This criteria article describes S&P Global Ratings' approach to analyzing the credit risk in U.S. single-family rental (SFR) securitizations. There are generally two types of SFR transactions: single-borrower (SB) transactions, backed by a single loan to a borrower, where the underlying assets are primarily single-family properties; and multi-borrower (MB) transactions, backed by loans to multiple borrowers, where the underlying assets are majority single-family properties, with the remaining being predominantly multifamily properties. The detailed scope of these criteria is outlined in Appendix I. For additional information, including changes between the RFC and the final criteria, and a summary of the comments received during the RFC process, see "Criteria For Rating U.S. Single-Family Rental Securitizations Published" and "RFC Process Summary: U.S. Single-Family Rental Securitization--Methodology And Assumptions," published in conjunction with this article.

METHODOLOGY

SFR Securitization Ratings Framework Overview

Given the operating nature of SFR portfolios predominately containing single-family properties (including but not limited to one-to-four-unit attached, detached, townhouse, and condominium properties), our approach to rate SFR securitizations draws from both commercial mortgage-backed securities (CMBS) and residential mortgage-backed securities (RMBS) criteria frameworks.

The criteria for SFR securitizations primarily address the likelihood that cash flow (whether from property generated rental income, liquidation proceeds, or other applicable forms) would be sufficient to satisfy amounts due to bondholders at the applicable rating levels. We apply these criteria to derive 'B' and 'AAA' loss projections for the securitized portfolio, and then interpolate the in between rating level loss projections. Our loss projections incorporate other factors, such as geographic concentration accounting for property level diversification and minimum credit enhancement levels. The criteria framework, set out in chart 1, highlights key analytical considerations for SB and MB transactions.

Chart 1

Our approach to rate SB and MB transactions is summarized below:

Single borrower

• For an SB transaction (generally backed by a single loan), the credit enhancement (CE) is driven by the loss severity analysis since we assume the loan defaults, similar to our approach for single-asset single-borrower (SASB) CMBS transactions.
• Since the underlying assets are primarily single-family homes, the loss severity analysis largely borrows from our U.S. RMBS criteria framework. While the recovery values in SFR closely resemble U.S. RMBS at the 'AAA' level, the 'B' level reflects larger recovery values than U.S. RMBS. This difference, predominately at the 'B' level, reflects our view that: (i) potential property value reductions related to repossession stigma would not be material; (ii) idiosyncratic property-specific losses would be substantially diversified away given all properties in the portfolio would be exposed to a loan default; (iii) the eventual loss severity calculated would be partially offset by rental cash flow income; and (iv) compared to an RMBS portfolio, greater liquidation efficiencies exist due to economies of scale and geographic clustering of the properties.

Multi-borrower

• Our probability of default (PD) assessment is based upon the premise that PD is a function of debt service coverage (DSC). This premise shapes a benchmark DSC/PD matrix, which is informed by RMBS criteria. We use this benchmark matrix to determine a starting point for a given portfolio's PD. Once we have determined the benchmark PD, we make adjustments based on factors such as loan characteristics, historical performance information, and transaction-specific effective loan count.
• For an MB transaction, the loss severity for single-family properties is between the SB loss severity and that of a traditional RMBS, reflecting features that increase the likelihood of servicer advances and the applicability of certain loss severity components. To determine the loss amount for multifamily properties, we apply our CMBS property valuation analysis framework using capitalization rate and S&P Global Ratings net cash flow (S&P NCF). We combine both single- and multifamily property loss severities to determine 'AAA' and 'B' rating level loss severities for the entire MB pool.

Our analysis of SFR securitizations also incorporates the payment structure and cash flow mechanics, operational and administrative risk, counterparty risk, and legal and regulatory risk. These areas are addressed in separate criteria articles (see Related Criteria section).

The following sections discuss our analytical framework in detail.

Section 1: Debt Service Coverage And Property Value Assessment

Chart 2

Debt service coverage assessment

Our starting point for evaluating an SFR portfolio is to determine sustainable S&P Global Ratings' net cash flow (S&P NCF) from which we derive S&P Global Ratings' debt service coverage (S&P DSC).

