How deeply to evaluate Limited Partners while rating subscription finance exposures
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Hi RB, Hope you’re doing well
We've recently built a model for subscription finance (bridge loans to PE funds while they wait for LPs to honor capital calls). Our model involves a deep rating of each LP, which made the rating process quite time-consuming - especially painful since the portfolio has never seen any defaults for them
We're aware of other models take a higher-level approach with LPs, using info like LP type, number of LPs, and contract covenants—without needing to rate each LP individually. These models also factor in GP aspects like financial strength and track record.
Whilst intriguing, were concerned about whether such a model (not rating individual LPs) would satisfy regulatory requirements. I’d love to tap into the collective wisdom of this esteemed group to get your tack - any thoughts or experiences you can share?
Thanks so much!
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This product has come up a few times at our bank, and we've utilized bottom-up information about each of the LPs to assign them into risk buckets in line with the PD masterscale, but generally in a manner that could be derived from structured data (e.g. a waterfall considering external rating where available, then AUM and one or two other factors), rather than requiring a laborious rating assessment for each LP.
Then the final rating assignment considered information on the deal structure, GP attributes and the pool of LP ratings. As I recall, there was some nuance of relating the pool of LP ratings to the deal structure in that final logic – e.g., if according to the deal terms, only a subset of (stronger) LPs would be counted as eligible for inclusion in calculating allowable advances, then having some lower-rated LPs who were not included in the eligible pool wouldn’t necessarily tank the deal rating. And if the deal had a lower advance rate, that could also offset having a few lower-quality LPs in the eligible pool to some degree.
There was a lot of judgement involved in structuring this model and its parameters, and zero actual defaults to work with, but it did allow the assessments to then be done in a structured bottom-up fashion. We also sought an external support to test and improve the documentation, and testing the impact of different rating proxying assumptions
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We are in the process of building a PD model for our Capital Call Lines of Credit (CCLOC) portfolio, and we are taking an expert judgement approach where we account for both fund and LP factors such as:
- Fund factors
- Firm quality
- NAV/Cost
- Fund Siz
- LP Factors
- Investing method
- Type of commitments
- Credit ratings
It is a pretty qualitative approach and there are no defaults to work with, but it at least allows for risk differentiation amongst the portfolio and can be back-tested historically and then a qualitative assessment of whether the backtesting is appropriate can be done
- Fund factors
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I think most use a blended approach, with the largest / riskiest LPs getting a deeper review and others being rated based on higher level characteristics. LPs who are too risky and/or cant be rated should get kicked out of the borrowing base. NB: I don’t think LP risk is the only criteria, and similar to a reply above, Fund and GP factors are also really important (if not more so). Given the lack of historical defaults, it’s important to have a good conceptual understanding of what could drive defaults… which varies based on the type of LP, the legal frameworks for the LP’s commitments, and the likelihood of things going sideways for the fund/GP.
Worth skimming the characteristics the ratings agencies use to assess sub lines for some additional color. (portfolios of sub lines get rated both for distribution to US Life Insurers, who rely on IG ratings, and for other distribution mechanisms). Summarized nicely by KBRA below
Subscription Lines: Why Are Ratings Needed?
https://www.kbra.com/publications/KKbkyMsj/subscription-lines-why-are-ratings-needed?format=fileSubscription Finance Rating Criteria [Fitch]
https://www.fitchratings.com/research/fund-asset-managers/subscription-finance-rating-criteria-08-06-2023Methodology For Rating Subscription Lines Secured By Capital Commitments [S&P]
https://disclosure.spglobal.com/ratings/en/regulatory/article/-/view/sourceId/13199000Subscription Credit Facilities: Proposed methodology [Moodys]
https://ratings.moodys.com/api/rmc-documents/410678