Article Archives

Nearly $8 Trillion in Senior Home Equity Pushes Reverse Mortgage Market Index Upward

The NRMLA/RiskSpan Reverse Mortgage Market Index (RMMI) rose to 280.99 during the third quarter of 2020, an all-time high. This reflects a 1.6% increase in senior home equity, which now stands at an estimated $7.82 trillion. Growth in senior homeowner’s wealth was largely attributable to an estimated 1.6% (or $149 billion) increase in senior housing value, offset by 1.6% (or $28 billion) increase of senior-held mortgage debt.

The National Reverse Mortgage Lenders Association (NRMLA) and RiskSpan have published the Reverse Mortgage Market Index (RMMI) since the beginning of 2000. The RMMI provides a trending measure of home equity among U.S. homeowners age 62 and older.

The RMMI defines senior home equity as the difference between the aggregate value of homes owned and occupied by seniors and the aggregate mortgage balance secured by those homes. This measure enables NRMLA to help gauge the potential market size of those who may be qualified for a reverse mortgage product. The chart above illustrates the steady increase in this index since the end of the 2008 recession.

Increasing house prices drive the index’s upward trend, mitigated to some extent by a corresponding modest increase in mortgage debt held by seniors. The most recent RMMI report (reflecting data as of the end of Q3 20202) was published last week on NRMLA’s website.

Note on the Limitations of RMMI

To calculate the RMMI, an econometric tool is developed to estimate senior housing value, senior mortgage level, and senior equity using data gathered from various public resources such as American Community Survey (ACS), Federal Reserve Flow of Funds (Z.1), and FHFA housing price indexes (HPI). The RMMI is simply the senior equity level at time of measure relative to that of the base quarter in 2000.[1] The main limitation of RMMI is non-consecutive data, such as census population. We use a smoothing approach to estimate data in between the observable periods and continue to look for ways to improve our methodology and find more robust data to improve the precision of the results. Until then, the RMMI and its relative metrics (values, mortgages, home equities) are best analyzed at a trending macro level, rather than at more granular levels, such as MSA.

[1] There was a change in RMMI methodology in Q3 2015 mainly to calibrate senior homeowner population and senior housing values observed in 2013 American Community Survey (ACS).

Cash-out Refis, Investment Properties Contribute to Uptick in Agency Mortgage Risk Profile

RiskSpan’s Vintage Quality Index is a monthly measure of the relative risk profile of Agency mortgages. Higher VQI levels are associated with mortgage vintages containing higher-than-average percentages of loans with one or more “risk layers.”

These risk layers, summarized below, reflect the percentage of loans with low FICO scores (below 660), high loan-to-value ratios (above 80%), high debt-to-income ratios (above 45%), adjustable rate features, subordinate financing, cash-out refis, investment properties, multi-unit properties, and loans with only one borrower.

The RiskSpan VQI rose 4.2 points at the end of 2020, reflecting a modest increase in the risk profile of loans originated during the fourth quarter relative to the early stages of the pandemic.

The first rise in the index since February was driven by modest increases across several risk layers. These included cash-out refinances (up 2.5% to a 20.2% share in December), single borrower loans (up 1.8% to 52.0%) and investor loans (up 1.4% to 6.0%). Still, the December VQI sits more than 13 points below its local high in February 2020, and more than 28 points below a peak seen in January 2019.

While the share of cash-out refinances has risen some from these highs, the risk layers that have driven most of the downward trend in the overall VQI – percentage of loans with low FICO scores and high LTV and DTI ratios – remain relatively low. These layers have been trending downward for a number of years now, reflecting a tighter credit box, and the pandemic has only exacerbated tightening.

VQI Q4 2020 Risk Layers Historical Trend–2

VQI Q4 2020 Loans w Subordinate Financing

VQI Q4 2020 Cash Refinance-Share of Issued Loans

VQI Q4 2020 Loan Occupancy – Investment – Share of Issued Loans

VQI Q4 2020 Multi-Unit – Share of Issued Loans

VQI Q4 2020 One Borrower Loans – Share of Issued Loans

Population assumptions:

Monthly data for Fannie Mae and Freddie
Loans originated more than three months prior to issuance are excluded because the index is meant to reflect current market
Loans likely to have been originated through the HARP program, as identified by LTV, MI coverage percentage, and loan purpose, are also These loans do not represent credit availability in the market as they likely would not have been originated today but for the existence of HARP.

