Waterfall Forensics.

Waterfall Forensics

We ran the contract forward for eight years. It matched to the penny.

Sequoia Mortgage Trust 2013-1: deconstructed from its prospectus into an executable encoding, then replayed against every monthly distribution the trustee ever reported — 93 periods, February 2013 through final termination.

$363M

of actual distributions reproduced

99.7%

of 2,139 comparisons within $1

$0.08

worst principal delta, ever

Every period, every class — computed from the contract vs. reported by the trustee

2017-05-25 · 42/93
ClassInterest computedInterest reportedPrincipal computedPrincipal reportedΔ
1-A153,807.2353,807.23295,526.59295,526.590.01
1-AX78,745.5878,745.55——0.03
2-A1127,203.03127,203.03944,620.63944,620.630.01
2-AX125,668.92125,668.95——0.03
B-126,519.4126,519.4131,408.0031,408.000.00
B-217,679.6117,679.6120,938.6720,938.670.01
B-311,960.6611,960.6614,165.4914,165.490.01
B-48,839.808,839.8010,469.3310,469.330.01
B-512,684.1512,684.140.000.000.01

drag through 93 distribution dates — Δ is the summed absolute difference between the contract-computed and trustee-reported figures for the period

Or see all 93 periods at once: the tie-out heatmap ›

How

The governing documents are deconstructed into a provenance-linked encoding — every waterfall step, trigger, and floor provision cites the clause that defines it. A deterministic interpreter executes that encoding, period by period, against the collateral cashflows the trustee reported. State rolls forward on computed values only; an error anywhere would compound and surface. It doesn't.

The same engine then runs Monte Carlo counterfactuals — what should have happened under different prepayment, default, or servicing behavior — and exports the whole model as readable Python your own analysts run and defend. Every encoding is open to clause-by-clause verification, and every verification lands in an append-only ledger.