NOVEMBER 2016
METHODOLOGY
European RMBS Insight:
U.K. Addendum
European RMBS Insight: U.K. Addendum DBRS.COM
2
Contact Information
Table of Contents
Keith Gorman
Senior Vice President
Global Structured Finance
+44 (20) 7855 6671
[email protected]
Executive Summary
3
U.K. Mortgage Scoring Model
4
U.K. Segmentation and Delinquency Migration Matrices 7
U.K. Correlation
9
Sebastian Hoepfner
Global Structured Finance
+44 20 7855 6663
[email protected]
U.K. House Price Model
10
Rehanna Sameja
Vice President, EU RMBS
Global Structured Finance
+44 20 7855 6677
[email protected]
U.K. Distressed Sale Discount
10
U.K. Foreclosure Costs
10
U.K. CPR Assumptions 11
Kali Sirugudi
Vice President, EU RMBS
Global Structured Finance
+44 20 7855 6609
[email protected]
U.K. Cash Flow Assumptions
11
Asim Zaman
Assistant Vice President, EU RMBS
Global Structured Finance
+44 20 7855 6626
[email protected]
Belen Bulnes Meneses
Senior Financial Analyst, EU RMBS
Global Structured Finance
+44 20 7855 6699
[email protected]
Davide Nesa
Senior Financial Analyst, EU RMBS
Global Structured Finance
+44 20 7855 6697
[email protected]
Lloyd Morrish-Thomas
Financial Analyst, EU RMBS
Global Structured Finance
+44 20 7855 6679
[email protected]
Claire Mezzanotte
Group Managing Director
Global Structured Finance
+1 (212) 806 3272
[email protected]
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Executive Summary
This report is the United Kingdom (U.K.) Addendum to the DBRS European RMBS Insight Methodology (published 17 May 2016).
The report outlines the country-specific aspects of the methodology to estimate defaults and losses for U.K. RMBS and Covered
Bonds. This addendum should be read in parallel with the DBRS European RMBS Insight Methodology. The addendum includes
an overview of:
1. Data used for building the U.K. Mortgage Scoring Model and U.K. Delinquency Migration Matrices,
2. U.K. Mortgage Scoring Model (U.K. MSM),
3. U.K. Dynamic Delinquency Migration Matrices (U.K. DMM),
4. U.K. Correlation Assumption,
5. U.K. House Price Model,
6. U.K. Distressed Sale Discount,
7. U.K. Foreclosure Costs,
8. U.K. CPR Assumptions and
9. U.K. Cash Flow Assumptions.
Data
The U.K. MSM and the U.K. DMM were constructed using loan-level data aggregated from three data sources:
1. European Data Warehouse,
2. Proprietary dataset constructed with data sourced from U.K. residential mortgage originators and U.K. residential mortgagebacked security (RMBS) issuers and
3. Publicly available data on servicer and trustee websites.
Home price data from the non-seasonally adjusted Nationwide House Price Index was used to generate a base house price forecast
and MVDs. Additionally, the monthly U.K. Harmonised Consumer Price Index (CPI) from Eurostat was used to calculate real
house prices.
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U.K. Mortgage Scoring Model
U.K. MSM Modelling Sample
In the first step of the portfolio defaults and portfolio losses estimation for U.K. mortgages, loans are scored dynamically over
a forecast horizon in the U.K. MSM. The technology used to build the U.K. MSM is logistic regression. To build a score in this
framework, a loan’s risk characteristics at a point in time (the as-of date) and a binary outcome variable that represents the loan’s
performance over a period of time subsequent to the as-of date are needed.
A set of data-cleaning rules were applied to the aggregated U.K. loan-level data, the universe of loans, to identify a dataset to develop
the U.K. MSM. The dataset included loans with the following characteristics:
• For each reporting date, there is a 12-month performance window of data available subsequent to that reporting date;
• The account is current at the as-of date;
• The current balance is greater than GBP 1,000;
• The current indexed loan-to-value (LTV) ratio is less than 150%; and
• The current interest rate margin is between 0% and 7%.