Chart 3

The S&P DSC is a key input for assessing PD for MB portfolios and recovery values for SB portfolios. To determine S&P NCF, and therefore S&P DSC, we follow an approach similar to that described for multifamily properties in our CMBS global property evaluation criteria (see the Related Criteria section), with certain modifications. As such, the major cash flow parameters our approach considers are:

• Gross potential rent (GPR): A comparison of in-place rents to our view of market rents, with vacant units generally leased up at the lower of the average in-place rent and the market rent.
• Vacancy: Generally, the higher of in-place and our view of market vacancy is applied, with consideration given to historical averages. We also consider collection losses and tenant concessions.
• Operating expenses: Generally, these expenses are reflective of historical averages and our view of these expenses, specifically: for property management fee, use the greater of actual and our view of the fee that would be sufficient to attract a replacement property manager, which is generally between 8% and 12% of effective gross income (EGI--generally gross potential revenue adjusted for vacancy), and could be lower depending on factors such as property proximity; for real estate taxes, use the actual taxes or our estimate of taxes considering other factors, including reassessments; and for insurance, use the actual insurance premium or an estimate of insurance if we expect a material change in insurance rates is likely.
• Capital expenditures: Our determination is informed by factors such as location, size, age, and extent of recent property renovations. We may assume a specific dollar amount for each property or base our determination on a percentage of EGI.

Property value assessment

The property value used in our analysis (which is then subject to additional rating-specific reductions) is generally informed by considering multiple data points on the property, including but not limited to the acquisition price, the amount and nature of capital expenditure since purchase, and third-party valuations provided by appraisals/broker price opinions (BPOs). We may adjust our valuation based on factors including, but not limited to, our consideration of the integrity of the valuation method, portfolio seasoning, forward-looking view of the housing market, and the variation/diversification of property composition within the portfolio. We also index the valuation to account for home price changes since the valuation date using an approach described in our U.S. RMBS issued 2009 and later criteria (see Related Criteria section).

Section 2: Default Analysis

Chart 4

SB transactions

Our default analysis for SB SFR resembles the approach typically applied for a SASB CMBS transaction. As such, we assume that a default on the loan occurs, and the realization of cash flow to repay noteholders is based on the underlying recoveries on the collateral, which is detailed in Section 3.

MB transactions

Chart 5

Determine diversified 'B' anchor probability of default 

To determine our diversified 'B' anchor PD, we take our starting point from a benchmark matrix that gives diversified 'B' anchor PDs relative to DSCs. The lower the DSC, the greater the expected PD. The benchmark PDs in table 1 relate to a pool of single-family properties with characteristics such as a 65% LTV and non-amortizing loans. The LTV is based on the property values described in Section 1. In our framework, a pool with an effective loan count (see Appendix II for effective loan count calculation) of 55 or more is considered fully diversified, whereas a pool with an effective loan count of five or less is considered non-diversified.

Table 1

Determine adjusted diversified 'B' PD 

The diversified 'B' anchor PD derived using table 1 above may be further adjusted by recognizing certain attributes that can influence default behavior. These factors may include loan/portfolio characteristics (e.g., LTV, underlying property type, and loan type) compared to the benchmark used within table 1 above, historical performance information, underwriting guidelines, peer comparison, and our outlook on the sector. Based on this adjusted diversified 'B' PD, we then use table 2 to determine the corresponding diversified 'AAA' PD, as well as the non-diversified 'B' PD and 'AAA' PD. For example, assuming 1.30 DSC for a given pool, our diversified 'B' anchor PD derived using table 1 would be 15%. Considering certain factors, we then increased this diversified 'B' anchor PD to 20%. This 20% adjusted diversified 'B' PD (column 1 of table 2) is then used to determine the corresponding diversified 'AAA' PD (52%), as well as the non-diversified 'B' PD (59%) and 'AAA' PD (94%) from table 2.

Table 2

Determine final pool-specific PD 

The pool-specific 'B' and 'AAA' PDs are then linearly interpolated between the corresponding diversified and non-diversified PDs using the pool-specific effective loan count. Appendix III provides a detailed example illustrating these steps.

Section 3: Loss Severity Analysis

Chart 6

SB transactions - loss severity

Chart 7

SB transactions: determining initial SB SFR loss severity for single-family properties 

For SB SFR, given the 100% default assumption, loss severity (at a given rating level) represents the difference between the portfolio value derived in Section 1, and the recovery proceeds from the portfolio (i.e., recovery value) at that rating level. Since the underlying assets are primarily single-family homes, the loss severity analysis largely borrows from our U.S. RMBS criteria framework. We determine the initial SB SFR loss severity by applying a modified U.S. RMBS criteria loss severity framework to the property value determined in Section 1. The two key components of RMBS loss severity--repossession market value decline (MVD) and liquidation expenses--are modified to account for the differences between the SFR and U.S. RMBS sectors. Table 3 compares the assumptions related to these components for the initial SB SFR loss severity to those for RMBS loss severity.

