comprehensive approach to forecasting dougherty

© 2011 Bayview Advisory Services, LLC. All Rights Reserved.

Boardroom Forum on Lending DECEMBER 2011

A Comprehensive Approach to Forecasting Credit Losses: Triangulating Loss Estimates

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Forecasting Credit Losses in Bank Loan Portfolios – Acquisition vs. Lending

Challenges:

Deals continue to be competitive – multiple bidders.

Short time frames and limited data.

The credit environment has completely redefined the “worst case scenario.”

Bank transactions leave little margin for error.

Key Goals:

With respect to NPLs:

Quantify true loss severity.

For Performing Loans:

Estimate default probabilities and loss severities.

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Portfolio analysis is not an exact science; therefore, Bayview employs a three pronged approach

to estimate portfolio losses:

Roll Rate Analysis

Borrower Related Underwriting and Property Level Analysis

Regression Based Models

Portfolio Loss Estimate

A Comprehensive Approach to Forecasting Credit Losses: Triangulating Loss Estimates

3

CONFIDENTIAL


As of August 2011, the portfolio is approximately 3.1% 60+ days delinquent.

Key Observations:

− 90.4% of current loans were still current 6 months later; 4.3% paid in full during the period.

− Only 20.9% of 30 day loans were current 6 months later.

− Only 7.00% of 60+ day loans were current 6 months later.

Assuming the 6 month experience repeats itself:

− In two years, 13.9% of the portfolio will be 60+ day delinquent.

− In three years, 17.9% of the portfolio will be 60+ day delinquent.

− In five years, 23.8% of the portfolio will be 60+ day delinquent.

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A Comprehensive Approach to Forecasting Credit Losses: A Roll Rate Analysis

A Roll Rate Analysis evaluates historical portfolio performance across multiple points in time in

order to predict future performance.

− This approach tracks the actual migration of (a) current loans to delinquent/default; (b)

delinquent to re-performing, and (c) prepayments.

Sample Commercial Loan Pool: 6 Month Illustrative Roll Rate Analysis

(February 2011 to August 2011)

Current 30 60+ Default Prepay

Current 90.4% 2.9% 2.3% 0.1% 4.3%

30 20.9% 16.4% 55.6% 6.4% 0.8%

60+ 7.0% 10.3% 68.5% 13.9% 0.3%

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A Comprehensive Approach to Forecasting Credit Losses: Roll Rate Analysis

− Assuming recent transition rates are at unsustainably high levels, a pure roll rate analysis may reflect

a “severe case” scenario for defaults.

− In fact, recent experience with residential transition rates provides evidence that default rates “burn-out”

from peak levels.

− If we apply the slope of the reduction in subprime transition rates from their peak to the sample pool, it

would result in significantly lower 2 year, 3 year, 5 year, and lifetime default rates.

Severe

Case

Subprime

Trend Slope

2 year 13.9% 10.1%

3 year 17.9% 11.6%

5 year 23.8% 13.7%

Lifetime 40.3% 23.2%

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Benefits of Roll Rate Analysis:

− Accounts for actual performance of a specific population over a recent period, a key factor

not included in any other forecasting tool.

− Illustrates what the portfolio can be expected to look like at specific points in time if transition

rates remain constant.

− Can accommodate expected changes to transition rates as a result of macro variables,

burnout, or servicing practice change.

− Applicable to most asset classes

Roll rate analysis should be performed separately on risk stratified sub-portfolios. Mixing low

quality assets with high quality assets in a roll rate analysis can lead to exaggerated default

expectations. We recommend analyzing roll rates on sub-portfolios by asset type (Residential,

CRE, C&D, etc) and within asset type by loan quality (risk grades, credit score, vintages, etc).

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A Comprehensive Approach to Forecasting Credit Losses: Roll Rate Analysis

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A regression based model correlates the performance of approximately 12 key variables to

historical data of similar loan populations to predict expected portfolio default probability and

severity.

Examples of variables which correlate to long term portfolio performance include:

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A Comprehensive Approach to Forecasting Credit Losses: Residential Modeling

• Occupancy • Property Type • Geography (Zip code, MSA level) • Loan Balance • Credit Score • Documentation Type • Loan Type • Loan Age • Original LTV • Mark to Market LTV • Payment History • Forward Home Price Projections

Key Model Variables

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A Comprehensive Approach to Forecasting Credit Losses: Residential Modeling

0%

10%

20%

30%

40%

50%

60%

70%

Projected Frequency of Foreclosure (FOF) Bucket

Static Pool Performance by Model FOF Groups(Model run as of EOM July 07 (all current loans) and actual performance data is as of EOM Nov 09)

Default

REO

FCL

90+

60

30

0

200000

400000

600000

800000

1000000

0

5

10

15

20

25

Loan

Cou

nt

Vol C

PR

Remittance Date

Fixed Model vs. Actual

Actual CPR Model CPR Sample Size

Credit Model Validation Prepayment Model Validation

To test the validity of the model, projected figures are compared to actual results.