Given the universe of loans, the data on each loan is assembled with the risk characteristics at the as-of date and the binary outcome
variable calculated from its subsequent performance. The outcome variable is determined based on the loan’s performance over the
subsequent 12 months from the as-of date. A loan is considered to be bad if, during the 12-month period, it either (1) entered into
90+ days arrears, (2) was foreclosed, (3) was repurchased from a delinquency status of two months or more or (4) was prepaid from
a delinquency status of two months or more.
Loans with multiple as-of dates were subject to entering the modelling sample only once. Bad loans did not represent a very high
proportion and, as a result, were over-sampled to increase their presence in the modelling sample. The modelling sample for the U.K.
MSM included approximately 100,000 loans of which 26,000 were considered to be bad and 74,000 were considered to be good.
U.K. MSM Parameters
The U.K. MSM was built with classification variables (originator-product type), objective variables (loan and borrower
characteristics) and judgemental variables (U.K. Underwriting Score). The U.K. MSM consists of 27 model parameters from 14
variables (Figure 1). Figure 1 also reports the odds ratio for each parameter. The odds ratio measures the effect of each parameter
in the U.K. MSM.
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Figure 1 – U.K. MSM Parameters
Parameter
Odds Ratio
Variable Change
Variable Type
Originator-Product Type
Building Society — Buy-to-Let
0.24
Binary
Specialised Lender — Buy-to-Let
0.31
Binary
Bank — Buy-to-Let
0.37
Binary
Specialised Lender — Non-Conforming — Buy-to-Let
0.66
Binary
Building Society — Prime
1.00
Binary
Bank — Prime
1.59
Binary
Specialised Lender — Non-Conforming
2.78
Binary
Indexed LTV
1%–40%
1.32
30%-40%
Continuous
40%–65%
1.14
55%-65%
Continuous
65%–100%
1.11
90%-100%
Continuous
100%–125%
1.19
115%-125%
Continuous
0.0%–0.8%
1.16
0.55%-0.8%
Continuous
0.8%–3.5%
1.00
3.25%-3.5%
Continuous
3.5%–5.0%
1.10
4.75%-5%
Continuous
5.0%–7.0%
1.10
6.75%-7%
Continuous
0–25,000
0.93
20000-25000
Continuous
25,000–100,000
0.98
95000-100000
Continuous
Employed Borrower/Protected Borrower
0.62
Binary
Purchase/Remortage/Renovation**
0.64
Binary
Self-Cert Borrowers
1.19
Binary
Number of Investment Properties > 8 (Buy-to-Let Only)
1.38
Binary
Prior CCJs
3.92
Binary
Restructured Non-Conforming
4.29
Binary
Fixed Rate (Short term, reset to variable or fixed for life)
0.40
Binary
SVR (Non-Conforming)
0.77
Binary
SVR (Prime)
1.87
Binary
Non-Standard Rate Stress
1.24
Binary
Tracker
1.24
Binary
High
0.51
Binary
Medium
1.00
Binary
Low
1.99
Binary
Margin*
Total income
Interest Rate Types
U.K. Underwriting Score
* For fixed rate loans and SVR the loan margin is equal to the current interest rate; consistent with the EDW loan-evel data reporting.
** Buy-to-Let product type excluded.
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Given the nature of the scoring model, the most direct way to measure the effect of a variable is by examining the odds ratio. Take,
for example, the binary variable Purchase. The odds ratio comparing Purchase to non-Purchase is:
P[Purchase]/(1-P[Purchase])/P[non-Purchase]/(1-P[non-Purchase])
Here, P[Purchase] is the probability of a purchase loan becoming bad in the 12-month time horizon. For logistic regression, the odds
ratio constructed on the values of one explanatory variable does not depend on the values of any of the other explanatory variables.
Variables included in the U.K. MSM are either binary, where the loan includes the relevant parameter or does not, or continuous,
where the odds ratio represents a specific change in the variable. For binary variables, the odds ratio is calculated for each value as
a loan characteristic versus not a loan characteristic. Furthermore, for the continuous variables Indexed LTV, Interest Rate Margin
and Total Income the change in odds ratio is not constant across the spectrum. As can be seen, e.g. the odds ratios for a 10% Indexed
LTV change is greater from 115% to 125% versus 90% to 100%.
