cecl methodology q&a anthology

Sageworksanalyst.com

Neekis Hammond, CPAPrincipal - Advisory Services

1

February 16, 2017

CECL Methodology SeriesQuestion and Answer


About the Webinar

• We will address as many questions as we can throughout the presentation or through direct communication via follow-up email

• Ask questions throughout the session using the GoToWebinar control panel

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Disclaimer

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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.


Neekis Hammond, CPAPrincipal - Advisory Services

About Today’s Presenters

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Agenda

• Series Overview

• Question and Answer

• Data

• Contractual Life

• Segmentation

• Methodology

• General/Miscellaneous

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Series Overview

• Thursday, February 16th, 2017, 2-3 p.m.: CECL Methodology Q&A

• Thursday, February 23, 2017, 2-3 p.m.: Unfunded Commitments & Construction Loan CECL Methodologies

• Thursday, March 9, 2017, 2-3 p.m.: Forecasting with CECL

• Thursday, March 16th, 2017, 2-3 p.m.: CECL Calculations in a Software Environment

• Thursday, March 23, 2017, 2-3 p.m.: Disclosures with CECL

Sign up at: web.sageworks.com/cecl-methodology-webinar-series/

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Agenda

• Series Overview


• Data


• Segmentation

• Methodology


8


Data

Questions related to the amount and type of historical data:

• How much historical data is required?

• How many historical periods do I need to include; do they need to be stored monthly, quarterly, or annually?

• We have call report data going back n years; do we have enough data?

• We have loan number, balance, and loan term information stored; is this what you’re referring to?

• We have origination information, loan number, loan balance, and loan-level chargeoff data; what else are we missing?

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Data



• How many historical periods do I need to include; do they need to be stored monthly, quarterly, or annually?




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Data

11

1.0

4%

0.9

6%

1.1

4%

0.8

4%

0.7

0%

0.5

4%

0.5

1%

0.4

3%

0.3

4%

0.5

1%

0.4

3%

0.3

4%

6/30/2017 9/30/2017 12/31/2017


Data

How much historical data is required?

How many historical periods do we need to include; do they need to be stored monthly, quarterly, or annually?

• ASU 326-20-55-20: Community Bank A, after considering underwriting standards and the contractual terms of loans that existed over the historical period, believes that the most recent 10-year period is reasonable.

• 2009/2010 to 2019/2020

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Data

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When Will the Amendments Be Effective?

For public business entities that are U.S. Securities and Exchange Commission(SEC) filers, the amendments in this Update are effective for fiscal years beginning after December 15, 2019, including interim periods within those fiscal years. For all other public business entities, the amendments in this Update are effective for fiscal years beginning after December 15, 2020, including interim periods within those fiscal years. For all other entities, including not-for-profit entities and employee benefit plans within the scope of Topics 960 through 965 on plan accounting, the amendments in this Update are effective for fiscal years beginning after December 15, 2020, and interim periods within fiscal years beginning after December 15, 2021. All entities may adopt the amendments in this Update earlier as of the fiscal years beginning after December 15, 2018, including interim periods within those fiscal years. An entity will apply the amendments in this Update through a cumulative-effect adjustment to retained earnings as of the beginning of the first reporting period in which the guidance is effective (that is, a modified-retrospective approach).


Data

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When Will the Amendments Be Effective?

For public business entities that are U.S. Securities and Exchange Commission(SEC) filers, the amendments in this Update are effective for fiscal years beginning after December 15, 2019, including interim periods within those fiscal years. For all other public business entities, the amendments in this Update are effective for fiscal years beginning after December 15, 2020, including interim periods within those fiscal years. For all other entities, including not-for-profit entities and employee benefit plans within the scope of Topics 960 through 965 on plan accounting, the amendments in this Update are effective for fiscal years beginning after December 15, 2020, and interim periods within fiscal years beginning after December 15, 2021. All entities may adopt the amendments in this Update earlier as of the fiscal years beginning after December 15, 2018, including interim periods within those fiscal years. An entity will apply the amendments in this Update through a cumulative-effect adjustment to retained earnings as of the beginning of the first reporting period in which the guidance is effective (that is, a modified-retrospective approach).


Data

15


Data

16

3 Yr.

4 Yr.


3 Yr.

4 Yr.

Data

17

3 Yr.

4 Yr.


Data



• How many historical periods do we need to include; do they need to be stored monthly, quarterly, or annually?




