OUTDATED
METHODOLOGY
RATING
METHODOLOGY
RESIDENTIAL MBS
OU
ME
RATING
METHODOLOG
Y
Table of Contents:
SCOPE 1
RATING APPROACH 2
ASSET-LEVEL ANALYSIS AND RELATED
MODELING 3
STRUCTURAL ANALYSIS AND LIABILITY
MODELING 6
OTHER CONSIDERATIONS 7
MONITORING 8
APPENDICES 9
MOODY’S RELATED PUBLICATIONS 16
Analyst Contacts:
FRANKFURT +49.69.70730.700
Steven Becker +49.69.70730.939
Vice President – Senior Anal
y
st
steven.becker@moodys.com
LONDON +44.20.7772.5454
Barbara Rismondo +44.20.7772.5448
Senior Vice President/Manager
barbara.rismondo@moodys.com
» contacts continued on the second to last page
CLIENT SERVICES:
Americas: +1.212.553.1653
J
apan: +81.3.5408.4100
EME
A: +
44.20.7772.5454
Asia-Pacific
: +
852.3551.3077
DECEMBER 20, 2022
Reverse Mortgage Securitizations
Methodology
This rating methodology replaces Reverse Mortgage Securitizations Methodology published in
April 2020. We clarified how we apply our home price decline assumptions, and we made
editorial updates to enhance readability.
Scope
This rating methodology applie
s
s to securities backe
d
d b
y
y revers
e
e mortgag
e
e loans.
In this methodology, we explain our approach to assessing credit risks for reverse mortgage
securitizations, including quantitative and qualitative factors that are likely to affect rating
outcomes in this sector.
We discuss the asset and liability analysis, including associated modeling, as well as other
considerations. We also describe our monitoring approach.
This methodology is no longer in effect. For information
on rating methodologies currently in use by
Moody’s Investors
Service, visit ˫˫̭˭
OUTDATED
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2 DECEMBER 20, 2022 RATING METHODOLOGY: REVERSE MORTGAGE SECURITIZATIONS
RESIDENTIAL MBS
Rating Approach
I
I
n
n thi
s
s section
,
, w
e
e summariz
e
e ou
r
r approac
h
h t
o
o assessin
g
g credi
t
t risk
s
s fo
r
r securitie
s
s backe
d
d b
y
y revers
e
e
mortgag
e
e loans
,
, includin
g
g quantitativ
e
e an
d
d qualitativ
e
e factor
s
s tha
t
t ar
e
e likel
y
y t
o
o affec
t
t ratin
g
g outcome
s
s i
n
n
thi
s
s sector
.
.
Asset Description
A reverse mortgage is a mortgage loan – usually secured by a residential property – in which the main
source of repayment is the proceeds from the sale of the underlying home or prepayment by the borrower.
The reverse mortgage, which lenders typically market to older borrowers, is typically due and repayable
either upon the death of the borrower or when the borrower moves out of the home. We refer to these as
maturity events. The loans can feature a bullet repayment for the whole loan, or a series of repayments, or
take the form of a revolving credit line. Interest usually accrues until the loan is repaid. For certain product
types, the borrower agrees instead to sell a portion (or all) of the home at a discount in return for a lump
sum payment. The lender or buyer then receives a portion (or all) of the proceeds when the home is sold.
Key Risks
The major risk for investors in a reverse mortgage securitization is a decline in home values such that when
the homes underlying the securitized loans are sold, the proceeds are insufficient to pay off the original loan
amount and any accrued interest. To account for this risk, the main variable that we consider in our analysis
is the future price movement of the underlying homes in the asset pool. Since each loan’s maturity is
uncertain, the interest that can accrue and the exposure to home price movements are also uncertain.
Consequently, we also analyze the factors that can affect the loan maturity dates, such as expected
mortality rates for borrowers and the likelihood of moving out of the home before death.
In addition, cash flows are highly uncertain because reverse mortgages do not have regularly scheduled
payments. Consequently, we assess the extent to which the transaction’s assets or reserve funds provide
sufficient cash to make the required payments on the securities and transaction fees. In our assessment, we
incorporate any additional risk that might arise if the securities have a variable interest rate.
To analyze the risks, we stress each of the related variables to levels we deem consistent with the target
rating on the securities, applying greater stress to the risk variables the higher the rating. We use a cash flow
model of the transaction to determine whether investors would be paid in full in the stress scenario. The
cash flow model generally represents how the transaction allocates cash flows from the assets, credit
enhancement, and hedging vehicles among the various transaction participants, as well as how it allocates
asset losses. It also models how triggers within the transaction change those allocations.
In determining our ratings, we may also consider the results from other stressed combinations of the risk
variables to account for idiosyncrasies in a particular transaction, such as correlations across the variables or
concentrations among the assets. Model outputs derived by our quantitative modeling are important
considerations in our rating committee process. However, the ratings assigned by the rating committee also
incorporate a variety of qualitative factors, including operational, counterparty and legal risks, as well as
underwriting and servicing practices. As a result, the assigned rating may differ from the model output.
This publication does not
announce a credit rating action.