Classification Variables – Originator and Product Type
All loans in the universe were assigned to a specific originator and product type at the portfolio level. Each of the classification
variables have three categories:
• Originator type: Bank, building society or specialised lender
• Product type: Prime, Buy-to-Let (BTL) or non-conforming
Originator type was derived from the institution that originated the mortgage loan. A loan was assigned to the category “Bank”
if the operations of the lender reflect well-established high-street lenders or challenger banks. “Building societies” consist of
originating entities that are listed members with the Building Societies Association. “Specialised lenders” primarily consist of
entities occupying a niche segment of the market or institutions which could not be assigned to other categories.
Product type was assigned based on the main mortgage product within each portfolio. The U.K. market does not have marketstandard definitions for prime versus non-conforming product types; however, both banks and building societies tend to have
stricter underwriting standards lending mostly to prime borrowers. Non-conforming borrowers are typically classified as those
borrowers with one or more loan characteristic which fall outside the standard lending criteria (higher LTV, higher debt to income,
self-certified, etc.). The prime label was assigned to both banks and building societies while the non-conforming label was only
assigned to specialised lenders
BTL loans are originated by any of the three originator types. As mentioned, the originator and product type was assigned on a
portfolio level, however BTL loans were also present within prime and non-conforming portfolios not classified as BTL. These BTL
loans were identified and separately scored in the U.K. MSM. The analysis found that, on average, BTL-labelled portfolios showed
a better performance than BTL loans as part of a mixed portfolio.
Figure 1 shows the seven originator type and product type combinations in the U.K. MSM; however, more than seven combinations
of originator type and product type are possible. These additional combinations were either not present in the data set (e.g., Building
Society – Non-Conforming) or were insignificant in the logistic regression analysis in constructing the U.K. MSM. When analysing
portfolios DBRS will tend to follow the approach outlined above for assigning originator type and product type to a portfolio. In
cases of other originator or product mixes, DBRS will determine classifications that reflect the expected loan quality of the portfolio.
Judgmental Variable – U.K. Underwriting Score
The U.K. MSM includes a judgmental variable (U.K. Underwriting Score) to assess the credit risk of loans relative to a generic
loan with similar characteristics. U.K. Underwriting Score is an ordinal variable with three values: high, medium and low. When
looking at a transaction, DBRS will assess quantitative and qualitative variables to evaluate the potential deviation of expected
performance of loans from those with comparable characteristics. These factors include positive or adverse loan selection, changes
in origination criteria, volatile historical performance and observed differences in vintage performance. DBRS expects most
portfolios to be assigned a U.K. Underwriting Score of medium, but this may be adjusted based on results from an originator or
servicer review, assessment of changes to origination criteria, analysis of an issuer’s historical performance or other factors. Positive
factors influencing the U.K. Underwriting Score would result in assigning a value of high with negative factors resulting in a value
of low.
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Although each loan is assigned a U.K. Underwriting Score, in practice, the score is generally assigned at the portfolio level. In
circumstances where DBRS determines that a pool consists of sub-portfolios which would entail multiple scores, the sub-portfolios
would be defined with a different respective U.K. Underwriting Score assigned to each.
The U.K. Underwriting Score was estimated based on analysis of the transactional performance data of 320 U.K. RMBS deals in
Intex from 1999–2015. The maximum 90-day plus delinquency rate of each transaction was set based on historical performance
data. The distribution of the maximum values was analysed with low assigned to loans in the lower quartile, medium assigned to the
second and third quartiles and high assigned to the fourth quartile. Deals were assigned a low, medium or high variable independent
of both the originator and product type. The deal-level U.K. Underwriting Score from each transaction was subsequently assigned
to each of the loans in the U.K. universe to construct the U.K. MSM. Transactions included in the loan universe but not in the Intex
dataset were assigned a U.K. Underwriting Score using a benchmark approach based on the transaction characteristics.
Interest-Only Loans
The modelling sample used to develop the U.K. MSM included 28.5% interest-only (IO) loans. The observed bad rate for IO loans in
the sample was higher relative to the overall bad rate of the sample (34.8% versus 26.0%). However, the IO variable was not found
to be significant in the logistic regression analysis. Other loan and borrower characteristics likely had more explanatory power for
the bad state.
IO originations have declined significantly over time for owner-occupied purchase loans. According to the Council of Mortgage
Lenders data, IO originations in 2015 made up just 1% of all originations down from 33% in 2007. However, non-conforming
portfolios with origination vintages from 2006–2008 typically consist of high percentages of IO loans. Additionally, BTL borrowers
continue to prefer IO loans versus an amortising loan to minimise financing costs related to renting a property.
