Current economic conditions are challenging borrowers, especially those that have previously restructured their mortgages or those paying a floating rate of interest. This could lead to credit metrics deteriorating, including higher defaults and losses incurred, which could result in negative rating actions for European residential mortgage-backed securities (RMBS) transactions.

Inflation across European countries increased significantly in 2022, pushing policy and mortgage rates to multi-year highs and constraining consumer-related securitizations' credit performance. The European Central Bank (ECB) continues to increase interest rates to reduce inflation, which means consumers are suffering a cost of living shock, while at the same time mortgage borrowers with floating-rate mortgages are exposed to interest rate volatility. Simultaneously, our forecasted European house price declines for these jurisdictions range from 0.5% (France) up to 4.4% (Portugal) for 2023 (see "European Housing Prices: A Sticky, Gradual Decline," published on Jan. 11, 2023).

Given that we expect the European RMBS sector could experience some stress, we tested the resiliency of a representative sample of our rated transactions (in France, Ireland, Italy, Netherlands, Spain, and Portugal). These transactions are backed by prime, reperforming, and buy-to-let (BTL) collateral from a range of origination vintages (see "How Much Shock Can U.K. RMBS Take?" for our comparable U.K. scenario analysis). Hypothetical scenarios included increased levels of loans in 90+ days arrears, house price declines, and combinations of the two.

Scenario Analysis Details

During the global financial crisis, 90+ days arrears in our rated European RMBS transactions rose sharply. Additionally, in some countries house prices fell by approximately 5%-15%, depending on the jurisdiction.

For this scenario analysis, we applied eight hypothetical stress scenarios to simulate the impact of increased 90+ days arrears and house price declines. We stressed transactions by applying four, six, and eight percentage point increases in 90+ days arrears. We also looked at the effect of house prices declining by 5%, 10%, and 15%. Finally, we ran a set of scenarios in which we combined higher levels of 90+ days arrears and house price declines to see the overall effect on European RMBS ratings.

Although these stress scenarios are somewhat extreme and potentially implausible for certain collateral types--i.e., arrears for prime transactions only increased by an average of two percentage points--they do provide a good picture of the relative strength of our rated European RMBS transactions.

We divide the scenarios into three categories:

• Higher levels of 90+ days arrears (scenarios 1 to 3);
• House price declines leading to higher loss severities (scenarios 4 to 6); and
• A combination of both (scenarios 7 and 8).

Scenario Analysis Results

All the scenario analysis results are accessible in greater detail here.

Generally, the results of these tests indicate that, even under increased economic stress, 'AAA' rated tranches demonstrate significant stability (see table 1). Even under the most stressful scenarios, less than 15% of 'AAA' rated tranches see a downgrade, and those that do have their rating lowered by only one or two notches.

Table 1

Although transactions with legacy reperforming collateral are particularly vulnerable to performance deterioration, our scenario analysis demonstrates rated notes are relatively resilient to additional stresses. This is because the current ratings reflect our forward-looking view of this sector and consider an expectation of increased arrears.

Additionally, the results also show that non 'AAA' rated tranches may be more affected and suffer steeper downgrades, particularly at speculative-grade rating levels.

Assumptions For Scenario Analysis

For this scenario analysis, we focused on a representative sample of 60 transactions featuring prime, reperforming, and BTL collateral. The sample included both transactions with very seasoned assets and more recently originated transactions. When presenting our results we grouped together France, Italy, and Portugal because we expect less rating impact on these transactions in the scenario analysis: the French transactions only have tranches rated 'AAA' and the Italian and Portuguese transactions are all very seasoned and capped by our sovereign criteria. In addition, there are much fewer transactions in our rated universe from these three jurisdictions. We excluded rated excess spread notes and tranches with ratings below 'B (sf)' across all jurisdictions.

We performed our scenario credit analysis in line with our criteria by applying a default frequency of 100% in all rating scenarios for borrowers that are 90+ days in arrears (see "Global Methodology And Assumptions: Assessing Pools Of Residential Mortgage Loans," published on Jan. 25, 2019). So, for example, a stress test involving a 400 basis points (bps) increase in loans in 90+ days arrears resulted in a 400 bps rise in the assumed foreclosure frequency for all our rating scenarios.

To simulate house price declines, we applied haircuts to the property valuations, which principally affect and increase the loss severity assumptions in our ratings analysis. After applying these scenario stresses, we conducted our cash flow analysis by applying our cash flow criteria (see "Global Framework For Payment Structure And Cash Flow Analysis Of Structured Finance Securities," published on Dec. 22, 2020). We applied our standard cash flow stress scenarios, using two different default patterns, interest rate stress scenarios, and prepayment scenarios. The cash flows were run for a total of 195 rated tranches from these 60 European RMBS transactions.

