Rating SME transactions

Tycjan BieleckiAssistant Vice President- Analyst Business Development CEEStructured Finance Group

Thursday, May 15 2008Thursday, May 15 2008

BratislavaBratislava

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Moody’s StructuredFinance Rating Approach

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Informal discussions with arranger and originator

Operations review and discussion with manage-ment

Rating mandate

Portfolio analysis, legal, tax and structural analysis

Rating

Committee: Decision on CE Levels and ratings

Iterative process giving feedback to arranger and originator

Rating Levels and CE

Publicationof rating and New Issue Report

Monitoring and rating changes

Definitive Ratings* and New Issue Reports

* Publication depends on the nature of a rating.

t0

Term sheet

Moody’s Structured Finance Rating Approach

The Rating Process

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Rating Process: Qualitative and Quantitative

Loan/Pool Analysis

•Origination sources•Underwriting quality•Management level•General risk factors•Economic trends

Deal andSecurities’

Structure Analysis

•Loan-by-loan analysis•Pool characteristics•Statistical andquantitative modeling

•Pool cash flows•Default frequency and

timing, loss severity•Payment priorities•Spread analysis•Performance/ cash triggers •Tranching/ credit enhancement

•Models review•Tranching andenhancement

RatingCommittee

•Deal Structure•Parties involved•Legal/ tax issues

Qualitative

Quantitative

•Discussion of all factors•Checking models’

•reasonableness•sensitivity

•Benchmarking vs. similar deals

•Final vote

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Moody’s Rating – Expected Loss

Ratings measure credit risk

Probability of a default

Severity of a loss

Expected loss = Probability of default x Severity

Example:

Prob. Def. = 5%

Severity of Loss = 20% (recovery rate = 80%)

EL = 5% x 20% = 1%

– And, if the average life of the security is 6 years…

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YearRating 1 2 3 4 5 6 7 8 9 10Aaa 0.00003% 0.00011% 0.00039% 0.00099% 0.00160% 0.00220% 0.00286% 0.00363% 0.00451% 0.00550%Aa1 0.00031% 0.00165% 0.00550% 0.01155% 0.01705% 0.02310% 0.02970% 0.03685% 0.04510% 0.05500%Aa2 0.00075% 0.00440% 0.01430% 0.02585% 0.03740% 0.04895% 0.06105% 0.07425% 0.09020% 0.11000%Aa3 0.00166% 0.01045% 0.03245% 0.05555% 0.07810% 0.10065% 0.12485% 0.14960% 0.17985% 0.22000%A1 0.00320% 0.02035% 0.06435% 0.10395% 0.14355% 0.18150% 0.22330% 0.26400% 0.31515% 0.38500%A2 0.00598% 0.03850% 0.12210% 0.18975% 0.25685% 0.32065% 0.39050% 0.45595% 0.54010% 0.66000%A3 0.02137% 0.08250% 0.19800% 0.29700% 0.40150% 0.50050% 0.61050% 0.71500% 0.83600% 0.99000%Baa1 0.04950% 0.15400% 0.30800% 0.45650% 0.60500% 0.75350% 0.91850% 1.08350% 1.24850% 1.43000%Baa2 0.09350% 0.25850% 0.45650% 0.66000% 0.86900% 1.08350% 1.32550% 1.56750% 1.78200% 1.98000%Baa3 0.23100% 0.57750% 0.94050% 1.30900% 1.67750% 2.03500% 2.38150% 2.73350% 3.06350% 3.35500%Ba1 0.47850% 1.11100% 1.72150% 2.31000% 2.90400% 3.43750% 3.88300% 4.33950% 4.77950% 5.17000%Ba2 0.85800% 1.90850% 2.84900% 3.74000% 4.62550% 5.37350% 5.88500% 6.41300% 6.95750% 7.42500%Ba3 1.54550% 3.03050% 4.32850% 5.38450% 6.52300% 7.41950% 8.04100% 8.64050% 9.1905% 9.7130%B1 2.57400% 4.60900% 6.36900% 7.61750% 8.86600% 9.8395% 10.5215% 11.1265% 11.6820% 12.2100%B2 3.93800% 6.41850% 8.55250% 9.9715% 11.3905% 12.4575% 13.2055% 13.8325% 14.4210% 14.9600%B3 6.39100% 9.13550% 11.5665% 13.2220% 14.8775% 16.0600% 17.0500% 17.9190% 18.5790% 19.1950%Caa 14.3000% 17.8750% 21.4500% 24.1340% 26.8125% 28.6000% 30.3875% 32.1750% 33.9625% 35.7500%