For any credit ratings referenced in
this publication, please see the
issuer/deal page on
ratings.moodys.com for the most
updated credit rating action
information and rating history.
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3 DECEMBER 20, 2022 RATING METHODOLOGY: REVERSE MORTGAGE SECURITIZATIONS
RESIDENTIAL MBS
Asset-level Analysis and Related Modeling
I
I
n
n thi
s
s section
,
, w
e
e explai
n
n ho
w
w w
e
e analyz
e
e th
e
e underlyin
g
g asset
s
s tha
t
t bac
k
k revers
e
e mortgag
e
e securitization
s
s
an
d
d ho
w
w w
e
e estimat
e
e potentia
l
l losse
s
s o
n
n thos
e
e assets
.
.
Home Price Risk
Repayment of a reverse mortgage loan depends on the net liquidation proceeds from the sale of the
property,
1
and thus our home price assumptions play a key role in our approach. In our scenarios, we
generally assume a decline in home prices occurs in the first year of the transaction and no decline for B2
(sf)-rated securities. Furthermore, we typically assume no price appreciation for Aaa (sf)-rated securities. For
outstanding transactions, the decline occurs the year of the review date.
Home Price Decline Assumptions
Home price decline is a more critical assumption for reverse mortgage-backed securities than for standard
residential mortgage-backed securities (RMBS) for two key reasons: unlike standard RMBS, where only
defaulted properties are liquidated, all properties with reverse mortgages - if not prepaid - are eventually
sold. In addition, the average life of a reverse mortgage transaction is much longer than an RMBS
transaction.
As a starting point for our Aaa (sf) home price decline assumptions, we apply a stress similar to one
applicable to a portfolio of residential mortgage loans under our country-specific asset modeling approach.
In the US, we typically use a fixed home price decline assumption similar to the one described in our US
RMBS methodology
2
and apply this assumption throughout the transaction’s life. For countries where the
home price decline assumption varies over time, we typically consider a “through-the-cycle” concept, i.e.,
an average stress decline over a long-term period, to maintain stability in that assumption. For B2 (sf)-rated
securities, we typically assume no price decrease in the first year. For securities with ratings ranging from
Aa2 (sf) to Ba2 (sf) as per the tables in Appendix A, the home price decline is typically based on an
interpolation of the stresses applied in Aaa (sf) and B2 (sf) scenarios. Our home price decline assumption
includes foreclosure costs.
We may apply a higher stress (at each rating level) for home price decline assumptions if there are specific
risks in the transaction or unusual concentrations in the reverse mortgage pool, such as geographic
concentrations, which make it more likely that a regional downturn could cause a significant decline in the
overall pool performance.
Our home price decline assumptions for reverse mortgages in a severe stress scenario could be higher than
the assumptions we use to rate standard RMBS transactions because of (1) the higher sensitivity to home
price declines in a reverse mortgage transaction since all of the properties need to be sold - if not prepaid;
(2) the potential selection bias in terms of borrower (borrowers who expect to live longer) and property type
(higher value properties); and (3) the uncertainty regarding the level of property maintenance. However, a
strong mitigant to the above factors is the lack of correlation in reverse mortgages between the timing of a
sale and the home price cycle. This contrasts with the correlation between severe home price declines and
higher defaults and subsequent foreclosures among residential mortgage borrowers. In addition, in reverse
mortgage transactions we conservatively apply the home price decline to the whole portfolio in the first
year of the transaction for the Aaa to Ba2 scenarios.
1
We typically index the property value at the analysis date.
2
For more information, see our methodology for rating US RMBS. A link to a list of our sector and cross-sector methodologies can be found in the “Moody’s Related
Publications” section.
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4 DECEMBER 20, 2022 RATING METHODOLOGY: REVERSE MORTGAGE SECURITIZATIONS
RESIDENTIAL MBS
Home Price Appreciation Assumptions
We set the long-term assumption for home price appreciation at zero for Aaa (sf)-rated securities. For B2
(sf)-rated securities, we typically apply a growth rate which is a stable approximation of our expected long-
term growth rate. For securities with ratings ranging from Aa2 (sf) to Ba2 (sf) as per the tables in Appendix
A, the growth rate is typically based on an interpolation of the appreciation applied in Aaa (sf) and B2 (sf)
scenarios. We may apply lower home price appreciation assumptions (at each rating level) if there are
specific risks in the transaction or in the reverse mortgage pool.
Our home price appreciation assumptions incorporate an expectation that the homes of reverse mortgage
borrowers will appreciate less on average than those of the population as a whole because of the following
factors:
» Reverse mortgage borrowers are relatively unlikely to repair or refurbish their homes given that part or
all of the upside in value will mostly benefit the reverse mortgage provider. A decline in the value of the
home will also not leave the borrower’s estate with unpaid mortgage debt (the debt would be
extinguished).
» In contrast with a traditional mortgage, the balance on a reverse mortgage rises over time, which
increases the likelihood that the homeowner’s equity stake will be wiped out, reducing the incentive to
maintain the home.
See Appendix A for our typical country-specific home price decline and appreciation assumptions. When
relevant, we may also consider alternative home price appreciation assumptions.