18


Data

19

1.0

4%

0.9

6% 1.1

4%

0.8

4%

0.7

0%

0.5

4%

0.5

1%

0.4

3%

0.3

4%

2.3

7%

2.1

9%

2.5

9%

1.9

0%

1.5

9%

1.2

2%

1.1

6%

0.9

8%

0.7

7%

12/31/2015 3/31/2016 6/30/2016 9/30/2016 12/31/2016 3/31/2017 6/30/2017 9/30/2017 12/31/2017

3 Year Loss Rate Sum of Annual Loss Rate


Data







20


Data

21

14

.1%

0.0

%

0.2

%

0.1

%

0.5

%

0.8

%

2.4

%

12

.6%

24

.0%

0 1 2 3 4 5 6 7 8

0.69% 0.65%

1.36%1.24%

1.06%0.97% 1.04%

0.95% 0.91%

9/30/2011 12/31/2011 3/31/2012 6/30/2012 9/30/2012 12/31/2012 3/31/2013 6/30/2013 9/30/2013

36 MONTH LOSS RATE - MIGRATION


Data







22


Data

ASU 326:

• 20-55-10 through 14 “addresses the meaning of the term portfolio segment

• 20-55-15 through 16 “addresses the application of the term credit quality indicator• “as of the balance sheet date, the entity should use the most current information it has obtained”

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http://www.fasb.org/jsp/FASB/FASBContent_C/CompletedProjectPage&cid=1176168232014


Agenda

• Series Overview


• Data


• Segmentation

• Methodology


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Contractual Life

Questions related to determination and utilization of contractual life:

• How do you calculate the average life for the loan? Can you go into more details on how it is related to attrition analysis?

• Is attrition count based or dollar based?

• When do we use a prepayment rate such as CPR or SMM and when do we use expected life?

• How do you calculate the prepayment rate? Can you go into more detail on how it is calculated?

25


Contractual Life


• How do you calculate the average life for the loan? Can you go into more detail on how it is related to attrition analysis?




26


Contractual Life

27


Contractual Life

28


Contractual Life


• How do you calculate the average life for the loan? Can you go more details on how it is related to attrition analysis?




29


Contractual Life

Is attrition count based or dollar based?

• In a sample of N equally likely outcomes mathematicians assign a chance (or weight) of 1/N to each outcome

• The probability of an event is defined as the number of certain outcomes divided by the total number of equally likely outcomes in the sample space of the experiment.

• Using a dollar based approach implies an already determined (supportable) correlation to attrition rates.

• 11 Loans; 10 @ $1, and 1 @ $90. $90 exits the portfolio over the analysis period. Should we then assume 9 of the remaining 10 loans will exit in the following quarter?

• If dollars are correlated to behavior, that implies a risk variance between loans within a pool that is, by definition, intended to contain loans with similar risk characteristics

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Contractual Life






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Contractual Life

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LOAN NUMBER 4.A CAPITAL EXPENDITURESGL Balance 115,000,000.00 Segment 4.a CapExSubsegment PassDate 12/31/2015Interest Rate 5.50%Discount Rate 1.53%Payment Type BalloonPayment Amt 3,472,528.71 Mat Date 1/31/2020Nper 36 Renewal Assumption (months) -CPR (Conditional Prepayment Rate) 33.00%SMM (Standard Monthly Mortality) 3.28%PD (Probability of Default) 2.47%CDR (Constant Default Rate) 0.21%LGD (Loss Given Default) 25.44%Recovery Delay (Foreclosure Lag) 12


Contractual Life

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LOAN NUMBER 4.A CAPITAL EXPENDITURESGL Balance 115,000,000.00 Segment 4.a CapExSubsegment PassDate 12/31/2015Interest Rate 5.50%Discount Rate 1.53%Payment Type BalloonPayment Amt 3,472,528.71 Mat Date 1/31/2020Nper 36 Renewal Assumption (months) -CPR (Conditional Prepayment Rate) 33.00%SMM (Standard Monthly Mortality) 3.28%PD (Probability of Default) 2.47%CDR (Constant Default Rate) 0.21%LGD (Loss Given Default) 25.44%Recovery Delay (Foreclosure Lag) 12