Table 3

Our approach and related assumptions used to determine initial SB SFR loss severity are detailed below.

Repossession MVD:

• Fixed MVD: We apply a fixed MVD of 15% for 'B' and 40% for 'AAA' to property value.
• Over and undervaluation: Based on the assessment of the level of over/undervaluation (see U.S. RMBS issued 2009 and later criteria in Related Criteria section) for a given metropolitan statistical area (MSA) or state, we continue to apply such adjustments at the 'B' and 'AAA' level. It is intended to reflect how a given area of the country (and therefore property within such area) may be prone to market value declines either in addition to or less than the standard fixed MVDs.
• Forced sale discount (FSD): We do not apply FSD at the 'B' rating category. We continue to apply 10% FSD under the 'AAA' rating scenario. FSD addresses factors such as repossession-based stigma and related material deferred maintenance. In RMBS, properties backing defaulted loans may be more prone to repossession-based stigma and associated sub-standard upkeep, resulting in higher loss severities. In SFR, however, factors such as security deposits and their subsequent return to tenants, as well as historically strong occupancy rates, reinforce our view that the underlying properties would be less subject to adverse property effects. As a result, we do not apply an FSD under the 'B' scenario.

Liquidation expenses:

• Brokerage and other costs: In SFR transactions, we assume a 5% cost for 'AAA' and 'B' rating levels, primarily reflecting expenses such as real estate commissions (broker fees); this cost is a percentage of the liquidation value of the property under the given rating level. We do not apply any fixed foreclosure costs because of expected foreclosure related efficiencies compared to RMBS. We may modify these assumptions if, in our view, these costs are expected to be materially different, or there are other material expenses not already captured in our analysis.
• Advancing: Our RMBS methodology accounts for loss amounts related to the servicer recouping amounts they have advanced through default and property liquidation. These amounts may include taxes, insurance, and, in some cases, principal and interest. For SB SFR, we do not include these amounts in the loss severity calculation. The premise for this approach to SB SFR loss severity is that certain features such as the existence of "lock-box" mechanisms (or equivalents) support the continued flow through of rental cash flow from tenants to the securitization trust after the assumed borrower default. We also assume that these properties are likely subject to shorter disposition timelines given transaction features that more quickly enable rights of disposition, as compared to U.S. RMBS.

SB transactions: determine portfolio tier and adjust loss severity 

Loss severity discounts in table 4 are applied and reflect our view that while the recovery values closely resemble U.S. RMBS at the 'AAA' level, the 'B' level reflects larger recovery values than U.S. RMBS. In particular, predominately at the 'B' level, (i) idiosyncratic property-specific losses would be substantially diversified away given all properties in the portfolio would be exposed to a loan default, (ii) the eventual loss severity calculated would be partially offset by rental cash flow income, and (iii) compared to an RMBS portfolio, greater liquidation efficiencies exist due to economies of scale and geographic clustering of the properties. Given the above considerations, portfolio level-derived initial SB SFR loss severities for 'B' and 'AAA' (subject to floors of 10% and 20%, respectively) are then discounted based on a portfolio tier.

Table 4

Portfolio tier is a function of a portfolio's operating and transaction-specific characteristics as compared to the sector characteristics and/or of cohorts therein and considers factors such as:

• S&P DSC: Given that the debt service coverage provides a strong indication of cash flow coverage and incorporates net cash flow compared to debt service obligations, we view higher S&P DSCs more favorably.
• Debt yield: Because the S&P DSC may be comparatively high due to a low cost of funds on the liabilities, we also assess debt yield to understand the net cash flow generated by a given property or portfolio relative to the amount of debt outstanding against those assets.
• Net rental yield: This measure removes the effects of loan leverage and assesses the net cash flow as a percentage of the portfolio value.
• Sponsor/portfolio characteristics: This includes assessing factors including, but not limited to, historical and current occupancy rates, tenant profile, tenant delinquencies, remaining lease term, and average property age. Property management is also a factor as it may affect the status of the portfolio (e.g., centralized vs. decentralized, lease renewal rates, etc.).
• Loan term/structure: We assess if the subject transaction has stronger or weaker features compared to typical structures (that resemble CMBS) and a typical loan (that utilizes full-term interest-only balloon maturities) in this sector. For example, an amortizing loan is considered positive as the transaction benefits from deleveraging.
• Sector outlook: We may incorporate our sector outlook informed by single-family rental market dynamics in a broader context of overall macro and residential housing market (for both single- and multifamily units) conditions.