Reverse Mortgage Maturity
Reverse mortgages mature when the borrower dies or, in the case of co-borrowers, when both die (mortality
event). When the borrower moves into long-term care (morbidity event) or when the borrower repays the
loan (prepayment or mobility event), the reverse mortgage will also mature. For each mortgage in the pool,
we estimate the probability of maturity in each year after origination, taking these types of events into
account.
Timing of Mortality Events
We establish baseline assumptions for the timing of mortality events using the mortality rates compiled in
the country of the securitization, typically by the life insurance industry, to the extent that they are
available. Typically, the mortality rates are stratified by gender and age, allowing us to distinguish broadly
among types of borrowers in the pool. If data in a particular country are not available, we may use data
from comparable countries and adjust accordingly for possible discrepancies.
In light of their sociodemographics, we assume longer life expectancy for the population of borrowers that
use reverse mortgages than for the general population, but reasonably equivalent to that of a life insurance
annuitant population. Therefore, we may also adjust the data to account for likely differences between the
population reflected in the historical data and the borrowers in the pool.
Another factor that we account for is whether the mortgage has a single obligor or joint obligors. A reverse
mortgage maturity event caused by mortality is triggered by the death of the second individual in a couple.
Therefore, when there are joint borrowers, we calculate the mortality rate for the couple, which is the joint
probability of both obligors’ death. Consequently, near-term mortality rates for couples are considerably
lower than the mortality rates of individuals.
Our analysis of the likely mortality rates of the pool also incorporates expectations of changes in life
expectancies resulting from improvements in living standards and in healthcare technology and availability.
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5 DECEMBER 20, 2022 RATING METHODOLOGY: REVERSE MORTGAGE SECURITIZATIONS
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We typically assume in our analysis more improvement for higher-rated securities than for lower-rated
securities, resulting in greater longevity and, thus, a higher stress. See Appendix B for more information. In
addition, we may apply different improvement factors if the pool is concentrated in a specific cohort (for
example, in cases where all borrowers have similar ages).
Timing of Morbidity and Mobility Events
In our analysis, we distinguish between two sources of prepayments, which are influenced by different
factors and treated differently in reverse mortgage contracts. Borrowers who move to a long-term care
facility or nursing home due to health reasons (which is usually referred to as a morbidity event) typically do
not incur a prepayment penalty (i.e., properties are sold without additional costs) on a reverse mortgage,
while borrowers who move out for other reasons (usually referred to as a mobility event) can incur a
prepayment penalty. In addition, borrowers who prepay the reverse mortgage outside of these
circumstances can also incur a prepayment penalty. The most important factors determining the likelihood
of a health-related morbidity event are the age of the borrower(s) and whether there is a single borrower or
joint borrowers. For example, older borrowers are more likely to need the services of long-term care
facilities or nursing homes, and there is a higher likelihood that a single person will need those services than
both people in a joint-borrower mortgage. In contrast, older borrowers are less likely to move for non-
health-related reasons.
There is often little incentive for reverse mortgage borrowers to prepay their loans, causing a mobility event.
Typically, prepayments are highest in the early years of a transaction in instances where the borrower
decides that the reverse mortgage product was unsuitable. In addition, borrower mobility typically declines
with age. Higher home price appreciation rates can also result in higher prepayment rates as borrowers look
to withdraw equity from their homes to repay debts. Conversely, prepayments could fall as home prices
decline. Interest rate changes can also affect prepayment rates, with interest rate declines inducing some
fixed-rate borrowers to prepay their loans as they start shopping for lower rates.
We derive the prepayment and morbidity rates, which are typically low single-digit numbers, based on the
portfolio’s characteristics, the rating scenario and available market data. In our analysis, we may reduce the
prepayment and morbidity rates to zero when considering high rating scenarios and in cases where there is
not sufficiently reliable data or prepayment penalties are high.
Interest Rate Risk
Transactions with variable interest rates on either assets or liabilities or both are subject to interest rate risk.
For example:
» For transactions with floating-rate bonds and fixed rates on the mortgages, there is a risk that the
interest rates on the liabilities will rise.
3
» For transactions with variable rates on both assets and liabilities, there is a risk that the spread between
the interest rate on the assets and the rate on the securities will move adversely. In addition, even if the
spread between the rates remains constant, increases or decreases in the overall interest rate can
positively or negatively affect the credit quality of the transaction, depending on how home prices
move and the transaction structure.
» For transactions with variable rates on the assets (mortgages) and fixed rates on the securities, the risk
is that the interest rates on the assets will decline.
3
For more information, see our methodology for assessing counterparty risks in structured finance transactions. A link to a list of our sector and cross-sector
methodologies can be found in the “Moody’s Related Publications” section.
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6 DECEMBER 20, 2022 RATING METHODOLOGY: REVERSE MORTGAGE SECURITIZATIONS
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Consequently, in transactions with variable rates, we review the results of the cash flow model assuming
various levels of interest rates to capture the appropriate risk.
In the base case, we generally assume an interest rate level based on the applicable home price growth rate
for each rating stress, while typically maintaining a fixed differential between long-term interest rates and
home price growth rates after the initial home price decline. For example, in our Aaa scenario where we
assume a severe home price decline with no recoveries, we generally assume a low interest rate of 1%
throughout the transaction’s life. See Appendix A for our typical country-specific interest rate and home
price growth rate stresses.