11

5,0

00

,00

0

11

3,8

30

,96

1

4,1

29

,93

3

10

8,0

90

,63

5

9,0

72

,70

0

2,7

79

,43

2

1,0

50

,57

2

3,0

79

,36

1

12

3,0

22

,12

7

GL BALANCE PV DEFAULTED PRINCIPAL

PRINCIPAL INTEREST PREPAYMENT ESTIMATED LOSS

ESTIMATED RECOVERY

CASH FLOW

DISCOUNTED CASH FLOW RESULTS

Contractual Life

34


11

5,0

00

,00

0

11

3,8

30

,96

1

4,1

29

,93

3

10

8,0

90

,63

5

9,0

72

,70

0

2,7

79

,43

2

1,0

50

,57

2

3,0

79

,36

1

12

3,0

22

,12

7



ESTIMATED RECOVERY

CASH FLOW


Contractual Life

35


Contractual Life

36


Contractual Life

37


Contractual Life






38


Contractual Life

39

Date Period Beginning Balance Expected Principal Expected Interest End of Month Balance Principal Collection SMM CPR

TOTAL 113,113,050 13,947,211 1.55% 16.91%

- (150,000,000)

12/31/2015 1 150,000,000 1,065,070 393,750 146,274,115 2,660,815 1.06% 12.04%

1/31/2016 2 146,274,115 1,074,851 383,970 142,534,477 2,664,787 1.09% 12.29%

2/29/2016 3 142,534,477 1,084,667 374,153 138,864,780 2,585,030 1.05% 11.93%

3/31/2016 4 138,864,780 1,094,300 364,520 134,151,365 3,619,114 1.82% 19.76%

4/30/2016 5 134,151,365 1,106,673 352,147 130,100,329 2,944,363 1.37% 15.25%

5/31/2016 6 130,100,329 1,117,307 341,513 125,697,376 3,285,646 1.67% 18.26%

6/30/2016 7 125,697,376 1,128,865 329,956 120,131,821 4,436,690 2.63% 27.39%

7/31/2016 8 120,131,821 1,143,474 315,346 116,324,217 2,664,130 1.27% 14.18%

8/31/2016 9 116,324,217 1,153,469 305,351 111,247,654 3,923,093 2.38% 25.11%


Contractual Life

40


TOTAL 113,113,050 13,947,211 1.55% 16.91%

- (150,000,000)

12/31/2015 1 150,000,000 1,065,070 393,750 146,274,115 2,660,815 1.06% 12.04%

1/31/2016 2 146,274,115 1,074,851 383,970 142,534,477 2,664,787 1.09% 12.29%

2/29/2016 3 142,534,477 1,084,667 374,153 138,864,780 2,585,030 1.05% 11.93%

3/31/2016 4 138,864,780 1,094,300 364,520 134,151,365 3,619,114 1.82% 19.76%

4/30/2016 5 134,151,365 1,106,673 352,147 130,100,329 2,944,363 1.37% 15.25%

5/31/2016 6 130,100,329 1,117,307 341,513 125,697,376 3,285,646 1.67% 18.26%

6/30/2016 7 125,697,376 1,128,865 329,956 120,131,821 4,436,690 2.63% 27.39%

7/31/2016 8 120,131,821 1,143,474 315,346 116,324,217 2,664,130 1.27% 14.18%

8/31/2016 9 116,324,217 1,153,469 305,351 111,247,654 3,923,093 2.38% 25.11%


Contractual Life

41


TOTAL 113,113,050 13,947,211 1.55% 16.91%

- (150,000,000)

12/31/2015 1 150,000,000 1,065,070 393,750 146,274,115 2,660,815 1.06% 12.04%

1/31/2016 2 146,274,115 1,074,851 383,970 142,534,477 2,664,787 1.09% 12.29%

2/29/2016 3 142,534,477 1,084,667 374,153 138,864,780 2,585,030 1.05% 11.93%

3/31/2016 4 138,864,780 1,094,300 364,520 134,151,365 3,619,114 1.82% 19.76%

4/30/2016 5 134,151,365 1,106,673 352,147 130,100,329 2,944,363 1.37% 15.25%

5/31/2016 6 130,100,329 1,117,307 341,513 125,697,376 3,285,646 1.67% 18.26%

6/30/2016 7 125,697,376 1,128,865 329,956 120,131,821 4,436,690 2.63% 27.39%

7/31/2016 8 120,131,821 1,143,474 315,346 116,324,217 2,664,130 1.27% 14.18%

8/31/2016 9 116,324,217 1,153,469 305,351 111,247,654 3,923,093 2.38% 25.11%


Agenda

• Series Overview


• Data


• Segmentation

• Methodology


42


Segmentation

Questions related to segmentation and sub-segmentation:

• We presently segregate our pooled loans by loan type (collateral) and then by risk rating. Under CECL, would you anticipate segregating by product type, then collateral type and then risk rating?