Data assumptions:

Freddie Mac data goes back to 12/2005. Fannie Mae only back to 12/2014.
Certain fields for Freddie Mac data were missing prior to 6/2008.
GSE historical loan performance data release in support of GSE Risk Transfer activities was used to help back-fill data where it was missing.

This analysis is developed using RiskSpan’s Edge Platform. To learn more or see a free, no-obligation demo of Edge’s unique data and modeling capabilities, please contact us.

EDGE: GNMA Forbearance End Date Distribution

With 2021 underway and the first wave of pandemic-related FHA forbearances set to begin hitting their 12-month caps as early as March, now seems like a good time to summarize where things stand. Forbearance in mortgages backing GNMA securities continues to significantly outpace forbearance in GSE-backed loans, with 7.6% of GNMA loans in forbearance compared to 3.5% for Fannie and Freddie borrowers.[1] Both statistics have slowly declined over the past few months.

Notably, the share of forbearance varies greatly amongst GNMA cohorts, with some cohorts having more than 15% of their loans in forbearance. In the table below, we show the percentage of loans in forbearance for significant cohorts of GN2 30yr Multi-lender pools.

Percent of Loans in Forbearance for GNMA2 30yr Multi-lender Pools:

Cohorts larger than $25 billion. Forbearance as of December 2020 factor date.

Not surprisingly, newer production tends to experience much lower levels of forbearance. Those cohorts are dominated by newly refinanced loans and are comprised mostly of borrowers that have not struggled to make mortgage payments. Conversely, 2017-2019 vintage 3s through 4.5s show much higher forbearance, most likely due to survivor bias – loans in forbearance tend not to refinance and are left behind in the pool. The survivor bias also becomes apparent when you move up the coupon stack within a vintage. Higher coupons tend to see more refinancing activity, and that activity leaves behind a higher proportion of borrowers who cannot refinance due to the very same economic hardships that are requiring their loans to be in forbearance.

GNMA also reports the forbearance end date and length of the forbearance period for each loan. The table below summarizes the distribution of forbearance end dates across all GNMA production. This date is the last month of the currently requested forbearance period.[2]

GNMA Loans in Forbearance–January 5 2020

For loans with forbearance ending in December 2020 (last month), half have taken a total of 9 months of forbearance, with most of the remaining loans taking either three or six months of forbearance.

Total Months of Forbearance Taken–January 5 2020

For loans whose forbearance period rolls in January and February 2021, the total months of forbearance is evenly distributed between 3, 6, and 9 months. Among loans with a forbearance end date of March 2021, more than half will have taken their maximum twelve months of forbearance.[3]

In the chart below, we illustrate how things would look if every Ginnie Mae loan currently in forbearance extended to its full twelve-month maximum. As this analysis shows, a plurality of these mortgages – more than 25 percent — would have a forbearance end date of March 2021, with the remaining forbearance periods expiring later in 2021.

A successful vaccination program is expected to stabilize the economy and (hopefully) end the need for wide-scale forbearance programs. The timing of this economic normalization is unclear, however, and the distribution of current end dates, as illustrated above, suggests that the existing forbearance period may need to be extended for some borrowers in order to forestall a potentially catastrophic credit-driven prepayment spike in GNMA securities.

Contact us if you interested in seeing variations on this theme. Using Edge, we can examine any loan characteristic and generate a S-curve, aging curve, or time series.

[1] As of the December 2020 factor date, using the data reported by the GSEs and GNMA. This data may differ marginally from the Mortgage Bankers Association survey, which is a weekly survey of mortgage servicers.

[2] Data as of the December 2020 factor date.

[3] Charts of January, February and March 2021 rolls are omitted for brevity. See RiskSpan for a copy of these charts.

EDGE: COVID Forbearance and Non-Bank Buyouts

November saw a significant jump in GNMA buyouts for loans serviced by Lakeview. Initially, we suspected that Lakeview was catching up from nearly zero buyout activity in the prior months, and that perhaps the servicer was doing this to keep in front of GNMA’s requirement to keep seriously delinquent loans below the5% of UPB threshold. [1]

Buyout rates for some major non-bank servicers.

Using EDGE to dig further, we noticed that Lakeview’s buyouts affected both multi-lender and custom pools in similar proportions and were evenly split between loans with an active COVID forbearance and loans that were “naturally” delinquent.

The month-on-month jump in Lakeview buyouts on forborne loans is notable. The graph below plots Lakeview’s buyout rate (CBR) for loans that are 90-days+ delinquent.

