Many capital allocators have embraced the thesis that financial services will continue to modernize through technology and innovation. They understand the unparalleled transparency offered by digital private credit and are keen to add exposure to their private debt portfolio.
A digital private credit portfolio owned via an open-ended evergreen investment program must value its underlying whole loans in order to produce a NAV, or price, at the end of a reporting period.
The intelligent investor asks: How does a manager or valuation consultant determine the fair value of those Level 3 assets (GAAP speak) at the end of a reporting period?
Investment managers typically formulate and adhere to a valuation policy that described how fair value should be measured. Key valuation inputs typically fit into 3 buckets: known, asset-specific estimates, and market-based estimates. Let’s go through each.
Known: Underlying loans in the strategy have a known present value – typically the loan amount’s opening principal balance (e.g., $10,000), and a known future value: zero! Most loans have stated contractual terms (e.g., 12 months, 36 months, 60 months), contractual repayment rates (e.g., 5% per month) or amortization rates (e.g., installment, like a mortgage), and contractual coupons – fixed or variable (e.g., 12% or base rate + spread). The combination of all these known inputs result in a series of expected cash flows over the underlying loan life.
Asset-specific estimates: The two critical variables in this bucket are loss and prepayment estimates which are informed by large amounts of historical data (when available), and therefore tend to be fairly reliable. These estimates impact the contractual cash flows produced by the known inputs. Not surprisingly, losses reduce expected contractual cash flows, and perhaps counterintuitively, prepayments also reduce expected contractual cash flows. Losses typically have more weight than prepayments.
Market-based estimates: The main input is the expected rate of return that should be used to discount the expected cash flows mentioned above. In effect, it is the discount rate.
With these inputs, a reasonable fair value can be calculated.
The intelligent investor may follow up with: Why do fair values of digital private credit portfolios differ across managers?
In our experience, fair values of digital private credit investment programs can differ for a variety of reasons, including, but not limited to, the following:
Different underlying asset profile: Known inputs and estimates differ by asset profile. For example, a 60-month consumer personal installment loan has different characteristics than a 12-month consumer point of sale loan. Similarly, a 12-month consumer loan will behave differently than a 12-month small business loan due to inherent differences in the asset and borrower profile.
Varying quality due to origination source: Even if two loans look exactly the same, they might have a wide gap in performance due to their origination source. Originators vary meaningfully from one another in terms of the quality of the assets they generate for investors. Careful selection of origination sources is a key differentiator among digital private credit portfolios.
Different purchase prices and forward returns: A known input such as purchase price may vary. For example, a loan purchased at par will not be worth the same as a loan purchased at 5% discount or another purchased at a 5% premium. Purchasing a discounted secondary portfolio can offer meaningful tailwind and lead to higher forward return.
Different predictive analytics: Asset-specific estimates offer good starting points, but they can be enhanced by incorporating analytics to improve predictive accuracy. These tend to be proprietary to each manager.
Structural protections: Including these can reduce the impact of loss on expected contractual cash flows. For example, first loss protection and credit enhancement are used often to mitigate credit losses.
Active portfolio construction and management: A powerful mitigant to market-based pricing, active portfolio management can introduce meaningful tailwind in an environment that is repricing rapidly. For example, low duration / weighted average life portfolios will fare better given an ability to reinvest cash flow quickly into new assets issued at higher rates. Furthermore, portfolio managers can choose to allocate to assets that are repricing more favorably and away from those that don’t.
Portfolio construction and management decisions along the above impact and drive fair value. Ultimately, it is the responsibility of the manager to educate the prospective intelligent investor about the nuances of their strategy so that an informed allocation decision can be made.