• Can we simply break out our loan pools by call code?

• If FICO is considered a risk identifier then isn’t the most current FICO the important indicator & thus 5 years of data with only 2 years of FICO works?

• FICO, as referenced in this question, is analogous with risk rating or any other credit quality indicator

43


Segmentation






44


Segmentation

ASU 326-20-55-5,12,15

• Payment Structure• Interest Only, Balloon, Amortizing, etc.

• Contract Term• 30 yr., 15 yr., 3/1 or 5/1 ARM, Revolving, etc.

• Interest Rate

• Fixed/Variable

• Exposure/Loan Type• Call Code, Product Type, Loan Purpose, etc.

• Example: 1.c.2.a, 4.a, 1st Lien Residential, 2nd Lien Residential, HELOC, New Auto, Used Auto, Unsecured, commercial equipment, etc.

45


Segmentation

46


Segmentation

47


Segmentation






48


Segmentation

49


Segmentation

50


Agenda

• Series Overview


• Data


• Segmentation

• Methodology


51


Methodology

Questions related to calculating historical loss experience:

• Vintage• Do you need to have both the origination date and renewal date? Is it ok to replace the first origination date with the

renewal date when it happens?

• Regarding extensions/renewed loans, do you count the extended/renewed life as part of the life of the loan?

• Migration• What's optimal for loss rate calculation? 36 months? Longer? Shorter?

• When we are talking about migration analysis, are we only concerned with the beginning credit quality indicator and how much of that pool moved to loss OR are we following the pool through all grade changes through the life of the loan?

• Why are you using 3-year old data? Why not use 2014-2016? Sure, you'll have some loans that weren't in existence for the entire 3-year life of the pool, but that will be the case for any pool. It would seem that 2011-2013 loss data for setting loss rates for 2017 and forward is nearly worthless?

• The outputs are measuring loss rates, not the migration from one risk rating to another. In my institution loss typically occur once a credit gets to a specific risk rating. Therefore, loss rates in every risk rating category, except that one, will essentially be 0. Am I understanding that correctly?

52


Methodology


• Vintage• Do you need to have both the origination date and renewal date? Is it ok to replace the first origination date with

the renewal date when it happens?






53


Methodology

54


Methodology

55


Methodology









56


Methodology

Regarding extensions/renewed loans, do you count the extended/renewed life as part of the life of the loan?

ASU 326-20-6, 326-20-50-7, 310-20-35-9,10,11,12

In most cases, a renewal would result in a "new loan" for vintage or any life-of-loan analysis. The guidance contained within the new standard (ASU 326/CECL) points to a "more than minor" test contained within ASC 310-20: "This condition would be met if the new loan’s effective yield is at least equal to the effective yield for such loans and modifications of the original debt instrument are more than minor."

In practice, more than minor has been determined to be >10% change in NPV. Also, short-term extensions that facilitate administrative needs are ignored and/or do not meet the "more than minor" test. For example, a 90-day extension would likely not constitute a new loan while a full 3-year renewal would.

57


Methodology

58


Methodology









59


Methodology

60


Methodology

61


Methodology

62


Methodology









63


Methodology

64


Methodology

65


Methodology

66


Methodology






• When we are talking about migration analysis are we just concerned with where a loan started, say grade 3 and how much of that pool moved to loss OR are we following the pool through all grade changes through the life of the loan.

• Why are you using 3-year old data? Why not use 2014-2016? Sure, you'll have some loans that weren't in existence for the entire 3-year life of the pool, but that will be the case for any pool. It would seem that 2011-2013 loss data for setting loss rates for 2017 and forward is nearly worthless.


67


Methodology

68

0.00%

0.20%

0.40%

0.60%

0.80%

1.00%

1.20%

1.40%

1.60%



Methodology

69

0.00%

0.20%

0.40%

0.60%

0.80%

1.00%

1.20%

1.40%

1.60%



Methodology






• When we are talking about migration analysis are we just concerned with where a loan started, say grade 3 and how much of that pool moved to loss OR are we following the pool through all grade changes through the life of the loan.

• Why are you using 3-year old data? Why not use 2014-2016? Sure, you'll have some loans that weren't in existence for the entire 3-year life of the pool, but that will be the case for any pool. It would seem that 2011-2013 loss data for setting loss rates for 2017 and forward is nearly worthless.