Moody’s Idealised Expected Loss Table

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Not Prime

long term short term

Aaa

Aa1Aa2Aa3 Prime-1

A1A2A3

Prime-2Baa1Baa2Baa3 Prime-3

Ba1Ba2Ba3

B1B2B3Caa1Caa2Caa3CaC

Inve

stm

ent

Gra

deSp

ecul

ativ

e G

rade

Quality of credit

Gilt edged

Very high

Upper-medium

Medium grade

Questionable

Poor quality

Very poor

Moody’s Rating Scale

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How High Can The Rating Be?

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Risk Layers and Typical Issues In New Markets

AssetsOriginationSerivicngHistory

Structure

Systemic risks

Political risk

Currency swapIR swapLiquidityBack-up servicing

Legal

Enforcement

Fraud risk

Payment systems

Quality of data/IT

Overall stability------------LCC

TransferabilityConvertibilityExpropriation--------------------“SOV. CEILING”

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Possible Credit Enhancement Types

Internal– Excess spread (Interest on receivables, Fees and expenses,

Interest on securities)– Reserve account– Subordination– Over-collateralisation

External– Letter of credit– Mortgage insurance– Limited financial guaranty– Bond insurance (“wrap”)

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CEE Sovereign Ceilings and Local Currency Guidelines

AaaAaa/STASlovenia

AaaAa1/STASlovakia

Aa3A1/STARomania

AaaAa1/STAPoland

AaaAa1/STALithuania

AaaAa1/POSLatvia

AaaAa1/STAHungary

AaaAa1/POSEstonia

AaaAa1/POSCzech Republic

Aa1A1/POSCroatia

Aa3A1/POSBulgaria

Local currency ceilingForeign currency ceilingCountry

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Rating SME transactions

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What are SMEs ?

Enterprise classification scheme from the EU:

– micro, small, medium-sized SMEs based on headcounts annual turnover or annual balance sheet total

Basel II:

– Corporates with total assets or an annual turnover below EUR 50 million, either classified as retail exposures or corporate exposures

Entities of all sizes are included in SME securitisations

Moody‘s uses the SME definition of the originating bank

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Common Framework for risk heterogeneous SME portfolios

Portfolios may contain less than 100 obligors or many 1000s of obligors

Portfolios with many 1000s of obligors can show concentrations in terms of:

– Regions, industry, collateral types

– Effective number used as measure of granularity

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Determining the methodology: default distribution

Concentrations in terms of obligors, industries or regions:

Key element of analysis is to find appropriate default rate distribution

Monte-Carlo simulation: Moody’s CDOROMTM

or STARFINDERTM

Granularity of the SME portfolio:

Inverse Normal distribution

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Parameters that need to be estimated

Default rate:

– Distribution parameters: mean and volatility

– Timing of default

Recovery rate:

– Distribution parameters: mean and volatility

– Correlation parameters

Prepayment rate

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Sources of information for our assumptions

Historical information (quarterly cohort data) easy and direct estimation of the expected cumulative

default rate

Originator’s internal Masterscale (if validated) and/ or RiskCalc expected default frequency

Country specific statistical information for SMEs

Benchmarking with similar deals + Moody’s corporate ratings/outlooks

Other qualitative and pool-derived aspects

1) and/or 2) tuned by the rest of sources

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Limitations on historical information (DR & RR)

