RMBS Archives

The way RMBS dealers communicate loan-level details to prospective investors today leaves a lot to be desired.

Any investor who has ever had to work with pre-issue Intex CDI files can attest to the problematic nature of the loan data they contain. Some are better than others, but virtually all of them lack information about any number of important loan features.

Investors can typically glean enough basic information about balances and average note rates from preliminary CDI files to run simple, static CPR/CDR scenarios. But information needed to run complex models — FICO scores, property characteristics and geography, and LTV ratios to name a few — is typically lacking. MBS investors who want to run to run more sophisticated prepayment and credit models – models that rely on more comprehensive loan-level datasets to run deeper analytics and scenarios – can be left holding the bag when these details are missing from the CDI file.

The loan-level detail exists – it’s just not in the CDI file. Loan-level detail often accompanies the CDI file in a separate spreadsheet (still quaintly referred to in the 21^st Century as a “loan tape”). Having this data separate from the CDI file requires investors to run the loan tape through their various credit and prepayment models and then manually feed those results back into the Intex CDI file to fully visualize the deal structure and expected cash flows.

This convoluted, multi-step workaround adds both time and the potential for error to the pre-trade analytics process.

A Better Way

Investors using RiskSpan’s Edge Platform can streamline the process of evaluating a deal’s structure alongside the expected performance of its underlying mortgage loans into a single step.

Here is how it works.

As illustrated above, when investors set up their analytical runs on Edge, RiskSpan’s proprietary credit and prepayment models automatically extract all the required loan-level data from the tape and then connect the modeling results to the appropriate corresponding deal tranche in the CDI file. This seamlessness reduces all the elements of the pre-trade analytics process down to a matter of just a few clicks.

Making all this possible is the Edge Platform’s Smart Mapper ETL solution, which allows it to read and process loan tapes in virtually any format. Using AI, the Platform recognizes every data element it needs to run the underlying analytics regardless of the order in which the data elements are arranged and irrespective of how (or even whether) column headers are used.

Contact us to learn more about how RMBS investors are reaping the benefits of consolidating all of their data analytics on a single cloud-native platform.

LEARN MORE

Now that six months have passed since Angel Oak issued AOMT 2021-2 – hailed as the first U.S. non-Agency RMBS to qualify as a social bond [1] – we can compare preliminary collateral performance to other deals. Angel Oak’s 2021-1, from the same shelf and vintage – but without the social bond distinction – provides an apt control group. To set the stage for this performance comparison, we’ll first reexamine the compositional differences – and significant overlap – between the two collateral pools. What we will show:

The pool compositions are highly overlapping, with marginally greater risk concentrations of self-employment and alternative documentation in the social securitization, and the same WA (weighted average) coupon
The social collateral has outperformed the benchmark credit-wise in the early going
The social deal has exhibited some lock-in, i.e., slower refinancing, providing some very preliminary evidence that the borrowers are indeed underserved, and that investors may be rewarded if the social collateral’s credit performance holds
However, the credit mix of the social collateral has drifted riskier – more so than the benchmark – meaning the strong early credit performance of the social deal could reverse, and ongoing surveillance is warranted

New Loans or New Label?

The Social AOMT 2021-2 Is Similar to AOMT 2021-1

Figure 1 shows AOMT 2021-1 vs. 2021-2 in the Collateral Comparison screen of Edge, RiskSpan’s data and analytics platform. Clearly, the two pools were similar at origination, with highly overlapping distributions of FICO, LTV, and DTI and many other similar metrics.

So What’s Different – And How Different Is It?

The distinguishing principle of a social bond under Angel Oak’s framework is that it provides affordable home mortgages to those who often can’t get them because they don’t qualify under the automated underwriting processes of traditional lenders because of the exceptional nature of their sources of income. [2]

Angel Oak says the specific characteristic hindering the borrowers in the AOMT 2021-2 deal is self-employment. [3] Self-employed borrowers make up 94.4% of the pool (with a median annual income of $227,803) [4], up marginally from 86.5% in the 2021-1 deal [5]. As Figure 1 shows, the proportion of low documentation by balance was up from 87.5% in 2021-1 to 97.5% in 2021-2.

Also, Figure 1 shows that 2021-2’s FICOs and LTVs are slightly worse on average with slightly more tail risk, and the cash-out proportion is slightly riskier.