70


Segmentation

71


Segmentation

72


Methodology - Continued


• Probability of Default & Loss Given Default – note that migration principles apply• We subscribe and/or calculate the probability of default at our institution. Can we use our current probability of

default model?

• Discounted Cash Flow• We’re approaching $10B and are looking for a solution for DFAST and CECL. Which approach is ideal for cross

application?

• Our institution is only $500MM, we don’t need to do complex modeling such as DCF; correct?

73

Note – This is not a complete list of all methodologies that can be used to determine historical loss experience





default model?


application?


74



1.2

5

3.2

5

3.7

5

2.1

5

1.7

5

4.2

5

WORKING CAPITAL LOC

EQUIPMENT VEHICLE CREDIT CARD CONSTRUCTION SBA

AVERAGE LIFE

Evaluating Risk Characteristics

75


Evaluating Risk Characteristics

76

0.00%

0.20%

0.40%

0.60%

0.80%

1.00%

1.20%

0 0.5 1 1.5 2 2.5 3 3.5 4 4.5

ANNUAL LOSS RATE & EXPECTED LOSS RATE RELATIVE TO AVERAGE LIFE

Annual Loss Rate Expected Loss





default model?


application?


77



Methodology

78


Methodology

79


0.00%

0.10%

0.20%

0.30%

0.40%

0.50%

0.60%

0.70%

Q1

20

04

Q2

20

04

Q3

20

04

Q4

20

04

Q1

20

05

Q2

20

05

Q3

20

05

Q4

20

05

Q1

20

06

Q2

20

06

Q3

20

06

Q4

20

06

Q1

20

07

Q2

20

07

Q3

20

07

Q4

20

07

Q1

20

08

Q2

20

08

Q3

20

08

Q4

20

08

Q1

20

09

Q2

20

09

Q3

20

09

Q4

20

09

Q1

20

10

Q2

20

10

Q3

20

10

Q4

20

10

Q1

20

11

Q2

20

11

Q3

20

11

Q4

20

11

Q1

20

12

Q2

20

12

Q3

20

12

Q4

20

12

Q1

20

13

Q2

20

13

Q3

20

13

Q4

20

13

Q1

20

14

Q2

20

14

Q3

20

14

Q4

20

14

Q1

20

15

Q2

20

15

Q3

20

15

Q4

20

15

Q1

20

16

Q2

20

16

Q3

20

16

Q4

20

16

Q1

20

17

Q2

20

17

Q3

20

17

Q4

20

17

Q1

20

18

Q2

20

18

Q3

20

18

Q4

20

18

Q1

20

19

BASELINE FORECAST

12 Month Average (Commercial & Industrial (C&I) Loans - Charge-Offs (% of Average Loans)) Max Standard Error Multi Regression Estimate

Methodology

80


Methodology

81

0.00%

0.10%

0.20%

0.30%

0.40%

0.50%

0.60%

0.70%

Q1

20

04

Q2

20

04

Q3

20

04

Q4

20

04

Q1

20

05

Q2

20

05

Q3

20

05

Q4

20

05

Q1

20

06

Q2

20

06

Q3

20

06

Q4

20

06

Q1

20

07

Q2

20

07

Q3

20

07

Q4

20

07

Q1

20

08

Q2

20

08

Q3

20

08

Q4

20

08

Q1

20

09

Q2

20

09

Q3

20

09

Q4

20

09

Q1

20

10

Q2

20

10

Q3

20

10

Q4

20

10

Q1

20

11

Q2

20

11

Q3

20

11

Q4

20

11

Q1

20

12

Q2

20

12

Q3

20

12

Q4

20

12

Q1

20

13

Q2

20

13

Q3

20

13

Q4

20

13

Q1

20

14

Q2

20

14

Q3

20

14

Q4

20

14

Q1

20

15

Q2

20

15

Q3

20

15

Q4

20

15

Q1

20

16

Q2

20

16

Q3

20

16

Q4

20

16

Q1

20

17

Q2

20

17

Q3

20

17

Q4

20

17

Q1

20

18

Q2

20

18

Q3

20

18

Q4

20

18

Q1

20

19

ADVERSE FORECAST12 Month Average (Commercial & Industrial (C&I) Loans - Charge-Offs (% of Average Loans)) Max Standard Error Multi Regression Estimate


