager, Wolf & Company, P.C.
Voice: (215) 983-5996
Email: [email protected]
LinkedIn: alan-lloyd
Martin Caine, CPA
Member of the Firm, Wolf & Company, P.C
Voice: (413) 726-6852
Email: [email protected]
LinkedIn: martin-caine
3
Agenda
• Discounted Cash Flow Model
– Key concepts and inputs
– Pros and cons
– Sample DCF model review
– Q&A
4
Key Concepts and Inputs
From ASC 326-20-30-4:
If an entity estimates expected credit losses using methods
that project future principal and interest cash flows (that is, a
discounted cash flow method), the entity shall discount
expected cash flows at the financial asset’s effective
interest rate. When a discounted cash flow method is
applied, the allowance for credit losses shall reflect the
difference between the amortized cost basis and the
present value of the expected cash flows.
5
Key Concepts and Inputs
For variable rate loans benchmarked to an index:
Projections of changes in the factor (e.g LIBOR, prime rate,
etc.) shall not be made for purposes of determining the
effective interest rate or estimating expected future cash
flows.
6
Key Concepts and Inputs
From ASC 326-20-30-6:
An entity shall consider estimated prepayments in the
future principal and interest cash flows when utilizing a
method in accordance with paragraph 326-20-30-4 (DCF).
An entity shall not extend the contractual term for
expected extensions, renewals, and modifications unless
it has a reasonable expectation at the reporting date that it
will execute a troubled debt restructuring with the borrower.
7
Key Concepts and Inputs
Information that can be used:
• Internal, external or combination of both related to past
events, current conditions, and reasonable, supportable
forecasts
• Consider quantitative and qualitative factors in the
environment
• Not required to search for all possible information that is
not readily available without undue cost and effort
8
Key Concepts and Inputs
Collateral-dependent loans:
Regardless of the initial measurement method, an entity shall
measure expected credit losses based on the fair value of
the collateral when the entity determines that foreclosure is
probable.
An entity also shall consider any credit enhancements that
are applicable to the financial asset when recording the
allowance for credit losses.
9
Key Concepts and Inputs
Changes in present value over reporting periods:
May result not only from the passage of time but also from
changes in estimates of the timing or amount of expected
future cash flows. DCF users are permitted to report the
entire change in present value as credit loss expense (or
reversal of credit loss expense). Alternatively, an entity may
report the change in present value attributable to the
passage of time as interest income.
10
Key Concepts and Inputs
Key Inputs:
• Loan Data:
– Loan number
– Unpaid principal balance (UPB), Book Balance
– Payment amount
– Maturity Date
– Segment Information (e.g. call code, product code, geography, risk
rating, FICO scores, etc.)
– Payment structure
– Revolving status
– Available credit balances
– Government guarantee info
– Participation information, etc.
11
Key Concepts and Inputs
Key Inputs:
• Assumptions:
– Prepayment rate (Conditional Prepayment Rate (CPR), Single
Monthly Mortality (SMM))
– Expected default rates
– Expected loss rates
– Timing to recovery
12
Key Concepts and Inputs
Example SMM calculation that can be translated to CPR:
TOTALS 25,376,213 11,933,614 76,169,702 1.24% 13.85%
Month
Beginning
Balance
Contractual
Payment
Contractual
Principal
Contractual
Interest Ending Balance
Actual Payments
Collected SMM CPR
1 300,000,000 3,109,152 1,984,152 1,125,000 293,846,416 6,153,584 1.02% 11.6%
2 293,846,416 3,109,152 2,007,228 1,101,924 287,436,704 6,409,711 1.13% 12.7%
3 287,436,704 3,109,152 2,031,265 1,077,888 280,918,095 6,518,609 1.19% 13.4%
4 280,918,095 3,109,152 2,055,709 1,053,443 274,738,317 6,179,778 1.10% 12.4%
5 274,738,317 3,109,152 2,078,884 1,030,269 268,315,888 6,422,429 1.21% 13.6%
6 268,315,888 3,109,152 2,102,968 1,006,185 262,007,906 6,307,981 1.20% 13.5%
7 262,007,906 3,109,152 2,126,623 982,530 255,773,425 6,234,481 1.20% 13.5%
8 255,773,425 3,109,152 2,150,002 959,150 249,455,112 6,318,313 1.26% 14.1%
9 249,455,112 3,109,152 2,173,696 935,457 242,977,159 6,477,953 1.36% 15.1%
10 242,977,159 3,109,152 2,197,988 911,164 236,575,062 6,402,096 1.36% 15.2%
11 236,575,062 3,109,152 2,221,996 887,156 230,252,965 6,322,097 1.36% 15.2%
12 230,252,965 3,109,152 2,245,704 863,449 223,830,298 6,422,667 1.44% 16.0%
Pros & Cons
13
Pros Cons
Less historical data required Significant amount of computational
power required
Works well for amortizing loans,
balloons, fixed P&I, etc.
Does not work well for revolving loans
Can be easily leveraged for other areas
(e.g. Stress-testing, pricing, fair value
calculations, etc.)