Compensating marginally for 2021-2 are slightly lower ARM proportions (0 vs. 0.8% for 2021-1), lower WA. DTI, and a higher proportion of owner-occupied (90% vs. 85%), which many view as credit-positive.

In summary, RiskSpan calculates 1.83 average risk layers per loan for the social 2021-2, slightly higher than 1.78 for 2021-1.

Notably the WA coupons for the two pools are the same.

Figure 1: Edge’s Collateral Comparison Screen Showing AOMT 2021-1 (aka AOAK 2101) vs. 2021-2 (aka AOAK 2102) at Origination Graph Source: CoreLogic, RiskSpan

Would you like to see the tool we used to perform this analysis?

REQUEST A DEMO OR TRIAL

In summary, it seems that most – though perhaps not all – of the loans that qualified for AOMT 2021-2 would have qualified for AOMT 2021-1 and other non-QM deals.

Kroll’s new issue report seems to acknowledge that what is new about 2021-2 is mostly the formal emphasis on the social benefits of the loans made, and less a change in the kinds of loans made: “While many of [Angel Oak’s] lending programs overlap meaningfully with other non-QM lender’s offerings, the actions taken by AOCA generally indicate management’s attention to ESG related matters. Specifically, AOCA’s SBF puts focus on the impact that credit availability for underserved borrowers can have.” [4]

A skeptical interpretation of the overlap between 2021-1 and the social 2021-2 collateral would be that the social claim is largely hollow. Another way of looking at it is that a financial market participant is finally taking credit for good work it has been largely doing all along. Angel Oak itself seems to take this latter view, saying, “Since 2011, AOCA has been implementing ESG principles within its non-qualified mortgage (non-QM) origination and securitization program to provide access to residential credit for underserved borrowers.” [2]

Either way, logical hypotheses would be that collateral performance will be similar between 2021-2 and 2021-1, with -2 showing (a) slightly more credit trouble and (b) slightly less able to refinance. Regarding the second hypothesis, logically it should challenge the premise that the deal serves underserved borrowers if its borrowers can refinance just as readily as others.

Early Performance of the Social Bonds

Let’s see how AOMT’s social 2021-2 has performed as benchmarked to 2021-1 during the first six and seven months, respectively, of available data.

Better Delinquency Trend Than the Benchmark

As Figure 2 shows, delinquencies opened higher for the social 2021-2 but have mostly cured. By contrast, delinquencies have trended up for 2021-1. So far, Angel Oak’s social origination is outperforming its non-social contemporary from a credit standpoint.

Figure 2: AOMT 2021-2 Delinquencies Began Higher, Have Mostly Cured; AOMT 2021-1’s Delinquencies Have Trended Up 60 day-plus delinquency share over time, AOMT 2021-2 vs AOMT 2021-1 Source: CoreLogic, RiskSpan

Significantly Better Credit Performance by the Social DSCR Investor Loans

A small slice of the deals driving outsized delinquencies in 2021-1 are the DSCR-based investor loans (Figure 3). In the social 2021-2, delinquencies among this cohort are zero. We plot the spreads at origination (SATO) of this cohort alongside delinquencies to show that the DSCR loans in 2021-2 had lower credit spreads by about 20bps. Perhaps the investor loans pooled into 2021-2 were managed to higher standards for DSCR, rent rolls or other attributes (their LTVs and ages are similar).

Figure 3: Delinquencies – and SATOs – Are Lower Among DSCR-Based Investor Loans in AOMT 2021-2 60 day-plus delinquency share and WA SATOs over time, AOMT 2021-2 vs. AOMT 2021-1, includes Detailed Doc Type = DSCR Investor Cash Flow.Source: CoreLogic, RiskSpan

Ironically, The Full Doc Loans Are the Social Deal’s Blemish

The slice of full doc loans in the social 2021-2 have a much lower WA FICO than the low doc loans in the same deal or either the low or full doc loans in 2021-1 (see the green dotted line in Figure 4). Correspondingly, these full doc loans have the highest delinquent share among the four cohorts in Figure 4 (green solid line). If this pattern holds, it highlights the viability of using tradeoffs to manage down the overall credit risk represented by loans with risky attributes.