0

200000

400000

600000

800000

1000000

0

5

10

15

20

25

Loan

Cou

nt

Vol C

PR

Remittance Date

Arm Model vs. Actual

Actual CPR Model CPR Sample Size

Projected Frequency of Foreclosure

(FOF) Bucket at July 2007

Actu

al

Sta

tus

at

No

vem

be

r 2009

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BAM has studied the performance of commercial loan (CRE and C&I) portfolios of banks

(over 20,000 loans) to better understand the default probability drivers of these loans.

Bank risk scores (adjusted to the BAM underwriting scale), macroeconomic variables,

historical loan performance, and certain loan characteristics were found to be primary risk

drivers.

Based on this study, BAM has developed regression based commercial loan default modeling

tool to first establish short-term (6 month) projections of performing loans migrating to a non-

performing status.

BAM then employs a cash flow-type modeling tool to take into account prepayments, default

timing, and potential improvements in economic conditions to establish a range of default

probabilities.

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A Comprehensive Approach to Forecasting Credit Losses: Commercial Loan Modeling

•Bank Risk Scoring (Adjusted by BAM)

•Macroeconomic Variables

•Proprietary Property Value Index

•Local Unemployment Levels

•Changes to Unemployment

•Loan Performance (Historical Pay History)

Commercial Loan Modeling (CRE and C&I): Model Input Variables

•Loan Characteristics

•Occupancy (Owner vs. Investor)

•Property or Collateral Type

•Loan Seasoning

•Loan Type (Fixed vs. ARM)

•Loan Balance

•Property/Collateral State & Zip Code

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A Comprehensive Approach to Forecasting Credit Losses: Commercial Loan Modeling

CRE Model Performance C&I Model Performance

0.00%

2.00%

4.00%

6.00%

Portfolio APortfolio B

Portfolio CPortfolio D

CRE Model NPL

Actual Roll to NPL

0.00%

1.00%

2.00%

3.00%

4.00%

Portfolio APortfolio B

Portfolio CPortfolio D

C&I Model NPL

Actual Roll to NPL

0.00%

2.00%

4.00%

6.00%

8.00%

10.00%

12.00%

1 2 3 4 5 6 7 8 9 10

6 M

on

thR

oll

to 6

0+

Actual vs Model by Predicted Decile (C&I)

Model

Actual

0.00%

2.00%

4.00%

6.00%

8.00%

10.00%

12.00%

14.00%

16.00%

18.00%

20.00%

1 2 3 4 5 6 7 8 9 10

6M

on

th R

oll

to 6

0+

Actual vs Model by Predicted Decile (CRE)

prediction

actual

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Benefits of Regression Based Models:

− Provide an indication of how the portfolio should perform based on characteristics

observable about the portfolio.

− Provide a consistent approach to estimating near-term and lifetime default probability for

homogenous and granular portfolios of residential mortgage, CRE, and C&I portfolios

− Take advantage of BAMs extensive data and research to produce default and loss

estimate ranges quickly and with limited data requirements

− Set a benchmark level of performance that can be reconciled against the roll rate

analysis.

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A Comprehensive Approach to Forecasting Credit Losses: Modeling Tools

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While Regression and Roll Rate Analyses provide important data points, there is no substitute for

re-underwriting loan files and evaluating the collateral supporting the loans.

For residential and small balance commercial mortgage loans, strength of a guarantor is an

important factor in long term performance. Underwriting is focused on evidence in the loan files

that the homeowner, investor, or business using the property has strong credit and stable cash

flows. Updated property values are obtained using AVMs and BPOs that are reviewed by internal

appraisers.

For larger balance commercial mortgage loans and C&D loans, property visits by real estate

professionals are essential to understanding the status and condition of the property, verifying

physical occupancy, assessing the market for vacant space, and incorporating market conditions

into an updated valuation.

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A Comprehensive Approach to Forecasting Credit Losses: Borrower Related Underwriting and Property Level Analysis

CONFIDENTIAL


Benefits of Borrower Related Underwriting and Property Level Analysis:

− Borrower Related Underwriting is essential for predicting default probabilities:

• Assesses the accuracy and quality of the original underwriting analysis to help determine

the risk profile of each borrower.

