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

2017-06-26 · 43/93
ClassInterest computedInterest reportedPrincipal computedPrincipal reportedΔ
1-A153,450.1353,450.13854,686.44854,686.440.00
1-AX78,479.9478,479.94——0.00
2-A1125,742.81125,742.81771,044.98771,044.980.00
2-AX124,272.26124,272.32——0.06
B-126,447.1526,447.1631,560.3631,560.360.01
B-217,631.4417,631.4421,040.2421,040.240.01
B-311,928.0711,928.0714,234.2014,234.200.01
B-48,815.728,815.7210,520.1210,520.120.00
B-512,695.2312,695.240.000.000.01

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.