We use our stress assumptions for home price changes, the timing of maturity events, and interest rates on
the mortgages to estimate the probability-based cash flows that would be generated by each reverse
mortgage in the asset pool. We use the interest rates on the loans to generate the loan balance in each
future period and the timing of maturity events to calculate the probability-based portion of the loan
balance paid down each period. See Appendix C for an example of how we determine the cash flow from a
single hypothetical reverse mortgage.
Data for Collateral Analysis
To perform the collateral analysis described above, we typically receive loan-level data on loan balance,
borrower(s) age, gender, latest available property value, valuation type, property location, property type,
interest on the loan and other information specific to the loan product type.
Structural Analysis and Liability Modeling
I
I
n
n thi
s
s section
,
, w
e
e explai
n
n ho
w
w w
e
e analyz
e
e th
e
e structura
l
l feature
s
s o
f
f revers
e
e mortgag
e
e securitizations
,
,
includin
g
g ho
w
w w
e
e mode
l
l an
d
d allocat
e
e cas
h
h flow
s
s t
o
o differen
t
t classe
s
s o
f
f securities
,
, takin
g
g int
o
o accoun
t
t asse
t
t
cas
h
h flow
s
s an
d
d availabl
e
e credi
t
t support
.
.
Cash Flow Model
We combine the cash flows generated by the reverse mortgages in the asset pool with any cash flows
generated by hedging instruments in the securitization. We then use a model of the transaction that
incorporates how it allocates cash flows and losses, the triggers that change those allocations, the interest
rates on the securities, and the credit enhancement (including guarantees)
4
to determine whether those
cash flows would be sufficient to pay investors in full and on a timely basis. The model output corresponds
to the rating consistent with the most stressful scenario the security could withstand without any losses.
Additionally, we also account for the potential loss severity of a tranche in relation to its thickness when
determining the rating.
Liquidity Risk
There are no regularly scheduled payments on reverse mortgages, but the payments of interest and
sometimes principal on the structured securities are due regularly. Consequently, in our analysis, we assess
the extent to which there will likely be sufficient cash flow from the assets (in the stress scenarios) and from
other sources (such as reserve funds) to pay interest and mandatory scheduled principal when relevant on
the securities. To assess the other sources of cash required in the transaction, we consider the consequences
of missed payments for each class of securities, as well as the likelihood and potential length of interest
payment deferral. In addition, we consider in our analysis whether there are mechanisms in place to
4
For special considerations regarding home equity conversion mortgages (HECMs) guaranteed by the Federal Housing Administration (FHA), see Appendix D.
OUTDATED
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7 DECEMBER 20, 2022 RATING METHODOLOGY: REVERSE MORTGAGE SECURITIZATIONS
RESIDENTIAL MBS
replenish such reserve funds, if necessary. For securities with floating interest rates, we incorporate into our
analysis the risk that interest rates may rise over the life of the transaction to test that interest is paid
regularly even if the pool has not generated any cash.
5
Other Considerations
A
Alon
g
g wit
h
h ou
r
r asset
,
, structura
l
l an
d
d liabilit
y
y analysis
,
, w
e
e conside
r
r othe
r
r quantitativ
e
e an
d
d qualitativ
e
e factor
s
s
i
n
n ou
r
r credi
t
t analysi
s
s suc
h
h a
s
s transactio
n
n counterparties
,
, lega
l
l risks
,
, reliabilit
y
y an
d
d completenes
s
s o
f
f
historica
l
l an
d
d portfoli
o
o data
,
, an
d
d environmental
,
, socia
l
l an
d
d governanc
e
e (ESG
)
) considerations
.
.
Counterparty Risks
We consider various counterparty-related risks at different stages throughout our credit analysis. More
specifically, the risks we consider include hedge counterparties and operational risks.
6
Based on our review,
we may adjust our assumptions, inputs or model results. If information is limited, we may also adjust the
rating level.
Hedge Counterparties
We analyze the rating impact of exposures to hedge counterparties including assessing the probability of a
transaction becoming unhedged and deriving additional potential losses. As part of our analysis, we may
conclude that we adjust the ratings to reflect the linkage and additional loss.
Operational Risk
Operational risks can arise from various potential sources, including disruption to cash flows caused by the
financial distress of a service provider to a reverse mortgage securitization. As part of our analysis, we
consider the financial disruption risk and the roles of relevant transaction parties.
Similar to other RMBS asset classes, our servicer quality analysis in reverse mortgage transactions addresses
the impact of servicer practices on the performance of the mortgage pool.
7
Reverse mortgages also pose
unique servicing challenges. Unlike traditional mortgage transactions, reverse mortgage transactions do not
require the servicer to process payments or make collection calls. Its responsibilities instead generally
include determining each property’s occupancy status (to determine if a maturity event has occurred),
updating the property values using a desktop or indexed valuation (generally when the borrower defaults)
and ensuring that payment of insurance is current. We update this assessment as necessary as we monitor
transactions and incorporate our views on the servicer’s quality.