• Helps assure that the data used in the Regression Model is accurate (documentation type,

DSCR, LTV).

• Provides for a re-grading of loans to normalize for institution specific risk grading process.

• Facilitates comparisons to other portfolios based upon strength of underwriting.

− Property Level Analysis provides a baseline forecast for portfolio loss severity:

• Determines the value of the collateral today.

• Integral to analysis of cash flow stability.

• Incorporates current and projected market conditions.

• Evaluates reasons for property value decline:

Capitalization rate deterioration vs. decline in property operating income due to

vacancy increase.

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A Comprehensive Approach to Forecasting Credit Losses: Borrower Related Underwriting and Property Level Analysis

CONFIDENTIAL


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Benefits of A Comprehensive Approach: Triangulating Loss Estimates

Portfolio Loss Estimate

• Serves as a benchmark

performance baseline

• Provides indication of future

portfolio performance based on

observable characteristics

• Works for homogeneous and

granular portfolios

Roll Rate Analysis

Borrower Related Underwriting and Property Level Analysis Regression Based Models

• Provides for normalizing of risk grades

• Determines value of the collateral today

• Assesses the accuracy and quality of the

original underwriting analysis and the loan

tape data

• Accounts for actual performance of a

specific population over a recent period

• Illustrates what portfolio can be expected

to look like at specific points in time

• Can accommodate expected changes to

transition rates

CONFIDENTIAL


Why Risk Grading Alone is Insufficient:

− Risk Grades are not uniformly applied.

− They reflect, in many cases, only relative grades--not an absolute risk metric (i.e. what is a

1, 2, or 3 rated construction loan in a tough market?).

− They do not directly translate in loss estimates.

They should, however, be incorporated as inputs in all three approaches to forecasting losses

that we have highlighted:

− Roll rates can be stratified by loan type and risk grade to illustrate how each loan type’s

best and worst risk grades are actually performing.

− Loans should be re-risk graded through the loan level re-underwriting process.

− Risk grades, where available, can be included in the Regression Model on a BAM-

adjusted basis.

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Benefits of a Comprehensive Approach: Why Risk Grading Alone is Insufficient

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Three approaches may not produce a consistent outcome and therefore must be reconciled

for financial modeling purposes. Consider the following 3 examples:

A: All Three Approaches Reconcile

• The Regression model says that loans that have the observable characteristics of the

target institution’s portfolio should perform well based upon the regression equations

that fit the large pools of loans upon which the models were based.

• Roll rates to delinquency are low over the previous 3 to 6 months.

• The underwriting and property analysis revealed strong, well documented files

signaling high credit guarantors and large commercial properties with stable cash

flows.

Conclusion: If only all deals looked like this!!

B: Roll Rates are Inexplicably Worse than Expected

• The Regression benchmark suggests that loans should perform well and the

underwriting appears sound but over the prior 3 months, the roll rates suggest that the

portfolio is declining quickly.

Recommendation: Further stratify the roll rate analysis to identify if the deterioration is broad

based. Re-underwrite the actual defaults during the period to ascertain whether the defaults

are idiosyncratic to certain large borrowers, loan types, or geography. Determine if problem is

isolated or widespread.

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Benefits of a Comprehensive Approach: Reconciling the Three Approaches

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C: Roll Rates Look Too Good

• The portfolio appears to be outperforming its observable characteristics. The loan

underwriting casts further doubt on the roll rate analysis as the credit culture of the target

institution appears weak.

Recommendation: Re-underwrite the loans that appear to be the highest risk in the

Regression model. Is the institution rolling due dates as part of an aggressive modification

campaign? Confirm payment histories.

Conclusions:

• Loan tapes can have inaccuracies and servicing practices can mask delinquency issues

but loans rarely significantly over perform or underperform their loan characteristics

without the reasons being observable in the loan underwriting and property analysis.

• A “triangulation” approach to credit is essential in the current high risk environment.

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Benefits of a Comprehensive Approach: Reconciling the Three Approaches

CONFIDENTIAL


About Bayview

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CONFIDENTIAL


Bayview was founded in 1984 and now has 964 employees. Our senior management team has an

average of 12 years company tenure.

Bayview Asset Management is minority-owned by affiliates of Blackstone Capital Partners.

Since 2008, Bayview has advised many clients on whole bank acquisitions ranging in asset size from

less than $200 million to greater than $50 billion.

Bayview services nearly 55,000 loans with an aggregate UPB of approximately $13.0 billion.