After assessing the above features and their weightings according to our views on particular transaction features, and conditions within the sector, we derive the loss severity discount factors for 'B' and 'AAA'. The portfolio tiers are scaled such that tier 3 represents the general comparable benchmark we would observe within the sector. For example, if we viewed a particular transaction as having features better than the comparable benchmark, we may assess the transaction as residing within a tier of 3-4. As a result, we would assign a 35%-50% discount factor for 'B' and 5.0%-7.5% for 'AAA'.

SB transactions: add applicable servicer advances  

As outlined above, the initial SB SFR loss severity is premised on the presence of certain features such as a robust 'lock-box' mechanism. As a result, we do not include servicer advance amounts in the initial SB SFR loss severity calculation. To the extent such features were lacking, we may assume that a portion of the servicer advancing (without any loss severity discounts on that portion) to be included in the overall SFR loss severity calculation. A very low S&P DSC could also result in a greater likelihood that a servicer would need to advance interest and other amounts on the loan and subsequently recoup such advances.

The following table displays certain rating level loss projections at different tiers for a geographically diverse SB portfolio assuming an equilibrium housing market (i.e., no over/undervaluation).

Table 5

SB transactions: loss severity for multifamily collateral 

For multifamily properties, our loss severity analysis uses a capitalization and recovery approach that is similar to the one described in CMBS global property evaluation and CMBS criteria (see Related Criteria section). This approach utilizes the S&P NCF in conjunction with capitalization rates to derive recovery values for 'B' and 'AAA' and uses the recovery values based on the stand-alone credit enhancement subject to minimum loss severity of 10% and 20% at the property level for 'B' and 'AAA' rating levels, respectively. No further loss severity discounts related to portfolio tier are applied for such collateral.

In addition, certain property type constructs could have multifamily elements, such as a single tax-parceled lot of multiple single-family homes. In such cases, the loss severity assessment may follow the single-family property approach (as outlined above, including the application of loss severity discount factors). This is based on our determination of whether these properties could be liquidated individually while also accounting for increased potential costs related to additional expenses and/or timeline extensions. Otherwise, we would determine loss severity based on the approach outlined in the prior paragraph for multifamily properties, to the extent the property/loan features adequately fall within the scope of these SFR criteria. In such a case, no further loss severity discounts are applied to the loss severity for such collateral.

MB transactions - loss severity

Chart 8

MB transactions: loss severity for single-family residential collateral 

For MB SFR transactions, the tenant cash flow trapping mechanisms (such as lock boxing) are generally weaker and not as efficiently enforceable compared to SB SFR. In addition, the concept of FSD could have relevance within MB transactions, given smaller and more fragmented operators. However, the presence of CMBS-style servicing mechanics and relative clarity in the ability to pursue on certain rights of receivership could make recovery timelines on collateral shorter compared to RMBS timelines. As a result, for MB SFR transactions, we apply a weighted severity that ranges from the initial SB SFR loss severity (not subject to the minimum loss severity floors) to the RMBS single-family property loss severity (see table 3 above). Our weighting assessment is informed by certain loan features (such as whether they are amortizing or not) and observed historical loss severities. Depending on loan and transaction features, this weighting would generally be 40% or higher at the 'AAA' and 'B' rating levels; but could potentially be lower if adequate mitigants were present. After the weighting, the single-family property loss amount for the portfolio is calculated at 'AAA' and 'B' and subject to the same minimum loss severities as in RMBS, which are 20% and 10%, respectively.

For example, at a 'B' rating level, the initial SB SFR loss severity was 5%, and an RMBS loss severity was 30% for a portfolio. Assuming a 40% weighting and no multifamily properties in the portfolio, the MB SFR loss severity for that transaction at a 'B' rating level would be 15% [0.40*(0.30 – 0.05) +0.05].

MB transactions: loss severity for multifamily property collateral  

For multifamily residential properties in MB transactions, we determine loss severity based on the approach outlined under "Loss severity for multifamily collateral" in the SB transactions section above. The presence of these property types/features may also be subject to concentration limits because, beyond certain thresholds or given certain characteristics, the credit evaluation may start to fall out of the scope of these criteria and resemble a CMBS transaction evaluation more closely.