Legal Risks
We assess legal risks that may affect the expected losses posed to investors. In particular, we consider the
potential legal consequences of whether the issuer is bankruptcy remote. We review legal opinions at
closing to inform our views on the key legal risks identified in a transaction.
Our legal analysis focuses on the risks posed by the potential bankruptcy of the transaction originator,
securitization entity, servicer and other relevant parties. We also consider the consumer protection laws and
regulations applicable to the reverse mortgage loans, the obligors and the originators. For example,
5
For more information, see Appendix A.
6
For more information, see our methodology for assessing counterparty risks in structured finance transactions. A link to a list of our sector and cross-sector
methodologies can be found in the “Moody’s Related Publications” section.
7
For more information, see our methodology for assessing counterparty risks in structured finance transactions. A link to a list of our sector and cross-sector
methodologies can be found in the “Moody’s Related Publications” section.
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8 DECEMBER 20, 2022 RATING METHODOLOGY: REVERSE MORTGAGE SECURITIZATIONS
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borrowers or heirs could challenge mortgage agreements, and aggressive cross-marketing of other financial
products, such as long-term annuities, could pose legal or reputational risks.
Data Quality Evaluation
We assign ratings to securities issued by reverse mortgage securitization when we have sufficient
information from reliable sources. Data quality is also important throughout the life of a reverse mortgage
transaction.
8
Environmental, Social and Governance Considerations
Environmental, social and governance (ESG) considerations may affect the ratings of securities backed by a
portfolio of reverse mortgage loans. We evaluate the risk following our cross-sector methodology that
describes our general principles for assessing these ESG issues
9
and may incorporate it in our analysis.
Monitoring
I
I
n
n thi
s
s section
,
, w
e
e describ
e
e ou
r
r approac
h
h whe
n
n monitorin
g
g transactions.
We generally apply the key components of the approach described in this methodology when monitoring
transactions, except for those elements of the methodology that could be less relevant over time, for
example some elements of a legal risk.
We receive periodic information for the purpose of monitoring the transaction. More specifically, we track
portfolio and loan-level information as well as information relating to the capital structure and credit
enhancement.
10
We may also gather updated information on other factors such as annual life improvement
factors, changes in house prices and foreclosure costs. The starting point is typically the monitoring of the
collateral performance relative to our initial expectations.
Our monitoring analysis may also include ongoing assessment of any entity whose ability to fulfill its
contractual obligation to the transaction could affect the cash flows that investors receive. Typically, those
entities would include the servicer, swap counterparties and credit support providers. Changes in the
financial stability of an entity could affect the credit quality of the securities. As pools season and borrowers
become older, the servicer’s role, in particular, becomes more important; for example, through active
monitoring of the properties’ occupancy status. We will reassess servicer quality as necessary as we monitor
transactions.
We may, at times, ask for additional information to adequately monitor our ratings.
11
8
For more information, see our approach to evaluating date quality in structured finance transactions. A link to a list of our sector and cross-sector methodologies can be
found in the “Moody’s Related Publications” section.
9
For more information, see our methodology that describes our general principles for assessing ESG issues. A link to a list of our sector and cross-sector methodologies
can be found in the “Moody’s Related Publications” section.
10
For example, in methodologies where models are used, modeling is not relevant when it is determined that (1) a transaction is still revolving and performance has not
changed from expectations, or (2) all tranches are at the highest achievable ratings and performance is at or better than expected performance, or (3) key model inputs
are viewed as not having materially changed to the extent it would change outputs since the previous time a model was run, or (4) no new relevant information is
available such that a model cannot be run in order to inform the rating, or (5) our analysis is limited to asset coverage ratios for transactions with undercollateralized
tranches, or (6) a transaction has few remaining performing assets.
11
For more information on our guidelines for assessing data quality in global structured finance transactions, a link to a list of our sector and cross-sector methodologies
can be found in the “Moody’s Related Publications” section.
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9 DECEMBER 20, 2022 RATING METHODOLOGY: REVERSE MORTGAGE SECURITIZATIONS
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Appendix A: Assumptions for Home Prices and Interest Rates
The following tables illustrate the home price decline, home price growth rate and interest rate assumptions
we typically apply in the US, UK and Australia for different rating categories.
EXHIBIT 1
UK Assumptions for Home Price and Interest Rates
Target Rating Aaa (sf) Aa2 (sf) A2 (sf) Baa2 (sf) Ba2 (sf) B2 (sf)
Home price decline over 1 year 35%* 25% 20% 15% 10% 0%
Growth rate after 1 year 0% 1.5% 2.0% 2.5% 3.0% 3.0%**
Home price returns to level at the
time of analysis
Never 20.5 years 12.5 years 8 years 5 years N/A
Interest rate level 1% 2.5% 3.0% 3.5% 4.0% 4.0%
* This is based on the country-specific home price decline assumption we use when analyzing residential mortgage loan portfolios, although
considering a “through-the-cycle” concept. The assumed home price decline of 35% over 1 year may be adjusted if deemed appropriate (e.g., to
reflect portfolio concentrations or transaction-specific risks). For securities with ratings ranging from Aa2 (sf) to Ba2 (sf), the home price decline is
typically based on an interpolation of the stresses applied in a Aaa (sf) and B2 (sf) scenarios.