IO loans may expose lenders to refinancing risk at the maturity date if a borrower has insufficient funds to repay the loan, home prices
have declined to the point at which a borrower’s equity is negative or a borrower is unable to source another refinancing option.
Lenders of BTL IO loans may also be exposed to a similar risk where a default and subsequent receivership of rent arrangements
on the loan have been initiated. Receivership is typically triggered if a borrower does not keep up with payments on the loans,
but the rental income from the property is sufficient to service the loans. Servicers tend to receive rental payments directly and
repayment of the loans will largely depend on the sale of the property at maturity. Each of these risks link the ultimate repayment
of the principal balance to the value of the property at time of potential sale.
All else equal, relative to a capital repayment loan, an IO loan will have a higher loan-level default rate calculated in the DBRS
European RMBS Insight Model, given the amortisation benefit repayment loans receive for a lower exposure at default in each
periodic default calculation. An additional stress is implemented in the expected Portfolio Default Rate (PDR) estimate for IO loans
susceptible to a higher degree of refinancing risk at maturity. The model includes an additive default amount of 5% of the outstanding
principal balance at maturity which is added to forecasted default balance for IO loans with the following characteristics:
• Owner Occupied: combination of Indexed LTV greater than or equal to 70%, and a total income of GBP 25,000 or below.
• BTL: Indexed LTV greater than or equal to 70%.
The additional stress applies to loans assigned to risk segment eight or lower (at maturity) where the impact of potential refinancing
risk may be underestimated in the expected PDR based on the modelling sample. Furthermore, a constant prepayment rate (CPR)
of 0% for the purpose of estimating the Exposure at Default (EAD) where the additional IO stress is applied.
U.K. Segmentation and Delinquency Migration Matrices
The U.K. MSM was applied to approximately 1,766,000 loans to estimate a loan-level score and assess the distribution of scores. 12
risk segments were identified for the purpose of calculating U.K. DMMs with a corresponding DMM for each risk segment. Figure
2 below shows cumulative percentiles for the distribution of scores within each risk segment. Additionally, Figure 2 shows the low
and high U.K. MSM score for each of the 12 risk segments.
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Figure 2 – U.K. MSM Score Distribution
Segment
Cumulative Percentile
Low Score
High Score
1
20%
0.0%
9.0%
2
30%
9.0%
12.0%
3
40%
12.0%
15.5%
4
50%
15.5%
20.4%
5
60%
20.4%
25.6%
6
70%
25.6%
30.6%
7
80%
30.6%
37.2%
8
90%
37.2%
48.2%
9
92%
48.2%
51.2%
10
94%
51.2%
54.3%
11
96%
54.3%
57.9%
12
100%
57.9%
100.0%
DMMs are calculated for each risk segment by computing the average roll rate observed in the loan-level data up to Q2 2015.1 For
the United Kingdom, the roll rates measure the quarterly transition rates between the six states described in the DBRS European
RMBS Insight Methodology.2
The risk segmentation exhibits separation in the default risk across the distribution of loan scores. When iterating the DMM within
each risk segment over time, higher cumulative default rates are calculated for higher-risk segments. Figure 3 shows the cumulative
defaults forecasted per risk segment over 50 iterations for a non-amortising pool3 of current loans as of period zero.
Figure 3: Cumulative Default Expectation per U.K. MSM Risk Segment
35.0%
31.9%
30.0%
Default Rates
25.0%
20.0%
14.2%
15.0%
17.3%
11.9%
9.1%
10.0%
5.0%
15.7%
1.4%
2.1%
2.7%
1
2
3
3.6%
4.2%
4
5
5.9%
0.0%
6
7
8
9
10
11
12
Risk Segment
1. The majority of the dataset covers the performance period between Q1 2013 and Q2 2015; however, the set also includes performance of loans back to 2005.
The roll-rate average takes this older data into consideration.
2. The six states are DQ0, DQ1, DQ2, DQ3, Default and Redeemed.
3. Assumed 0% CPR.
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Looking at Figure 2 and Figure 3 together, for a portfolio of current non-amortising U.K. loans, the following could be expected:
• For a high-quality portfolio in which all of the loans have an initial U.K. MSM score less than 9.0%, risk segment one, the
expected default rate would be approximately 1.4%.