Not as practical as some other models
such as historical loss and vintage
Useful if lack of loss history
Back-testing to support and fine-tune
assumptions
Go-forward analysis instead of historical
14
Sample DCF Model Review - Mortgage
Excerpt from model for single mortgage loan:TOTALS 99,858 55,707 156,549 18,592 2,789 15,804 327,918
Month
Beginning
Balance
Contractual
Payment Principal Interest Prepayment
Defaulted
Principal
Estimated
Loss
Estimated
Recovery Ending Balance Cash Flows
1 275,000 1,393 20 1,030 2,914 344 52 - 271,723 3,963
2 271,723 1,393 36 1,018 2,879 340 51 - 268,468 3,933
3 268,468 1,393 52 1,005 2,844 336 50 - 265,236 3,902
4 265,236 1,393 68 993 2,810 332 50 - 262,026 3,872
5 262,026 1,393 84 981 2,776 328 49 - 258,839 3,841
6 258,839 1,393 100 969 2,742 324 49 - 255,673 3,811
7 255,673 1,393 116 958 2,708 320 48 - 252,529 3,782
8 252,529 1,393 132 946 2,674 316 47 - 249,407 3,752
9 249,407 1,393 148 934 2,641 312 47 - 246,307 3,723
10 246,307 1,393 163 922 2,608 308 46 - 243,228 3,694
11 243,228 1,393 178 911 2,575 304 46 292 240,170 3,957
12 240,170 1,393 194 900 2,543 300 45 289 237,133 3,925
13 237,133 1,393 209 888 2,511 296 44 285 234,117 3,893
124 2,771 1,393 1,380 10 15 3 1 18 1,373 1,423
125 1,373 1,393 1,371 5 0 2 0 17 0 1,393
126 15 - 15
15
Sample DCF Model Review - Mortgage
Assumptions and Other Data Used for single mortgage loan:
NOTE: Assumptions would require qualitative adjustments for
reasonable, supportable forecasts (e.g. if rates have moved up
substantially in recent months, then prepayment speed (CPR)
may need to be decreased).
Contractual Rate (INPUT) 4.50% GL Balance 275,000
CPR 12.00% PV of Cash Flows 272,010
Months to Maturi ty (INPUT) 360 Estimated CECL DCF Reserve 2,990
Annual Default Rate 1.50% Reserve to Carrying Balance 1.09%
Loss Rate (% of Default Amt) 15%
Recovery Rate (% of Default Amt) 85% Loss to Carry Balance per Est. Loss 1.01%
Months to Recovery 10 Expected Principal Default 6.76%
DATA & OUTPUTSASSUMPTIONS & INPUTS
16
Sample DCF Model Review - Pool
Excerpt from model for pool:
TOTALS 169,479,009 35,934,473 117,727,983 12,793,007 1,535,161 11,257,846 334,399,312
Month
Beginning
Balance
Contractual
Payment Principal Interest Prepayment
Defaulted
Principal
Estimated
Loss
Estimated
Recovery Ending Balance Cash Flows
1 300,000,000 3,109,152 1,585,652 1,123,500 3,727,171 400,000 48,000 - 294,287,177 6,436,323
2 294,287,177 3,109,152 1,614,664 1,102,105 3,655,456 392,383 47,086 - 288,624,674 6,372,225
3 288,624,674 3,109,152 1,643,420 1,080,899 3,584,373 384,833 46,180 - 283,012,048 6,308,692
4 283,012,048 3,109,152 1,671,923 1,059,880 3,513,916 377,349 45,282 - 277,448,860 6,245,718
5 277,448,860 3,109,152 1,700,174 1,039,046 3,444,079 369,932 44,392 - 271,934,675 6,183,299
6 271,934,675 3,109,152 1,728,177 1,018,395 3,374,857 362,580 43,510 - 266,469,061 6,121,430
7 266,469,061 3,109,152 1,755,934 997,927 3,306,246 355,292 42,635 - 261,051,590 6,060,106
8 261,051,590 3,109,152 1,783,445 977,638 3,238,238 348,069 41,768 - 255,681,837 5,999,322
9 255,681,837 3,109,152 1,810,715 957,528 3,170,830 340,909 40,909 - 250,359,384 5,939,073
10 250,359,384 3,109,152 1,837,744 937,596 3,104,015 333,813 40,058 - 245,083,812 5,879,355
11 245,083,812 3,109,152 1,864,535 917,839 3,037,789 326,778 39,213 352,000 239,854,709 6,172,163
12 239,854,709 3,109,152 1,891,090 898,256 2,972,146 319,806 38,377 345,297 234,671,667 6,106,789
13 234,671,667 3,109,152 1,917,411 878,845 2,907,082 312,896 37,547 338,653 229,534,278 6,041,992
70 3,666,330 3,109,152 3,090,533 13,730 7,192 4,888 587 42,533 563,717 3,153,989
71 563,717 3,109,152 563,717 2,114 - - - 38,556 - 604,387
72 34,614 - 34,614
17
Sample DCF Model Review - Pool
Assumptions and Other Data Used at pool level:
NOTE: Assumptions would require qualitative adjustments for
reasonable, supportable forecasts (e.g. if rates have moved up
substantially in recent months, then prepayment speed (CPR)
may need to be decreased).
Contractual Rate (INPUT) 4.50% GL Balance 300,000,000
CPR 14.00% PV of Cash Flows 298,163,136
Average Li fe to Maturi ty (INPUT) 120 Estimated CECL DCF Reserve 1,836,864
Annual Default Rate 1.60% Reserve to Carrying Balance 0.61%
Loss Rate (% of Default Amt) 12%
Recovery Rate (% of Default Amt) 88% Loss to Carry Balance per Est. Loss 0.51%
Months to Recovery 10 Expected Principal Default 4.26%
DATA & OUTPUTSASSUMPTIONS & INPUTS
Discussion points
1. Any concerns with the complexity?
2. Any concerns with the required assumptions?
3. How can this analysis be improved?
3. Does anyone plan to use a DCF model for CECL?
18
Sample DCF Model Review
19
Thank You
www.wolfandco.com
Alan Lloyd, CPA
Senior Manager, Wolf & Company, P.C.
Voice: (215) 983-5996
Email: [email protected]
LinkedIn: alan-lloyd
Martin Caine, CPA
Member of the Firm, Wolf & Company, P.C.
Voice: (413) 726-6852
Email: [email protected]
LinkedIn: martin-caine