Section 4: Additional Considerations

Chart 9

Geographic concentration adjustment

Because property values and rental income can be influenced not only by national level factors but also have regional variation, we assess the SFR property level portfolio by applying the same geographic diversity assessment we do under the RMBS criteria (see Related Criteria section). Such calculation, which uses an Herfindahl–Hirschman Index (HHI) calculation compared to a benchmark, considers the corresponding MSA (state if MSA is unavailable) representation at the property level and results in a geographic concentration adjustment factor. This factor will be higher for less diversified portfolios and lower for more diversified portfolios. If an SFR pool has a significant geographic concentration risk that we believe is not sufficiently captured by the Herfindahl Index, we may apply a higher geographic concentration adjustment factor.

The application of a geographic diversity test in RMBS is intended to capture both default risk (from MSA level economic stress) and the potential for greater property value depreciations compared to the national average. Although we assume a default occurs in SB SFR, elements within SFR like higher concentration, inventory increases, and tenant financial pressure can result in more concentrated SFR portfolios being subject to greater value pressure. We, therefore, apply the entirety of the factor when assessing both SB and MB SFR securitizations.

MB – large loan test

We also apply a large loan test at the 'B' rating level at the time of assigning initial ratings. We assume the largest loan in the pool defaults with a loss severity equal to the greater of 50% and the 'B' loss severity for the loan. This large loan 'B' loss amount is then compared to the 'B' loss amount of the pool computed using these criteria, and the higher of these two loss amounts is used as the 'B' loss amount for the pool. We may also consider borrower overlap or other concentration factors that may warrant additional amounts to be included in the large loan test.

Minimum credit enhancement (CE) levels

Our minimum CE levels are 1% and 10% for 'B' and 'AAA,' respectively, with rating levels in between interpolated linearly. While SFR transactions have features that resemble both RMBS and CMBS, our minimum CE levels more closely align with CMBS given the higher loan concentrations in SFR compared to RMBS, and the greater diversification of default risk and loan count that exists in RMBS compared to SFR and CMBS.

Transaction features and collateral preservation mechanics

These criteria are intended to recognize the features that SFR securitizations possess compared to those specific to RMBS and CMBS. We expect SFR transactions to include appropriate mechanisms to enable the preservation of property and seniority of liens, such as property tax and insurance provisions. We also assess protective features such as applicable covenants, guarantees, safeguards related to loan quality, and ongoing property insurance coverage. We also consider the insurance coverage as it relates to protecting against certain perils based on the property types in SFR securitizations. Also, the presence of certain transaction features may introduce incremental risk to the transaction, such as excess collateral release provisions or other features, which we would seek to address in our rating analysis. Generally, if we have concerns related to certain aspects of a transaction, we may increase credit enhancement associated with a given rating level and/or cap the rating we assign to the extent these risks are not mitigated and/or the governance protocols related to certain features are inadequate to mitigate such risks.

Legal risk

We consider legal risk within our broader analytical framework as outlined in the asset isolation and special-purpose entity (SPE) criteria (see the Related Criteria section). Given the hybrid nature of SFR transactions and characteristics that may resemble RMBS and/or CMBS, certain additional legal assessments may be applicable, such as demonstration of single-purpose borrower formation and governance, and ownership structure. As a result, we typically apply an approach that draws upon principles set-forth in our borrower level SPE CMBS criteria (see the Related Criteria section) for SB SFR securitizations and may apply this approach to MB SFR securitizations depending on factors such as loan balance, concentration, and other considerations.

Surveillance

When performing surveillance of SFR securitizations, rating outcomes and credit enhancement sufficiency are informed by the observed performance relative to our expectations and forward-looking views of performance. For example, a change in housing prices or over/undervaluation may not directly translate to a rating change depending on considerations, such as housing fundamentals, the anticipated time horizon of price movements, and the associated loan(s) maturity date.

APPENDICES

Appendix I (criteria scope)

These criteria apply to U.S. SFR transactions for which:

• Single-family properties (including but not limited to one-to-four-unit attached, detached, townhouse, and condominium properties) that are subject to rental leases and generate rental income make up the majority of collateral backing the underlying loan(s);
• Factors such as rental income, expenses, and capital expenditures can be estimated in the derivation of a long-term sustainable net cashflow, similar to a multifamily property evaluation under our commercial mortgage-backed securities (CMBS) criteria; and
• The loan(s) in the portfolio predominately have features more akin to commercial real estate mortgages as opposed to residential real estate mortgages (e.g., underwriting, reporting, and borrowing entity).

Given some of the factors outlined above, loan portfolios backing RMBS securitizations predominately comprising debt-service coverage ratio ("DSCR") loans would be out of the scope of these criteria and continue to be analyzed using our criteria for U.S. RMBS issued in 2009 and later (see the Related Criteria section).

