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

2016-06-27 · 31/93
ClassInterest computedInterest reportedPrincipal computedPrincipal reportedΔ
1-A175,652.7375,652.733,673,558.833,673,558.830.00
1-AX109,531.59109,531.57——0.02
2-A1163,418.58163,418.582,048,169.012,048,169.010.01
2-AX162,171.67162,171.76——0.09
B-127,503.4727,503.4829,392.0029,392.000.01
B-218,335.6518,335.6519,594.6619,594.670.01
B-312,404.4812,404.4913,256.2413,256.240.01
B-49,167.829,167.839,797.339,797.330.01
B-512,667.8312,667.740.000.000.09

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.