Lack of representation of historical sample for securitized pool

Historical period does not cover a full economic period + real estate crisis

Lack of granularity for some vintages

Observation period shorter than the term of the loans

Distortions caused by refinancing/restructuring

Historical information needs often to be complemented with other sources of

information

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Default Rate analysis: Mapping Analysis

Infer the credit quality of a portfolio from the analysis of the originator’s internal rating system based on:- Originator‘s internal Masterscale (1 year- expected PD)- Observed yearly rating migration matrices;

Moody‘s KMV RiskCalc Results are compared to the Moody‘s idealised default probabilities

Determination of expected cum DR over the time horizon for the deal (i.e. WAL) based on Moody’s idealized cumulative default rate table

Ideally based on a combination of different sources & approaches

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Default rate Standard Deviation

Historical information allows an easy and direct estimation of the DP standard deviation

If meaningful historical analysis is not available or portfolio shows concentrations → estimate on the basis of correlation parameters

– Global correlation: driven by geographical concentration

– Intra-industry correlation: driven by industry concentration Stress applied for high industry-concentrated

portfolios

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Recovery Analysis

Moody’s moves from a fixed recovery to stochastic recoveries

input needed mean RR, standard deviation of RR, correlation between RR, correlation between DR and RR

For concentrated portfolios, Moody’s adopts a Beta distribution applied to each defaulted asset

For granular portfolios, Moody’s uses a Normal distribution applied on a portfolio basis

Moody’s uses a recovery distribution

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Source of information for Recovery Analysis

Usage of historical recovery data

Originator’s Internal loss given default (LGD) estimations (if validated)

Collateralisation ratios and type of collateral on a loan-by-loan basis for the securitised portfolio. Analysis for mortgaged properties:

– Type of property (residential vs. commercial) / occupancy type (owner occupied vs. income producing real estate)

Detailed information on RR is important

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Ideally securitised pool information needed:

Criteria used to select the portfolio

Amortisation profile

Spread vector

Loan-by-loan information with:

borrower information (e.g. group, type, industry)/ loan

characteristics (e.g. purpose, outstanding, amortization,

interest rate, etc.)/ collateral information / originator’s

internal estimations /behavioural data (e.g. arrears status)

Moody’s would like to see a detailed description of the loans securitised

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Moody’s Guidelines for Operational Reviews

Purpose and scope of on-site Moody’s operational reviews is to

understand

- the Business of the originator;

- Risk (especially credit) management,

- Product types and characteristics,

- Origination & monitoring process & Collection and recovery

processes including the internal rating systems (PD and LGD)

Key aim is to understand originator’s business

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Analytical tools

CDOROMTM: default and/or recovery distribution for concentrated portfolios

STARFINDERTM : obtain default distribution for portfolios not homogeneous in terms of size or credit risk

ABSROMTM: cash-flow allocation model

– Add-hoc cash flow models: deal specific aspects not incorporated in ABSROM

RiskCalcTM: web-based analytical solution for estimating default risk for privately held firms

– The model produces forward-looking default probabilities, as well as implied credit ratings for each obligor

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Obtaining representative rating

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Suggestions – Early Preparation For a Transaction

Discuss legal issues with lawyers & rating agency

Decide and discuss rating target

– See what enhancement/structure may be needed

Prepare portfolio data, including data format

Prepare historical performance data

Consider back-up servicer

Determine structure

– External support? (PRI, wrap, guarantee)

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Global reach

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Brazil

Cyprus

Australia

Japan

Hong Kong

Germany

Singapore

United Kingdom

Italy

United States

Canada

France

Spain

Mexico

China

Korea

India

ArgentinaChile

Czech Republic(2006)

Russia

Taiwan

South Africa

Egypt2003

Israel2003

Moody’s Offices and Affiliates

Bulgaria

UAE(2007)

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www.moodys.com/structured www.moodys.com/structured

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Contact:tycjan.bielecki@moodys.comDirect : +44 207 772 5602