• For an average-quality portfolio in which all of the loans have an initial U.K. MSM score between 15.5% and 20.4%, risk segment
four, the expected default rate would be approximately, 3.6%.
• For a low-quality portfolio in which all of the loans have an initial U.K. MSM score greater than 57.9%, risk segment 12, the
expected default rate would be approximately 31.9%.
Figure 3 illustrates a simplified estimate of potential default rates for each of the 12 different segments. In this example, the
respective DMM for each risk segment is applied to a portfolio of performing non-amortising loans for 12.5 years. Ultimately, a
forecasted portfolio default rate will be a function of the underlying loan characteristics and each loan’s amortisation profile. The
loan amortisation profile determines the EAD to calculate the periodic loan-level defaults. For the United Kingdom, the EAD for a
given period is equal to the outstanding loan balance 18 months4 prior to the loan defaulting, which is reflective of market practice
for recognising defaults.
U.K. Correlation
The correlation applied to each portfolio for estimating rating scenario default rates is a function of the expected default rate of the
portfolio. Correlations assigned to each portfolio range from 12% to 30% with higher-default portfolios assigned lower correlations
and lower-default portfolios assigned higher correlations (Figure 4). The scale of correlations for each expected portfolio default
rate is based on a modification of the Basel III framework.
Figure 4: Correlation Graph
35.0%
30.0%
Correlation
25.0%
20.0%
15.0%
10.0%
10.00%
9.00%
8.00%
7.00%
6.00%
5.00%
4.00%
3.00%
2.00%
1.00%
0.0%
0.0%
5.0%
Expected Portfolio Default Rate
Basel III
UK
DBRS estimated correlations across a subset of the product types ranging from 5% to 13% over a period of two years. Analysis of
the estimated correlations did show differences for products types with prime exhibiting the lowest and BTL showing the highest.
The correlations were estimated during a period of relatively benign macroeconomic factors (decreasing and low interest rates,
low unemployment and increasing house prices), which may have driven the lower estimates. During periods of economic stress,
idiosyncratic risks not reflected in the available data may influence the performance of portfolios with lower-expected defaults
versus those with higher-expected defaults. As a result, DBRS has applied higher correlations for lower-default portfolios.
4. Defined as “k” in the Base-Case Default Rates section of the European RMBS Insight Methodology.
5. Asset correlation for corporate, sovereign and bank exposures assumption per Basel III – BIS, Basel III: A global regulatory framework for more resilient
banks and banking system, December 2010, pg. 39.
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U.K. House Price Model
The U.K. House Price6 model generates MVDs for each rating scenario. The U.K. MVDs are estimated at the national level and for
the 13 regional levels reported in the Nationwide House Price Index. The Nationwide House Price Index covers quarterly data
since 1974 for the each of the U.K. regions. Real house prices were calculated using the harmonised CPI data with June 2002 as the
base year. MVDs for each of the 13 regions and the national level are shown below in Figure 4. MVDs are applied to the updated
property value to discount the sales prices of a property to calculate periodic losses.