** For securities with ratings ranging from Aa2 (sf) to Ba2 (sf), the growth rate is typically based on an interpolation of the stresses applied in a Aaa
(sf) and B2 (sf) scenarios.
Source: Moody’s Investors Service
EXHIBIT 2
US Assumptions for Home Price and Interest Rates (Active Reverse Mortgages)
Target Rating Aaa (sf) Aa2 (sf) A2 (sf) Baa2 (sf) Ba2 (sf) B2 (sf)
Home price decline over 1 year 30%* 25% 20% 15% 10% 0%
Growth rate after 1 year 0% 1.5% 2.0% 2.5% 3.0% 3.0%**
Home price returns to level at the
time of analysis
Never 20.5 years 12.5 years 8 years 5 years N/A
Interest rate level 1% 2.5% 3.0% 3.5% 4.0% 4.0%
* This is based on the country-specific home price decline assumption we use when analyzing residential mortgage loan portfolios. The assumed
home price decline of 30% (for a diversified portfolio) over 1 year may be adjusted if deemed appropriate (e.g., to reflect portfolio concentrations
or transaction-specific risks). For securities with ratings ranging from Aa2 (sf) to Ba2 (sf), the home price decline is typically based on an
interpolation of the stresses applied in a Aaa (sf) and B2 (sf) scenarios.
** For securities with ratings ranging from Aa2 (sf) to Ba2 (sf), the growth rate is typically based on an interpolation of the stresses applied in a Aaa
(sf) and B2 (sf) scenarios.
Source: Moody’s Investors Service
EXHIBIT 3
Australia Assumptions for Home Price and Interest Rates
Target Rating Aaa (sf) Aa2 (sf) A2 (sf) Baa2 (sf) Ba2 (sf) B2 (sf)
Home price decline over 1 year 40%* 32% 24% 16% 8% 0%
Growth rate after 1 year 0% 1% 1.5% 2% 2.5% 2.5%**
Home price returns to level at the
time of analysis
Never 40 years 19 years 10 years 4 years N/A
Interest rate level 1% 2% 2.5% 3% 3.5% 3.5%
* This is based on the country-specific home price decline assumption we use when analyzing residential mortgage loan portfolios, although
considering a” through-the-cycle” concept. The assumed home price decline of 40% over 1 year may be adjusted if deemed appropriate (e.g., to
reflect portfolio concentrations or transaction-specific risks). For securities with ratings ranging from Aa2 (sf) to Ba2 (sf), the home price decline is
typically based on an interpolation of the stresses applied in a Aaa (sf) and B2 (sf) scenarios.
** For securities with ratings ranging from Aa2 (sf) to Ba2 (sf), the growth rate is typically based on an interpolation of the stresses applied in a Aaa
(sf) and B2 (sf) scenarios.
Source: Moody’s Investors Service
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When relevant, we may also consider alternative scenarios to determine the sensitivity of our ratings to
various assumptions.
We may also review the results of liquidity stress scenarios assuming higher interest rate levels. In such
scenarios, we assess the extent to which the transaction characteristics and other cash sources can provide
sufficient cash flow to pay interest on the securities.
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Appendix B: Application of Ratings-Based Longevity Improvement Stresses
We established the following approach to estimating future mortality improvements in the US, UK and
Australia from their historical mortality improvement rates and based on the opinion of external longevity
experts. We will develop similar approaches for other countries as the need arises, based on the information
available in those countries.
Base-Case Scenario: Annual Improvement Factor Approach
We apply annual mortality improvement factor stresses based on rating levels and current age. Exhibits 4
and 6 illustrate the typical improvement factor stresses. For the Aaa (sf) scenario, we generally assume a 5%
annual mortality improvement in the US, while in the UK and Australia, we assume a 7.5% mortality
improvement for ages 60-69 and 5% for ages 70 and higher. We also cap the borrower age at 120.
EXHIBIT 4
US: Assumptions for Mortality Improvement Factor Stress
Age Aaa (sf) Aa2 (sf) A2 (sf) Baa2 (sf) Ba2 (sf) B2 (sf)
60-120 5.0% 4.0% 3.0% 2.0% 1.5% 1.5%
Source: Moody’s Investors Service
EXHIBIT 5
UK and Australia: Assumptions for Mortality Improvement Factor Stress
Age Aaa (sf) Aa2 (sf) A2 (sf) Baa2 (sf) Ba2 (sf) B2 (sf)
60-69 7.5% 6.5% 5.5% 4.5% 3.5% 3.5%
70-120 5.0% 4.0% 3.0% 2.0% 1.5% 1.5%
Source: Moody’s Investors Service
Sensitivity Scenario: Age-Setback Approach
We may also apply an age-setback approach to determine the reasonableness of our baseline scenario for
future improvement in expected life. In this case, we will not apply any improvement factor stresses. In the
Aaa (sf) scenario, we typically use an age setback of 10 years, which effectively means that a 70-year-old is
assumed to have the mortality rates of a 60-year-old, and hence increases the expected life.
