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

2020-01-27 · 74/93
ClassInterest computedInterest reportedPrincipal computedPrincipal reportedΔ
1-A125,019.2025,019.20153,475.73153,475.730.00
1-AX37,222.1737,222.24——0.07
2-A182,700.0682,700.061,181,742.221,181,742.220.00
2-AX80,872.5080,872.47——0.03
B-121,046.5421,046.5471,507.3971,507.390.01
B-214,031.0214,031.0347,671.5947,671.590.01
B-39,492.319,492.3132,250.9232,250.920.01
B-47,015.517,015.5123,835.8023,835.800.01
B-512,698.3012,698.300.000.000.00

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.