Upload
phamanh
View
231
Download
4
Embed Size (px)
Citation preview
Rating SME transactions
Tycjan BieleckiAssistant Vice President- Analyst Business Development CEEStructured Finance Group
Thursday, May 15 2008Thursday, May 15 2008
BratislavaBratislava
2
Moody’s StructuredFinance Rating Approach
3
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
4
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
5
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…
6
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
7
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
8
How High Can The Rating Be?
9
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”
10
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”)
11
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
12
Rating SME transactions
13
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
14
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
15
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
16
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
17
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
18
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
19
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
20
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
21
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
22
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
23
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
24
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
25
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
26
Obtaining representative rating
27
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)
28
Global reach
29
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)
30
www.moodys.com/structured www.moodys.com/structured
© Copyright 2008, Moody’s Investors Service, Inc. and/or its licensors including Moody’s Assurance Company, Inc. (together, “MOODY’S”). All rights reserved. ALL INFORMATION CONTAINED HEREIN IS PROTECTED BY COPYRIGHT LAW AND NONE OF SUCH INFORMATION MAY BE COPIED OR OTHERWISE REPRODUCED, REPACKAGED, FURTHER TRANSMITTED, TRANSFERRED, DISSEMINATED, REDISTRIBUTED OR RESOLD, OR STORED FOR SUBSEQUENT USE FOR ANY SUCH PURPOSE, IN WHOLE OR IN PART, IN ANY FORM OR MANNER OR BY ANY MEANS WHATSOEVER, BY ANY PERSON WITHOUT MOODY’S PRIOR WRITTEN CONSENT.
Contact:[email protected] : +44 207 772 5602