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

2017-10-25 · 47/93
ClassInterest computedInterest reportedPrincipal computedPrincipal reportedΔ
1-A148,135.7348,135.731,545,914.881,545,914.880.00
1-AX70,440.5370,440.49——0.04
2-A1120,412.98120,412.98644,617.26644,617.260.01
2-AX118,700.00118,700.09——0.09
B-126,019.4726,019.4732,714.1232,714.120.00
B-217,346.3117,346.3121,809.4121,809.410.01
B-311,735.1811,735.1814,754.5614,754.560.01
B-48,673.168,673.1610,904.7110,904.710.01
B-512,676.6712,676.670.000.000.00

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.