What is the underwriting quality of Pagaya’s AI loans?

Following its merger with a special purpose acquisition company (SPAC), the artificial intelligence lending platform Pagaya Technologies (PGY -10.18%) saw its share explode higher thanks to an extremely reduced public float. But a key underlying driver of Pagaya’s actual business fundamentals is the company’s ability to leverage its proprietary AI technology to underwrite loans to its banking and fintech partners and investors on its platform.

That said, let’s take a look at how effective the company’s loan underwriting has been so far.

Cumulative net loss rate

Pagaya partners with banks and other fintech companies who send loan applications to the platform to underwrite with its artificial intelligence technology, which has more than 16 million data formation points since its inception . The company then takes these loans for its partners and sells them to investors or securitizes the loans and sells notes to investors.

For securitized loans, investors can gain insight into credit quality performance by viewing reports from the Kroll Bond Rating Agency (KBRA), which continuously rates various asset-backed securities. There are many considerations that go into assessing credit quality, but the easiest way to assess different vintages is to look at how actual cumulative net loss (CNL) rates are performing against market expectations. KBRA at some point.

You can also see how the KBRA base case CNL rate for the life of securitization trends as securitization seasons. In this chart, I will only assess asset-backed securities that have been seasoned for at least six months.

Ancient seasoned month current CNL KBRA Expected CNL KBRA base case initial loss expectation KBRA Base Case Current Loss Forecast
2020-3 20 6.93% 12.75% 16.50% 12.75%
2021-1 15 7.84% 5.62% 14.35% 14.35%
2021-HG1 13 1.48% 0.99% 7.25% 7.25%
2021-3 9 3.95% 2.16% 15.20% 15.20%
2021-5 6 0.79% 0.01% 15.20% 15.20%

Data source: KBRA reports.

It is really important to focus less on the current CNL rate and more on how it compares to KBRA expectations. For example, while the 2020-3 vintage has a seemingly high CNL rate of 6.93%, it significantly exceeds the KBRA’s expectations over 20 seasoned months, when it expected the CNL rate i.e. 12.75%. In addition, KBRA lowered its 2020-3 lifetime expected loss base case scenario by 16.5%, when Pagaya issued the first securitization at 12.75%.

On the other hand, current CNL rates for all 2021 vintages are currently trending worse than KBRA had expected at this stage in their life, which ranges from six months seasoned to 15 months. But the KBRA has still not adjusted its loss forecast for the life of these securities.

I haven’t seen a ton of information in recent reports regarding the composition of loans in each securitization, but KBRA noted that it has raised its loss expectations for loan grades D and E, which are made to borrowers lower on the credit spectrum. The KBRA noted that this could be due to “the expiration of government stimulus measures offered throughout the COVID-19 pandemic, inflationary pressures on consumer prices and other macroeconomic factors.”

The KBRA added that new vintages issued by Pagaya in 2022 that are not yet seasoned were permitted to include higher levels of D and E grade loans. The KBRA also increased its base CNL loss assumption for the Pagaya’s most recent 2022 vintage at around 16% in the middle of its range, around 3% higher than the previous 2022 vintage.

So how’s the underwriting?

The bad news for Pagaya is that the current CNL rates for many of its 2021 vintages are worse than what the KBRA expected them to be at their various points of maturity. The good news is that the KBRA has yet to change its overall loss expectations over the lifetime of vintages, which means it expects loss trends to eventually return in line. to assumptions.

However, I don’t think it’s a good sign to see CNL rates worse than expected by the KBRA, given that there were still many government stimulus programs in effect in 2021. These programs have largely run their course. and economic conditions deteriorate. Loss assumptions have already increased on recent vintages, and these appear to have more borrowers lower on the credit spectrum, who are showing more cracks at this time.

From what is happening, I would expect CNL rates to get worse, not better. I have yet to be convinced that AI underwriting can materially outperform traditional underwriting in tougher economic conditions, which is why I think Pagaya, along with other fintechs in the industry, need to prove their concept more.

Bram Berkowitz has no position in any of the stocks mentioned. The Motley Fool has no position in the stocks mentioned. The Motley Fool has a disclosure policy.

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