Figure 5 – U.K. MVDs
Region
AAA
AA
A
BBB
BB
B
Volatile
Overheated
East Anglia
-44.23%
-41.02%
-35.19%
-28.87%
-19.72%
-11.03%
Yes
Yes
East Midlands
-46.60%
-43.59%
-37.72%
-32.38%
-23.98%
-14.06%
Yes
Yes
London
-52.82%
-46.73%
-37.26%
-28.11%
-18.93%
-10.59%
Yes
Yes
North
-48.09%
-44.54%
-38.74%
-33.58%
-25.24%
-14.87%
Yes
Yes
North West
-44.11%
-41.16%
-35.75%
-30.41%
-22.04%
-12.78%
Yes
Yes
Northern Ireland
-43.21%
-40.68%
-35.55%
-30.30%
-25.37%
-19.56%
Yes
Yes
Outer Metro
-47.77%
-44.67%
-37.59%
-28.59%
-19.27%
-10.86%
Yes
Yes
Outer South East
-43.07%
-38.91%
-30.02%
-21.78%
-14.03%
-7.38%
No
No
Scotland
-43.70%
-40.77%
-34.89%
-27.85%
-18.50%
-10.39%
Yes
Yes
South West
-44.48%
-41.32%
-35.23%
-27.25%
-18.31%
-10.11%
Yes
Yes
Wales
-46.64%
-43.50%
-37.83%
-31.99%
-22.45%
-13.11%
Yes
Yes
West Midland
-44.14%
-41.07%
-35.27%
-29.84%
-21.43%
-12.33%
Yes
Yes
Yorkshire
-48.89%
-45.73%
-39.79%
-34.07%
-24.81%
-14.62%
Yes
Yes
U.K. Total
-46.04%
-42.48%
-36.88%
-30.89%
-21.25%
-12.24%
Yes
Yes
Figure 4 also includes the market status for purposes of the MVD simulation where markets are considered overheated if the real
HPI (2002=100) has increased above 150 in the most recent run-up and has yet to drop below 85. Volatile indicates if a market has
ever been overheated. An overheated market which drops again below 85 is considered to be normal again, but will continue to be
looked at as volatile.
U.K. Distressed Sale Discount
Two Distressed Sale Discounts (DSD) have been estimated for the United Kingdom for loans where the property is owner-occupied
versus BTL. The DSD for owner-occupied property is estimated at 25% while, for BTL, it is 35%. The estimates are based on
analysis of 10,250 repossessed properties (7,953 owner occupied and 2,297 BTL) which were sold between January 2004 and 2015.
DSDs are applied to expected property value after applying the MVD and meant to address a property sale in a liquidation scenario.
U.K. Foreclosure Costs
DBRS estimates U.K. foreclosure costs to be 3.0% of the outstanding loan balance at the time of default and a fixed cost of GBP 2,750.
DBRS’s estimates of the variable and fixed costs are based on analysis of roughly 18,500 repossessed properties where foreclosure
cost data was provided.
6. See European RMBS Insight Methodology, Appendix 2 for further details
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DBRS has implemented minimum loss given default (LGD) for rating scenarios in the United Kingdom. DBRS recognises that,
in periods of high economic stress, it may be difficult or even impossible to find a market-clearing price for residential real estate
resulting in potential losses, which may be greater than those implied by stressed liquidation values. The minimum LGDs are set
for the AAA, AA, “A” and below-“A” rating scenarios at 25%, 20%, 15% and 10%, respectively.
U.K. CPR Assumptions
Absolute levels of prepayments differ across product types within the U.K. RMBS market. Since 2010, average prime CPRs have
ranged between 10% and 20% with a slightly increasing trend in recent years. Over this same period, average non-conforming CPRs
have ranged between 5% and 10% while BTLs have been at a relatively low level below 5%. Over this time period, mortgage rates
have declined steadily (three-year fixed 75% LTV rate down to 2.57% in June 2016 from 5.56% in January 2010 according to the
Bank of England) while annual gross lending increased to GBP 219 billion in 2015 from GBP 135 billion in 2010. Transaction CPRs
will be driven by loan-level characteristics (LTVs, IO percentages, relative interest rate, etc.) and credit availability.
Prime CPRs most likely benefited from declining interest rates and credit availability for strong borrowers; however, the high
prepayment rates are not expected to continue in case of interest rates increasing and/or home prices declining. On the other hand,
non-conforming borrowers are less sensitive to the current market rates and credit availability. Non-conforming CPRs are expected
to perform closer to the current averages, given an increase in rates and/or declining home prices. BTL loans are expected to remain
near the current averages as well, given the low CPR levels. The CPR assumed for each product type for the U.K. DMM is 8% for
prime, 5% for non-conforming and 3% for BTL.
U.K. Cash Flow Assumptions
Prepayments
Three prepayment stresses are generally run for the DBRS cash flow stresses. The stresses for the United Kingdom are 5% – Slow,
10% – Middle and 20% – Fast.
Recovery Timing
The U.K. recovery timing for cash flow analysis is 18 months. This is based on further analysis of the repossessed loans used to
estimate the U.K. DSDs. The recovery timing is the time between the first period in which a loan stops contributing principal and
interest payments to the collections and the receipt of the recoveries on the loan.
Structured Finance: EU RMBS
November 2016
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