Distance to Bankability (DTB) is what we publish alongside the Tokenization Readiness Score. Where TRS ranks projects on a 0–100 scale across five dimensions, DTB asks a different question: how far above the financing cliff does this project sit, in standard deviations of expected NPV?
The framing
The corporate credit literature has a long tradition of distance-to-default — a Merton-style structural model where you measure the firm's enterprise value relative to its debt threshold, normalized by volatility. Moody's commercializes it. Lenders use it. It works because it gives you a single number that combines the level (how far above the cliff) and the noise (how volatile the path).
Project finance bankability is the same kind of question, just with different inputs. The relevant cliff is not "default" — it's "fails to reach a financeable state." The relevant value is not "enterprise value" — it's expected net present value of project cash flows. The volatility is not equity vol — it's the dispersion of NPV outcomes given remaining uncertainty across permit, interconnection, offtake, and construction milestones.
The formula
DTB is computed as:
DTB = (E[NPV] − financing threshold) / σ(NPV)
Where:
- E[NPV] is the probability-weighted expected NPV across our scenario set
- financing threshold is the NPV cutoff below which institutional capital would not commit (lender-side or equity-side, depending on framing)
- σ(NPV) is the standard deviation of NPV across our scenario set, capturing remaining uncertainty
A DTB of 2.6 means the project sits 2.6 standard deviations above the financing cliff. Roughly: only an event in the bottom ~0.5% of the outcome distribution would push it below the threshold. That's a high-confidence read, given current information.
Why this matters more than TRS alone
TRS is ordinal — it ranks. DTB is structural — it tells you the level relative to a meaningful cutoff. A project with a TRS of 75 and a DTB of 0.4 is in a different position than a project with TRS 75 and DTB 2.6. Same ordinal rank, different structural margin of safety. DTB exposes that.
It also forces honesty about uncertainty. TRS scores compress everything into a single number, which can hide the volatility inherent in a project that's still 18 months from energization. DTB makes the volatility explicit — projects with higher σ(NPV) get penalized in the score even if E[NPV] looks attractive.
The Energy Forge One worked example
Energy Forge One LLC, our launch issue spotlight: Runtime TRS 81 / Framework TRS 83 / DTB 2.6. The DTB is computed assuming:
- 1,056 MW gas combined-cycle, ERCOT-zone, 2027 COD
- Probable Microsoft offtake (rumored, not disclosed)
- Bechtel EPC, GE Vernova OEM
- Interconnection at Agreement, TCEQ permit Filed
- Project NPV scenarios across permit, offtake, and gas-price paths
The 2.6 reads as a high-band signal — comfortably above the financing cliff with current information. As the project moves through milestones (TCEQ approval, PPA disclosure, equipment delivery), σ(NPV) will compress and DTB will move accordingly.
What DTB does not do
DTB does not give you a return forecast. It gives you a margin-of-safety read. The same DTB on a small project versus a 1 GW project carries different absolute money implications. We publish DTB alongside capacity and TRS so the picture is complete; we do not publish a "buy this" recommendation.
It also does not capture all risk. Engineering risk, sponsor execution risk, and macro risk (gas-price regime change, regulatory shift) sit inside σ(NPV) by construction, but the assumption set is ours and visible. If you disagree with our scenario weights, the framework is transparent enough that you can recompute with your own.
Read more: Tokenization Readiness Score →