We may apply the SB framework for transactions containing more than one loan based on factors such as borrower/sponsor/operator overlap, cross default provisions, and asset portfolio similarities/differences compared to typical SB transactions.

Appendix II (effective loan count)

The effective loan count accounts for the relative size of the loans in the pool by normalizing the loan count of a transaction in order to account for unevenly sized loans. Effective loan count may be adjusted based on factors such as sponsor/borrower overlap and geographic concentration. If the distribution of the loans in a pool is not uniform, the effective number of loans would be less than the unique number of loans in the pool. The formula used to calculate the pool-specific effective loan count is:

Appendix III (default analysis example – MB SFR)

We have created a hypothetical MB securitization example to illustrate the application of these criteria (see Section 2).

Table 6

Determine diversified 'B' anchor probability of default

For this MB portfolio, the diversified 'B' anchor PD would be 20% for 1.20 S&P DSC, based on table 1.

Determine adjusted diversified 'B' PD

In this example, we adjusted the diversified 'B' PD to 25% from 20%, considering additional factors such as a higher LTV compared to the benchmark, historical performance data, and loan underwriting.

As a result, the corresponding diversified 'AAA' PD, as well as the non-diversified 'B' PD and 'AAA' PD using table 2 would be:

Table 7

Determine final pool-specific PD

The pool-specific 'B' and 'AAA' PDs are then linearly interpolated between the corresponding diversified and non-diversified PDs using the pool-specific effective loan count of 35. As a result, our 'B' and 'AAA' PDs would be 43.4% and 73.2%, respectively:

• 'AAA' PD = 96% - (96%-58%)*(35-5)/(55-5) = 73.2%
• 'B' PD = 71% - (71%-25%)*(35-5)/(55-5) = 43.4%

These final 'B' and 'AAA' PDs, which are largely rooted in the portfolio S&P DSC and effective loan count but adjusted to account for other transaction features, would be applied to the 'B' and 'AAA' MB loss severities determined using Section 3.

IMPACT ON OUTSTANDING RATINGS

This is a new methodology; we do not have outstanding ratings for SFR transactions. Therefore, impact analysis is not applicable.

RELATED PUBLICATIONS

Related criteria

• Environmental, Social, And Governance Principles In Credit Ratings, Oct. 10, 2021
• Global Framework For Payment Structure And Cash Flow Analysis Of Structured Finance Securities, Dec. 22, 2020
• U.S. Structured Finance Asset Isolation And Special-Purpose Entity Criteria, May 15, 2019
• Counterparty Risk Framework: Methodology And Assumptions, March 8, 2019
• Methodology And Assumptions For Rating U.S. RMBS Issued 2009 And Later, Feb. 22, 2018
• Global Framework For Assessing Operational Risk In Structured Finance Transactions, Oct. 9, 2014
• Rating Methodology And Assumptions For U.S. And Canadian CMBS, Sept. 5, 2012
• CMBS Global Property Evaluation Methodology, Sept. 5, 2012
• Principles Of Credit Ratings, Feb. 16, 2011
• Assessing Borrower-Level Special-Purpose Entities In U.S. CMBS Pools: Methodology And Assumptions, Nov. 16, 2010
• Methodology For Servicer Risk Assessment, May 28, 2009

Related research

• S&P Global Ratings Definitions, updated from time to time
• RFC Process Summary: U.S. Single-Family Rental Securitization--Methodology And Assumptions, Feb. 20, 2024
• Criteria For Rating U.S. Single-Family Rental Securitizations Published, Feb. 20, 2024

This article is a Criteria article. Criteria are the published analytic framework for determining Credit Ratings. Criteria include fundamental factors, analytical principles, methodologies, and/or key assumptions that we use in the ratings process to produce our Credit Ratings. Criteria, like our Credit Ratings, are forward-looking in nature. Criteria are intended to help users of our Credit Ratings understand how S&P Global Ratings analysts generally approach the analysis of Issuers or Issues in a given sector. Criteria include those material methodological elements identified by S&P Global Ratings as being relevant to credit analysis. However, S&P Global Ratings recognizes that there are many unique factors / facts and circumstances that may potentially apply to the analysis of a given Issuer or Issue. Accordingly, S&P Global Ratings Criteria is not designed to provide an exhaustive list of all factors applied in our rating analyses. Analysts exercise analytic judgement in the application of Criteria through the Rating Committee process to arrive at rating determinations.