– Bayview Loan Servicing, whose predecessor was founded in 1999, now has 688 employees in 6

locations (FL (2), TX, PA, IL and PR) and is comprised of teams of experts in asset valuation, loss

mitigation, loan workouts, bankruptcy and foreclosure

– Senior and mid-level managers average more than 21 years of industry experience, with no change

in management personnel in the past five years

Bayview has proven success in loss mitigation with a focus on servicing delinquent and high-risk

performing loans for itself and third parties.

– Bayview Loan Servicing is one of only four servicers with S&P’s highest residential special servicer

rating and the only one with the highest rating for small balance commercial

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Bayview has a proven track record and is an industry leader in mortgage investment analytics and loan servicing

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Bayview enjoys strong institutional support via a non-controlling investment from affiliates of the Blackstone Group

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Bayview Asset Management is a fully-integrated mortgage investment company with expertise in the analysis and management of distressed and performing mortgage assets

Overview of the Bayview Asset Management Organization:

Founded in 1984, as a leading advisor,

valuation specialist, and broker of

mortgage servicing rights portfolios

Purchased $20 billion in loans from 2,000

counterparties in 9,000 transactions

Sponsored 75 commercial and residential

securitization transactions totaling $28

billion in securities sold to 200 institutional

investors (including securities issued

under Bayview’s small balance

commercial platform)

Raised over $3 billion and manages

three opportunity funds of credit-sensitive

residential and commercial mortgage

loans

Experience

964 employees in six offices

Dedicated teams specializing in:

Mortgage Research and Analytics

Loan and Securities Portfolio Management

Loan Special Servicing

Loan Underwriting and Valuation

Real Estate Construction and

Development

Bayview Loan Servicing manages a $13.0 billion mortgage portfolio of proprietary and third party assets

1 of only 4 servicers with S&P’s highest residential special servicer rating and the only one with the highest rating for small balance commercial loans

Depth

Minority-owned by affiliates of Blackstone

Capital Partners

Senior management team with an

average of 12 years company tenure

Flexible infrastructure and strong

management has enabled Bayview

to successfully navigate the credit

market turmoil

Stability

CONFIDENTIAL


Multi-family

Commercial

Residential

Improved

Construction

Raw Land

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Bayview has principal expertise in assessing risk and determining value across the full-spectrum of bank balance sheet assets

Real Estate

C & D Loans (Residential and Commercial)

Bayview also has experience in

Mortgage and Asset-Backed

Securities backed by real estate

asset classes

Bayview’s experience includes

both performing and non-

performing loans in the following

asset classes:

Mortgage and Asset-Backed Securities

C & D Loans (Residential and Commercial)

CONFIDENTIAL


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The same functional teams that drive Bayview Asset Management’s successful proprietary investment process are available to clients of Bayview Advisory Services

Loan Servicing

688 FTEs

Mortgage Research and

Analytics

6 Professionals

Real Estate Construction & Development

10 Professionals

Portfolio Management

4 Loan and MBS Managers

Loan Underwriting &

Valuation

22 Underwriters 21 Appraisers

Highly-rated by all rating agencies

Loss mitigation expertise for high risk and distressed

assets

$13.0 billion portfolio of residential, commercial and

C&D loans

Servicing $3 billion in loss share assets (9 banks)

Dedicated mortgage research

effort

Proprietary loan-level credit &

prepay analytics

Extensive database of proprietary

and industry data

Large balance commercial real estate team

with expertise in troubled and transitional

assets

Team management individuals have an

average 21 years of experience in

development, legal, valuation, construction,

engineering, banking, and property

management

Due diligence process created to

protect buyers of distressed assets

Asset level valuations by staff with

average experience between 15

years (residential) and 23 years

(commercial)

Valuations tracked and analyzed

via a proprietary database

Seasoned team of loan and securities

managers

Manage three funds of distressed

commercial and residential mortgages ($3

billion capital raised)

Active market participants provide detailed

information on capital flows

and capital markets activity

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Four core competencies serve as the foundation for the services Bayview delivers to its advisory clients

Credit Loss Forecasts and

Asset Valuation

Loss Mitigation Solutions

Structured Finance

Solutions

Principal Takeout for

Problem Assets

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To better understand how Bayview can meet your loan portfolio advisory needs, please contact us:

Jim Dougherty

Managing Director

Bayview Advisory Services, LLC

Office: 212.259.0630 / Cell: 212.960.8119

[email protected]

www.bayviewadvisoryservices.com

CONFIDENTIAL


DISCLAIMER: The information contained herein has been compiled by Bayview Advisory Services, LLC (“BAS”) solely for use by the intended recipient and for no others.

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comprehensive approach to forecasting dougherty

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portfolio analysis

portfolio losses

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pure roll rate analysis

benefits of roll rate

forecasting credit losses

current loans

comprehensive approach