EXHIBIT 6
Age-Setback Approach for the US, the UK and Australia
Aaa (sf) Aa2 (sf) A2 (sf) Baa2 (sf) Ba2 (sf) B2 (sf)
10 years 8 years 6 years 4 years 2 years 2 years
Source: Moody’s Investors Service
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Appendix C: Illustrative Example of Determining Cash Flow for a Sample Reverse
Mortgage
The following is an example of how we determine the cash flow from a sample reverse mortgage, taking
into account expected improvements in mortality rates. We calculate the maturity event rate which
represents the probability that a loan is repaid in a given year, with repayment triggered by the death of any
remaining obligors.
Define:
»
t
as the number of years since the date of our analysis.
» ݍ
(
ݐ
)
as the one year probability of death t years in the future for an individual who has survived
through year t-1.
In our example below, the individual who is the remaining obligor has lived up to age 60, so q(1) is the
probability of death in the 61
st
year of age (given that the individual has lived to age 60). Likewise, q(2) is the
probability of death in the 62
nd
year of age, conditional on the individual having lived to age 61, and so on.
» ܫܨ as the improvement factor that represents the annual rate of improvement in mortality of an
individual, or equivalently, the reduction in the conditional one year mortality rate q(t).
» ݏ
(
ݐ
)
= ൫1 െݍ
(
ݐ
)
൯כݏ(ݐെ1) as the probability that the individual is still alive after a period of t years
following the date of our analysis, with ݏ
(
0
)
=1.
»
(
ݐ
)
= ݍ
(
ݐ
)
כݏ(ݐെ1) as the maturity event rate, i.e., the probability that the individual will repay (by
way of death) t years following the date of our analysis. We assume that Σ p(t) =1.
» ܳ
(
ݐ
)
= ݍ
(
ݐ
)
כ (1 െܫܨ)^(ݐെ1) as the adjusted conditional one year probability of death ݍ
(
ݐ
)
after
accounting for the improvement factor IF.
» ܵ
(
ݐ
)
= [1െܳ(ݐ)] כܵ(ݐെ1) as the adjusted probability that the individual is still alive after a period
of t years following the date of our analysis, after accounting for the improvement factor IF, with
ܵ
(
0
)
=1.
» ܲ
(
ݐ
)
=
Q(t)*S(t-1)
as the maturity event rate adjusted for the improvement factor IF.
The exhibit below shows how we calculate the maturity event rates p(t) and P(t) using both 0% and 2%
improvement factors:
12
12
For this example, we will use ݍ
(
ݐ
)
based on the years 2015-2017 from the UK Office for National Statistics. We typically use individual annuity mortality tables from the
Society of Actuaries for the US and from the Bureau of Statistics for Australia.
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EXHIBIT 7
Maturity Event Rates
No mortality improvement:
IF equal to 0%
Adjusted
conditional prob
of death assuming
IF equal to 2%
Mortality improvement:
IF equal to 2%
t
q(t)
s(t) = [1- q(t)] *
s(t-1)
p(t) = q(t) *
s(t-1)
Q(t) = q(t)*
(1-IF)^(t-1)
S(t) = [1 - Q(t)]
*S(t-1)
P(t) = Q(t) *
S(t-1)
1 0.7955% 99.20% 0.80% 0.80% 99.20% 0.80%
2 0.8614% 98.35% 0.85% 0.84% 98.37% 0.84%
3 0.9324% 97.43% 0.92% 0.90% 97.49% 0.88%
4 1.0484% 96.41% 1.02% 0.99% 96.52% 0.96%
5 1.1447% 95.31% 1.10% 1.06% 95.51% 1.02%
6 1.2244% 94.14% 1.17% 1.11% 94.45% 1.06%
7 1.3496% 92.87% 1.27% 1.20% 93.32% 1.13%
8 1.4599% 91.51% 1.36% 1.27% 92.14% 1.18%
9 1.5607% 90.09% 1.43% 1.33% 90.91% 1.22%
10 1.7228% 88.53% 1.55% 1.44% 89.61% 1.31%
Source: Moody’s Investors Service
Assuming the following property and loan characteristics:
» Loan balance on the date of our analysis (LB(0)) = £ 150,000
» Property value on the date of our analysis (PV(0)) = £ 300,000
» Fixed interest rate (r) = 5%
» HPI growth rate (HPI rate) = 2%
The exhibit below shows a simplified example of how we determine the probability-based cash flows from a
reverse mortgage:
EXHIBIT 8
Reverse Mortgage Cash Flow Calculations
t Property Value Loan Balance Cash flow assuming IF 0% Cash flow assuming IF 2%
PV(0) * (1+HPI rate)^t LB(0) * (1+r)^t min(PV(t), LB(t)) * p(t) min(PV(t), LB(t)) * P(t)
1 £306,000 £157,500 £1,253 £1,253
2 £312,120 £165,375 £1,413 £1,385
3 £318,362 £173,644 £1,592 £1,530
4 £324,730 £182,326 £1,862 £1,754
5 £331,224 £191,442 £2,113 £1,951
6 £337,849 £201,014 £2,346 £2,125
7 £344,606 £211,065 £2,682 £2,383
8 £351,498 £221,618 £3,005 £2,621
9 £358,528 £232,699 £3,324 £2,847
10 £365,698 £244,334 £3,792 £3,191
Source: Moody’s Investors Service
The two exhibits below show the maturity event rates and the cash flow per period, with and without the
improvement factor.