Figure 4: AOMT 2021-2’s Full Doc Loans Are the Most Delinquent Doc Cohort from Either Deal 60 day-plus delinquency share and WA FICOs over time, AOMT 2021-2 vs. AOMT 2021-1 and Full Doc vs. Low Doc Source: CoreLogic, RiskSpan

Slower Refinances Than the Benchmark

While credit performance has been better for the social deal than we might expect, voluntary prepays so far (Figure 5) support our hypothesis that the social deal should prepay slower. Note that we plot voluntary prepays over loan age, and that all loans from this recent non-QM vintage have similar (and highly positive) refinance incentive. If the social deal’s refinances remain slower, that accomplishes two significant things: 1) it supports the claim that the social borrowers are indeed underserved; 2) if combined with sustained credit performance, it provides support in terms of financial risk and return for the price premiums that social bonds tend to command.

Figure 5: AOMT 2021-2 Is Refinancing Slower CRR over loan age, AOMT 2021-2 vs. AOMT 2021-1, July 2021-January 2022 Source: CoreLogic, RiskSpan

The Relative Refinance Slowness Is From the Large Balance Loans

The overall slowness of the social collateral in Figure 5 is driven by large loans. Figure 6 shows that, among loans <$417K, the prepay patterns of 2021-1 and 2021-2 are similar, while among loans > $417K, the prepays of 2021-2 are consistently slower. This may suggest that large loans with complex sources of income are particularly hard to underwrite.

Figure 6: The Social Deal’s Low-Balance Loans Refi Similar to Benchmark, But Large Balances Have Been Slower CRR over loan age, AOMT 2021-2 vs. AOMT 2021-1, bucketed by loan size, July 2021-January 2022 Source: CoreLogic, RiskSpan

Updated Collateral Mix

The Social Deal’s Credit Mix Has Drifted Riskier, Warranting Ongoing Monitoring

While the early performance of the social collateral is positive, Figure 7 provides reason for concern and ongoing watchfulness. Since origination, the composition of the social 2021-2 has drifted riskier in all respects except slight improvements in WA DTI and WA LTV. Its LTV tails, WA FICO, and FICO tails; proportions of cash-out, low doc, non-owner-occupied; and average overall risk layers are all somewhat riskier.

The drift for 2021-1 has been more mixed. Like 2021-2, it is safer with respect to WA DTI and WA LTV. Unlike 2021-2, it is also safer with respect to LTV tails, FICO tails, and cash-out proportion. Like 2021-2, it is riskier with respect to WA FICO; proportions of low doc and non-owner-occupied; and average overall risk layers.

We will continue to monitor whether this composition drift drives differential performance going forward.

Figure 7: Edge’s Collateral Comparison Screen Showing AOMT 2021-1 (aka AOAK 2101) vs. 2021-2 (aka AOAK 2102) updated to the Current Factor DateSource: CoreLogic, RiskSpan

Using Edge, you can examine prepay or credit performance of loan subsets defined by any characteristics, and generate aging curves, time series, or S-curves.

REQUEST A DEMO OR TRIAL

[1] https://angeloakhomeloans.com/angel-oak-capital-advisors-delivers-first-to-market-non-agency-social-bond-securitization/

[2] https://www.issgovernance.com/file/spo/spo-20210408-angel-oak.pdf

[3] https://www.businesswire.com/news/home/20210517005728/en/Angel-Oak-Capital-Advisors-Delivers-First-to-Market-Non-Agency-Social-Bond-Securitization

[4] https://www.kbra.com/documents/report/48093/angel-oak-mortgage-trust-2021-2-aomt-2021-2-new-issue-report

[5] https://www.fitchratings.com/research/structured-finance/angel-oak-mortgage-trust-2021-1-us-rmbs-02-03-2021

Enriching Pre-Issue Intex CDI Files with [Actual, Good] Loan-Level Data

A Better Way

How Has the First “Social” RMBS Performed – And What’s So Social About It?

New Loans or New Label?

The Social AOMT 2021-2 Is Similar to AOMT 2021-1

So What’s Different – And How Different Is It?

Early Performance of the Social Bonds

Better Delinquency Trend Than the Benchmark

Significantly Better Credit Performance by the Social DSCR Investor Loans

Ironically, The Full Doc Loans Are the Social Deal’s Blemish

Slower Refinances Than the Benchmark

The Relative Refinance Slowness Is From the Large Balance Loans

Updated Collateral Mix

The Social Deal’s Credit Mix Has Drifted Riskier, Warranting Ongoing Monitoring

Company

Products

Security & Compliance