With significant home price gains over the last two years, U.S. homeowners are sitting on vast, mostly untapped wealth. Nationally, home prices are up an aggregate of 28% over the last two years, with some regions performing even better. But unlike other periods of strong home price gains, cash-out refinancings lagged overall refinancings during the pandemic rate-rally. In this short article, we look at cash-out refinancings over time, and their potential impact on prepayments, especially on discount cohorts.

A historical perspective

In the early 2000s, mortgage rates fell nearly 200bp, triggering a massive refinancing wave as well as a rally in home prices that lasted well into 2005.

During this early millennium rally, the market saw significant cash-out refi activity with homeowners borrowing at then-historically low rates to free up cash. The market even saw refinancing activity in mortgages with note rates below the prevailing market rate. In 2002, CPRs on some discount cohorts hit the low to middle teens, which many participants attributed to cash-out refinancing. Resetting a mortgage 50 basis points higher can nevertheless often lead to overall lower debt servicing when borrowers use cash-out refis to consolidate auto loans, credit cards and other higher-rate unsecured borrowings.[1] In the early 2000s, this cash-out refinancing activity led to overall faster speeds and a higher S-curve for out-of-the-money cohorts. How does 2002-03 cash-out refi activity compare to today? In the early 2000s, issuance of cash-out mortgages, as a percentage of the total market, varied between 1% and 2.5% of the outstanding mortgage universe each month.

In June, we highlighted Fannie Mae’s and Freddie Mac’s new “expanded delinquency” states. The Enterprises are now reporting delinquency states from 1 to 24 months to better account for loans that are seriously delinquent and not repurchased under the extended timeframe for repurchase of delinquent loans announced in 2020.

This new data reveals a strong correlation between loan balance and “chronically delinquent” loans. In the graph below, we chart loan balance on the x-axis and 180+Day delinquency on the y-axis, for 2017-18 production 30yr 3.5s through 4.5 “generic” borrowers.[1]

As the graph shows, within a given coupon, loans with larger original balances also tended to have higher “chronic delinquencies.”

The graph above also illustrates a clear correlation between higher chronic delinquencies and higher coupons. This phenomenon is most likely due to SATO. While each of these queries excluded low-FICO, high-LTV, and NY loans, the 2017-18 30yr 3.5 cohort was mostly at-the-money origination, whereas 4.0s and 4.5s had an average SATO of 30bp and 67bp respectively. The higher SATO indicates a residual credit quality issue. As one would expect, and we demonstrated in our June analysis, lower-credit-quality loans tend also to have higher chronic delinquencies.

The first effect – higher chronic delinquencies among larger loans within a coupon – is more challenging to understand. We posit that this effect is likely due to survivor bias. The large refi wave over the last 18 months has factored-down higher-balance cohorts significantly more than lower-balance cohorts.

Higher-credit-quality borrowers tend to refinance more readily than lower-credit-quality borrowers, and because the larger-loan-balance cohorts have seen higher total prepayments, these same cohorts are left with a larger residue of lower-quality credits. The impact of natural credit migration (which is observed in all cohorts) tends to leave behind a larger proportion of credit-impaired borrowers in faster-paying cohorts versus the slower-paying, lower-loan-balance cohorts.

The higher chronic delinquencies in larger-loan-balance cohorts may ultimately lead to higher buyouts, depending on the resolution path taken. As loan balance decreases, the lower balance cohorts will have reduced risk to these potential buyouts, leaving them better protected to any uptick in involuntary speeds.

In June, the market got its first look at Fannie Mae and Freddie Mac “expanded delinquency” states. The Enterprises are now reporting delinquency states out to 24 months to better account for loans that are seriously delinquent and not repurchased under the extended timeframe for repurchase of delinquent loans announced in 2020. In this short post, we analyze those pipelines and what they could mean for buyouts in certain spec pool stories. 

First, we look at the extended pipeline for some recent non-spec cohorts. The table below summarizes some major 30yr cohorts and their months delinquent. We aggregate the delinquencies that are more than 6 months delinquent[1] for ease of exposition. 

Recent-vintage GSE loans with higher coupons show a higher level of “chronically delinquent” loans, similar to the trends we see in GNMA loans. 

In July, we examined buyouts of delinquent GNMA loans, with special focus on the buyout efficiency for bank servicers. At that time, several banks were 98% to 99% efficient at buying out delinquent loans, where “efficiency” is defined as the percentage of 90+ days delinquent loans that are repurchased. In this short note, we update the buyout efficiency of major bank and non-bank servicers. 

Buyout efficiency varies widely among banks. While the most efficient banks repurchase nearly 100% of eligible loans, others, including Flagstar and Citizens Bank, opt to leave virtually all the 90+ day delinquent loans they service in securities. In the table below, we show the dollar-weighted buyout efficiencies for top banks, as well as the UPB of each bank’s unpurchased 90+ day delinquent loans, as of the January 2021 factor date.

Buyout efficiency for 90+ day delinquent loans, data as of January 2021. 

Servicers listed by total UPB serviced.

The overhang of seriously delinquent loans serviced by Flagstar and Citizens is spread across several GN2 Multi-lender sectors, with concentrations of delinquent loans rising to just 1% of the total current face of 2018 4% and 2018 4.5% cohorts. If Flagstar and Citizens were to repurchase all of their delinquent loans in a single month, it would add roughly 11-12 CPR to these cohorts. This represents the upper limit in involuntary speed, and actual speeds would likely be much slower with repurchases spread over several months.

The markedly lower buyout efficiency among GNMA non-bank servicers has created involuntary prepay overhang that is potentially much more daunting. The following table summarizes top non-bank servicers, their buyout efficiency over the past two quarters, and their current overhang of 90+ day delinquent loans.

Buyout efficiency for 90+ day delinquent loans, data as of January 2021.

Servicers listed by total UPB serviced.

Both Penny Mac and Lakeview have improved their buyout efficiency over the last quarter and may continue to do so, as more investors begin to embrace the GNMA EBO trade. The multi-lender cohorts with the most exposure to 90+ day DQ loans serviced by Penny Mac or Lakeview include 2020 3.5s as well as 2017-19 production 3.5s and 4s, with each cohort ranging between 4% to 5% of its current face.

This final table, below, illustrates the impact of forbearance on buyout activity among non-banks. While forbearance status seems to pose no impediment to buyouts for banks — in fact, banks with the highest buyout efficiency seem to favor repurchasing loans that are in COVID-forbearance over loans that are “naturally” delinquent – non-bank behavior is more nuanced.

Of the top five non-bank servicers, only Lakeview has generated significant repurchases of loans in COVID forbearance, repurchasing 10% of eligible loans in Q4. In the table below, we separate the 90+ day delinquent loans by their forbearance status and then compute each servicer’s buyout efficiency across these sub-cohorts.

Buyout efficiency for 90+ day delinquent loans, data as of January 2021.

Lakeview’s buyout behavior suggests that forbearance is not an impediment to non-bank repurchases. If we see continued improvements in buyout efficiency over the next few months, involuntary speeds in GNMA securities have the potential to rise significantly.

Contact us if you are 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.

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.

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]

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.

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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.

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.