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EXHIBIT 9
Comparison of Maturity Event Rates (with and without improvement factor)
Source: Moody’s Investors Service
EXHIBIT 10
Comparison of Cash Flow per Period (with and without improvement factor)
Source: Moody’s Investors Service
0. 00%
0. 50%
1. 00%
1. 50%
2. 00%
2. 50%
3. 00%
3. 50%
4. 00%
4. 50%
5. 00%
1 3 5 7 9 1113151719212325272931333537394143454749515355575961
Maturity event rate
Years since the analysis date
Maturity event rate assuming 2% IF Maturity event rate assuming no IF
£0
£5 ,0 00
£1 0, 000
£1 5, 000
£2 0, 000
£2 5, 000
135791113151719212325272931333537394143454749515355575961
Cash flow per period
Years since the anal ysi s date
Cash flow p er perio d assuming no IF Cash Flow per perio d a ssumi ng 2% I F
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Appendix D: Special Considerations for FHA-Guaranteed HECMs in the US
Home equity conversion mortgages are a type of reverse mortgage in the US that is guaranteed by the
Federal Housing Administration (FHA). The FHA guarantees any deficiency between the loan balance and
the home value, as long as the home is sold within six months of entering real-estate-owned (REO) status.
13
If the servicer does not sell the home within six months of it entering REO status, the FHA requires that the
servicers obtain an appraisal of the property from a Department of Housing and Urban Development (HUD)
approved appraiser, and the FHA will only guarantee the deficiency up to the appraisal value. Therefore, if
the home is subsequently sold for less than the appraisal value, the FHA covers the difference between the
outstanding value of the loan and the appraisal value, but the securitization suffers a loss equal to the
difference between the appraisal value and the actual sale price of the home.
Therefore, to analyze the loss potential of HECMs, we assess the following factors:
» The extent to which a home is likely to have positive equity in each period after origination, using our
stress assumptions for the timing of maturity events, home price changes, and the interest rates on the
mortgages
» The likelihood that a home will not sell within six months of entering REO status
» The likely shortfall between the appraisal value (determined in the HUD-mandated appraisal conducted
six months after entering REO) and the sale price of the home
» One-third of the costs of foreclosure that is unreimbursed by HUD
Typically, we assume that 85% of HECMs with negative equity will not be sold within the six-month REO
window and will therefore be subject to the FHA-mandated appraisal. Our assumptions regarding the likely
shortfall between the appraisal value and the sale price of the home is ratings-based, as Exhibit 11 shows.
We also generally assume that the cost of foreclosure on each liquidated property will be close to historical
average values.
EXHIBIT 11
Assumed Shortfalls Between Home Sale Prices and Appraisal Values for FHA-Mandated Appraisals
Rating Level Assumed Shortfall Time Horizon
Aaa (sf) 20% Until Maturity
Aa2 (sf) 20% Until Maturity
A2 (sf) 20% 10 years and 0% thereafter
Baa2 (sf) 20% 5 years and 0% thereafter
Ba2 (sf) 20% 3 years and 0% thereafter
B2 (sf) 20% 2 years and 0% thereafter
Source: Moody’s Investors Service
13
A reverse mortgage typically enters REO status if it does not sell in a foreclosure sale, which usually takes place six months after the mortgage becomes due.
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16 DECEMBER 20, 2022 RATING METHODOLOGY: REVERSE MORTGAGE SECURITIZATIONS
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Moody’s Related Publications
Credit ratings are primarily determined through the application of sector credit rating methodologies.
Certain broad methodological considerations (described in one or more cross-sector rating methodologies)
may also be relevant to the determination of credit ratings of issuers and instruments. A list of sector and
cross-sector credit rating methodologies can be found here.
For data summarizing the historical robustness and predictive power of credit ratings, please click here.
For further information, please refer to Rating Symbols and Definitions, which is available here.
OUTDATED
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17 DECEMBER 20, 2022 RATING METHODOLOGY: REVERSE MORTGAGE SECURITIZATIONS
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» contacts continued from page 1
Analyst Contacts:
NEW YORK +1.212.553.1653
Padma Ra
j
a
g
o
p
al +1.212.553.7997
Vice President - Senior Credit Officer/Mana
g
er
padma.rajagopal@moodys.com
Yehudah Forster +1.212.553.7995
Senior Vice President – Structured Finance Legal
Review
y
Karandee
p
Bains +1.212.553.1441
Senior Vice President / Mana
g
er
karandeep.bain[email protected]
UTDATED
ODO
SYDNEY +61.2.9270.8100
J
ac
q
ui Dred
g
e +61.2.9270.1422
A
ssistant Vice President - Anal
y
st
j
Il
y
a Serov +61.2.9270.8162
A
ssociate Mana
g
in
g
Director
OUTDATED
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Author
Pier Paolo Vaschetti
Report Number: 1345695
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