Methodology

82

0.00%

0.10%

0.20%

0.30%

0.40%

0.50%

0.60%

0.70%

Q1

20

04

Q2

20

04

Q3

20

04

Q4

20

04

Q1

20

05

Q2

20

05

Q3

20

05

Q4

20

05

Q1

20

06

Q2

20

06

Q3

20

06

Q4

20

06

Q1

20

07

Q2

20

07

Q3

20

07

Q4

20

07

Q1

20

08

Q2

20

08

Q3

20

08

Q4

20

08

Q1

20

09

Q2

20

09

Q3

20

09

Q4

20

09

Q1

20

10

Q2

20

10

Q3

20

10

Q4

20

10

Q1

20

11

Q2

20

11

Q3

20

11

Q4

20

11

Q1

20

12

Q2

20

12

Q3

20

12

Q4

20

12

Q1

20

13

Q2

20

13

Q3

20

13

Q4

20

13

Q1

20

14

Q2

20

14

Q3

20

14

Q4

20

14

Q1

20

15

Q2

20

15

Q3

20

15

Q4

20

15

Q1

20

16

Q2

20

16

Q3

20

16

Q4

20

16

Q1

20

17

Q2

20

17

Q3

20

17

Q4

20

17

Q1

20

18

Q2

20

18

Q3

20

18

Q4

20

18

Q1

20

19

SEVERLEY ADVERSE FORECAST

12 Month Average (Commercial & Industrial (C&I) Loans - Charge-Offs (% of Average Loans)) Max Standard Error Multi Regression Estimate


Methodology

83

External Factor (National Data) R Square * Slope ** Lead (months)

Real GDP growth 20.51% -0.02% 18

Nominal GDP growth 27.45% -0.02% 18

Real disposable income growth 0.85% 0.00% 18

Nominal -disposable income growth 2.51% 0.00% 18

Unemployment rate 54.64% 0.05% 3

CPI inflation rate 0.12% 0.00% 6

3-month Treasury rate 9.56% -0.02% 6

5-year Treasury yield 0.62% -0.01% 6

10-year Treasury yield 2.45% 0.02% 6

BBB corporate yield 42.89% 0.07% 12

Mortgage rate 0.59% 0.01% 6

Prime rate 10.71% -0.02% 6

Dow Jones Total Stock Market Index (Level) 31.62% 0.00% 18

House Price Index (Level) 39.44% 0.00% 6

Commercial Real Estate Price Index (Level) 44.19% 0.00% 6

Market Volatility Index (Level) 37.21% 0.01% 18

Multi-Regression Statistics Result

Adjusted R Square 79.65%

Standard Error 0.05%

Observations 49

Regression Utilization Coefficients ***

Intercept 0.04%

Commercial Real Estate Price Index (Level) 0.00%

Unemployment rate 0.03%

BBB corporate yield 0.04%

Market Volatility Index (Level) 0.00%





default model?


application?

• We’re a small institution, we don’t need to do complex modeling such as DCF; correct?

84



Methodology

85


Methodology

86


Methodology

87

0.00%

0.20%

0.40%

0.60%

0.80%

1.00%

1.20%

1.40%

1.60%



11

5,0

00

,00

0

11

3,8

30

,96

1

12

3,0

22

,12

7

GL BALANCE PV CASH FLOW


DCF Analysis

88


DCF Analysis

89

11

5,0

00

,00

0

11

3,8

30

,96

1

1,1

69

,03

9

12

3,0

22

,12

7

GL BALANCE PV RESERVE CASH FLOW



11

5,0

00

,00

0

11

3,8

30

,96

1

4,1

29

,93

3

10

8,0

90

,63

5

9,0

72

,70

0

2,7

79

,43

2

1,0

50

,57

2

3,0

79

,36

1

12

3,0

22

,12

7



ESTIMATED RECOVERY

CASH FLOW


DCF Analysis

90


Agenda

• Series Overview


• Data


• Segmentation

• Methodology


91


General/Miscellaneous

General questions regarding the new standard and the impact:

• Some claim CECL may drive an increase in reserves, as much as doubling, or more. Should bank and credit unions worry how their data will be incorporated into stress testing?

• “CECL is being delayed…”

• “New administration will abolish CECL with regulatory reform…”

• “ABA advocating to delay implementation…”

92



93


Credit Unions are particularly vulnerable to the new standard given the industries application of qualitative and environmental factors and/or the relationship between annual loss rates and reserve levels:


94

Greater Than 1 Year in Q&E

46%Less Than 1 Year in Q&E

54% Greater Than 6 months in

Q&E64%

Less Than 6 months in

Q&E36%


Transition Planning and Execution

95

cecl methodology q&a anthology

Economy & Finance