EDGE — COVID Forbearance Lakeview Buyout Rate–Updated

Further, the buyouts were skewed towards premium coupons. Given this, it is plausible that the buyouts are economically driven [2] and that Lakeview is now starting to repurchase and warehouse delinquent loans, something that non-banks have struggled with due to balance sheet and funding constraints.

EDGE–COVID Forbearance Lakeview Buyout Rates by Coupon–Updated

Where do the current exposures lie? The table below summarizes Lakeview’s 60-day+ delinquencies for loans in GN2 multi-lender pools, for coupons and vintages where Lakeview services a significant portion of the cohort. Not surprisingly, the greatest exposure lies in recent-vintage 4s through 5s.

To lend some perspective, in June 2020 Wells serviced around one-third of 2012-13 vintage 3.5s and approximately 8% of its loans were 60-days delinquent, all non-COVID related.

This analysis does not include other non-bank servicers. As a group, non-bank servicers now service more than 80% of recent-vintage GN2 loans in multi-lender pools. The Lakeview example reflects mounting evidence that COVID forbearance is not an impediment to repurchasing delinquent loans.

If you interested in seeing variations on this theme, contact us. Using Edge, we can examine any loan characteristic and generate a S-curve, aging curve, or time series.

[1] Large servicers are required to keep 90-day+ delinquencies below 5% of their overall UPB. GNMA has exempted loans that are in COVID forbearance from this tally.

[2] Servicers can repurchase GNMA loans that have missed 3 or more payments at par. If these loans cure, either naturally or due to modification, the servicer can deliver them into a new security. Given that nearly all GNMA passthroughs trade at a significant premium to par, this redelivery can create a substantial arbitrage opportunity, even after accounting for the trial period for the modification.

Chart of the Month: Fed Impact on Credit ETF Performance

On March 23^rd, The Fed announced that its Secondary Market Corporate Credit Facility (SMCCF) would begin purchasing investment-grade corporate bonds in the secondary market, first through ETFs and directly in a later phase.

In June, we charted the impact of this announcement on the credit spreads of various corporate bonds. This month we are charting its impact on ETF performance.

This month’s chart plots the price of ETFs relative to their price as of March 23rd 2020 (i.e., all ETF prices are set to 1.00 as of that date). Data runs from Feb 24th to Nov 16th 2020.

23rd March 2020 –Nov Chart of the Month 2020–Final

EDGE: Unexplained Prepayments on HFAs — An Update

In early October, we highlighted a large buyout event for FNMA pools serviced by Idaho HFA, the largest servicer of HFA loans. On October 28, FNMA officially announced that there were 544 base-pools with erroneous prepayments due to servicer reporting error. The announcement doesn’t mention the servicer of the affected pools, but when we look at pools that are single-servicer, every one of those pools is serviced by Idaho HFA.

FNMA reports the “September 2020 Impacted Principal Paydown” at $133MM. The September reported prepayment for FNMA Idaho HFA pools was 43 CPR on a total of just over $6B UPB. If we add back the principal from the impacted paydown, the speed should have been 26 CPR, which is closer to the Freddie-reported 25 CPR.

FNMA provides an announcement here and list of pools here. According to the announcement, FNMA will not be reversing the buyout but instead recommends that affected investors start a claims process. We note that Idaho HFA prepayment speeds will continue to show these erroneous buyouts in the October factor date.

Contact us to try Edge for free.

RiskSpan VQI: Current Underwriting Standards Q3 2020

RiskSpan’s Vintage Quality Index, which had declined sharply in the first half of the year, leveled off somewhat in the third quarter, falling just 2.8 points between June and September, in contrast to its 12 point drop in Q2.

This change, which reflects a relative slowdown in the tightening of underwriting standards reflects something of a return to stability in the Agency origination market.

Driven by a drop in cash-out refinances (down 2.3% in the quarter), the VQI’s gradual decline left the standard credit-related risk attributes (FICO, LTV, and DTI) largely unchanged.

The share of High-LTV loans (loans with loan-to-value ratios over 80%) which fell 1.3% in Q3, has fallen dramatically over the last year–1.7% in total. More than half of this drop (6.1%) occurred before the start of the COVID-19 crisis. This suggests that, even though the Q3 VQI reflects tightening underwriting standards, the stability of the credit-related components, coupled with huge volumes from the GSEs, reflects a measure of stability in credit availability.

Risk Layers – September 20 – All Issued Loans By Count

Loan to Value > 80 - Share of Issued Loans

Debt-to-Income > 45 - Share of Issued Loans

Risk Layers – September 20 – All Issued Loans By Count

Analytical And Data Assumptions

Population assumptions:

Monthly data for Fannie Mae and Freddie Mac.