Table 2

Increase in 90+ days in arrears loans (scenarios 1-3)

For the increase in 90+ days in arrears loans scenarios, we stressed our RMBS ratings by increasing the final weighted-average foreclosure frequencies (WAFFs) by four, six, and eight percentage points, respectively, at each rating level. These scenarios would therefore lead to more required credit coverage at each rating level.

For example, if the 'AAA' WAFF (i.e., the gross default rate for the RMBS portfolio over the transaction's life in a 'AAA' scenario) was 24%, it increases to 28% under scenario 1.

House price declines (scenarios 4-6)

For the house price decline scenarios, we applied various valuation haircuts to original property valuations to calculate the weighted-average loss severity.

For example, in our 5% house price decline scenario, we applied a 5% valuation haircut to the original property valuation before indexation. This haircut was applied on top of any valuation haircut already applied under our rating criteria. If the property did not have a full valuation, according to our criteria we apply a 5% valuation haircut. In scenario 4 of this analysis, the total valuation haircut applied would then be approximately 10%.

Increase in 90+ days in arrears and house price declines (scenarios 7-8)

For scenarios 7 and 8, we stressed our RMBS ratings by combining scenario 1 with scenarios 4 and 5, respectively--i.e., we assumed a four percentage point increase in 90+ days in arrears and a house price decline of either 5% or 10%.

Some limitations and caveats to our scenario analysis

It's worth highlighting a few caveats to our scenario analysis:

• The stresses we selected for each scenario are hypothetical and are not meant to be predictive or part of any outlook statement.
• In our scenario analysis, we applied increases in arrears and declines in house prices immediately, which is a conservative assumption. An actual future decline in house prices or build-up in arrears is likely to occur gradually, during which the RMBS tranches are likely to build up credit enhancement due to deleveraging, potentially lessening the ratings impact.
• Our analysis does not consider any additional build-up in credit enhancement or increase in house prices since the last surveillance analysis.
• The stresses are also not meant to calibrate to any of the economic scenarios we associate with our ratings in our ratings definitions.
• The results are based on the application of the models we use to rate European RMBS transactions. A rating committee applying the full breadth of S&P Global Ratings' criteria and including qualitative factors might, in certain instances, assign a different rating than the quantitative analysis alone would indicate.
• In particular, the implied rating transitions to the 'CCC' rating category are based solely on our model results. Our ratings analysis makes additional considerations before assigning ratings in the 'CCC' and 'CC' rating categories (see "General Criteria: Criteria For Assigning ‘CCC+’, ‘CCC’, ‘CCC-‘, And ‘CC’ Ratings," published on Oct. 1, 2012).

Related Criteria

• Global Methodology And Assumptions: Assessing Pools Of Residential Loans, Jan. 25, 2019
• Global Framework For Payment Structure And Cash Flow Analysis Of Structured Finance Securities, Dec. 22, 2020
• Criteria For Assigning 'CCC+', 'CCC', 'CCC-', And 'CC' Ratings, Oct. 1, 2012
• Principles of Credit Ratings, Feb. 16, 2011

Related Research

• European RMBS Index Report Q1 2023, May 15, 2023
• Economic Outlook Eurozone Q2 2023: Rate Rises Weigh On Return To Growth, March 27, 2023
• How Much Shock Can U.K. RMBS Take?, March 1, 2023
• Cost Of Living Crisis: Southern European RMBS Grapples With Rising Rates, Jan. 25, 2023
• Economic Research: European Housing Prices: A Sticky, Gradual Decline, Jan. 11, 2023
• Cost Of Living Crisis: Mapping Exposures In European RMBS And Covered Bond Markets, June 27, 2022
• Residential Mortgage Market Outlooks Maintained For 15 European Jurisdictions Following Revised Economic Forecasts, April 28, 2022
• S&P Global Ratings Definitions, Nov. 10, 2021
• ESG Industry Report Card: Residential Mortgage-Backed Securities, March 31, 2021
• 2017 EMEA RMBS Scenario And Sensitivity Analysis, July 6, 2017
• Global Structured Finance Scenario And Sensitivity Analysis 2016: The Effects Of The Top Five Macroeconomic Factors, Dec. 16, 2016
• European Structured Finance Scenario And Sensitivity Analysis 2016: The Effects Of The Top Five Macroeconomic Factors, Dec. 16, 2016