Loans originated more than three months prior to issuance are excluded because the index is meant to reflect current market conditions.

Loans likely to have been originated through the HARP program, as identified by LTV, MI coverage percentage, and loan purpose are also excluded. These loans do not represent credit availability in the market as they likely would not have been originated today but for the existence of HARP.

Data assumptions:

Freddie Mac data goes back to 12/2005. Fannie Mae only back to 12/2014.

Certain fields for Freddie Mac data were missing prior to 6/2008.

GSE historical loan performance data release in support of GSE Risk Transfer activities was used to help back-fill data where it was missing.

An outline of our approach to data imputation can be found in our VQI Blog Post from October 28, 2015.

LIBOR Transition: Winning the Fourth Quarter

In July 2017, the United Kingdom’s Financial Conduct Authority (FCA) announced that financial institutions will no longer be required to publish LIBOR rates after December 2021, signaling the effective end of LIBOR. Given that the FCA provided a four-year transition period for market participants to identify and implement alternative reference rates, market participants are rapidly approaching the “fourth quarter” of the transition away from LIBOR.

Winning in the fourth quarter is more difficult when you finish the third quarter down by 28 points. And so, it is critical that institutions assess their progress to date in preparing for the cessation of LIBOR and making plans to implement an alternative reference rate. At this stage of an institution’s transition plan, a number of milestones need to be completed in order for an institution to reasonably consider itself “on-track.”

These include having the workstreams listed below and a detailed plan in place to complete the execution of these tasks over the next year:

LIBOR Transition Project Team Established – Financial institutions should have established a dedicated project team responsible for managing the transition from LIBOR. For larger institutions with LIBOR exposure in multiple business units, business unit leaders should be identified and made responsible for LIBOR transition activities in their business unit.
Identification of LIBOR Exposure – Legacy contracts should already have been evaluated and exposure to LIBOR products maturing beyond year-end 2021 should have been quantified. During the upcoming year, monthly and quarterly updates on LIBOR exposure should be communicated to management.
Assessment of LIBOR Contracts – Contracts should be reviewed to determine whether clear fallback language has been incorporated. Contracts with a) clear fallback language, b) fallback language requiring legal interpretation, and c) no fallback language must be identified and inventoried.

Remediate Contracts without Clear Fallback Language – For contracts without adequate fallback language, institutions need to identify and finalize options for alternative reference rates, remediation plans, and a communication strategy with stakeholders when LIBOR is terminated.
Assess Financial Exposure to Alternative Reference Rates – Because institutions will likely be impacted by exposure to alternative reference rates beginning in January 2022, plans need to be in the works for performing analyses on how the new alternative reference rate is likely to impact income, funding, liquidity, and capital levels.
Stop Use of LIBOR on New Products – It may not need to be said, but one of the most effective methods of mitigating LIBOR exposure is to stop creating new LIBOR products. To the extent new LIBOR products need to be issued, institutions must ensure that clear, easy-to-follow fallback language has been incorporated.
Update and Remediate Technology – LIBOR is likely embedded in many applications and systems that set pricing on products, determine contractual payments, and determine the fair value for instruments. Plans need to be developed and implemented to update and test technology applications with LIBOR exposure.

Consider engaging with external data and technology vendors to ensure operational readiness to transition away from LIBOR. Each business line and core function such as Finance or Treasury needs to inventory technology, operations, and modeling tools to ensure every LIBOR touch point is properly accounted for.

Validate Models With LIBOR Assumptions – As we discussed last month, many models rely on LIBOR as an assumption or as part of the cash flow discounting mechanism. Validators of models transitioning from LIBOR to an alternative reference rate need to account for this. And unscheduled validations may become necessary for models that might not otherwise be up for review before the end of 2021.

The cessation of LIBOR is a significant event impacting a broad set of financial products and market segments. Because it is intertwined in the products, technology, and models of a financial institution, LIBOR transition must be sufficiently planned, resources must be mobilized, and alternative reference rates must be implemented into every business and process.

The “fourth quarter” of the LIBOR transition game is upon us and the stakes are too high to rely on the second string. Financial institutions cannot underestimate the operational, technical, legal, communication, and risk management work required to move existing transactions off LIBOR and prepare for alternative reference rates. Although these efforts to transition from LIBOR should already be in full swing, they will continue to require additional time and resources. Teams that seem to be in control of the game still need to finish strong.

Financial institutions that have not begun a comprehensive LIBOR transition plan are running out of time and will need to mount a furious fourth-quarter comeback. It’s not too late, but with the last year of the LIBOR transition dawning, financial institutions that are behind in their planning need to hustle. No one can afford to lose this game. The costs of failing to prepare are simply too high.

EDGE: Unexplained Behavior for Idaho HFA

People familiar with specified pool trading recognize pools serviced by the state housing finance authorities as an expanding sector with a rich set of behavior. The Idaho Housing Finance Authority leads all HFAs in servicing volume, with roughly $18B in Fannie, Freddie and Ginnie loans.[1]

In the October prepay report, an outsized acceleration in speeds on FNMA pools serviced by the Idaho HFA caught our attention because no similar acceleration was occurring in FHLMC or GNMA pools.

FactorDate vs CPR — *Speeds on Idaho HFA-serviced pools for GNMA (orange), FHLMC (blue), and FNMA (black)*

Digging deeper, we analyzed a set of FNMA pools totaling around $3.5B current face that were serviced entirely by the Idaho HFA. These pools experienced a sharp dip in reported forbearance from factor dates August through October, dropping from nearly 6% in forbearance to zero before rebounding to 4.5% (black line). By comparison, FHLMC pools serviced by the Idaho HFA (blue line) show no such change.

Seeking to understand what was driving this mysterious dip/rebound, we noticed in the October report that 2.7% of the Fannie UPB serviced by the Idaho HFA was repurchased (involuntarily) on account of being 120 days delinquent, thus triggering a large involuntary prepayment which was borne by investors.

We suspect that in the September report, loans that were in COVID-forbearance were inadvertently reclassified as not in forbearance. In turn, this clerical error released these loans from the GSE’s moratorium on repurchasing forbearance-delinquent loans and triggered an automatic buyout of these 120+ day delinquent loans by FNMA.

We have asked FNMA for clarification on the matter and they have responded that they are looking into it. We will share information as soon as we are aware of it.

[1] Idaho HFA services other states’ housing finance authority loans, including Washington state and several others.

If you are interested in seeing variations on this theme, contact us. Using Edge, we can examine any loan characteristic and generate a S-curve, aging curve, or time series.

EDGE: An Update on Property Inspection Waivers

In June, we wrote about the significant prepay differences observed between loans with full inspection/appraisals and loans with property inspection waivers (PIW). In this short piece, we revisit these relationships to see if the speed differentials have persisted over the previous four months.

From an origination standpoint, PIWs continue to gain in popularity and are beginning to approach half of all new issuance (blue line). For refi loans this figure approaches 60% (green line).

Graph 1: Percent of loans with property inspection waivers, by balance. Source: RiskSpan Edge

Performance

Broadly speaking, PIW loans still pay significantly faster than loans with appraisals. In our June report, the differential was around 15 CPR for the wider cohort of borrowers. Since that time, the relationship has held steady. Loans with inspection waivers go up the S-curve faster than loans with appraisals, and top out around 13-18 CPR faster, depending on how deep in the money the borrower is.

Graph 2: S-curves for loans aged 6-48 months with balance >225k, waivers (black) vs inspection (blue). Source: RiskSpan Edge.

The differential is smaller for purchase loans. The first chart, which reflects only purchase loans, shows PIW loans paying only 10-12 CPR faster than loans with full appraisals. In contrast, refi loans (second chart) continue to show a larger differential, ranging from 15 to 20 CPR, depending on how deep in the money the loan is.

Graph 3: Purchase loans with waivers (black) versus inspections (blue). Source: RiskSpan Edge.

Graph 4: Refi loans with waivers (black) versus inspections (blue). Source: RiskSpan Edge.

We also compared bank-serviced loans with non-bank serviced loans. The PIW speed difference was comparable between the two groups of servicers, although non-bank speeds were in general faster for both appraisal and PIW loans.

Inspection waivers have been around since 2017 but have only gained popularity in the last year. While investors disagree on what is driving the speed differential, it could be as simple as self-selection: a borrower who qualifies for an inspection waiver will also qualify upon refinancing, unless that borrower takes out a large cash-out refi which pushes the LTV above 70%[1]. In any event, the speed differential between loans with waivers and loans with full inspections continues to hold over the last four months of factor updates. Given this, appraisal loans still offer significantly better prepay profiles at all refi incentives, along with a slightly flatter S-curve, implying lower option cost, than loans with inspection waivers.