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

2014-03-25 · 4/93
ClassInterest computedInterest reportedPrincipal computedPrincipal reportedΔ
1-A1130,808.84130,808.842,939,453.522,939,453.520.00
1-AX194,328.17194,328.13——0.04
2-A1270,646.91270,646.91797,495.48797,495.480.00
2-AX273,126.21273,126.18——0.03
B-130,084.3230,084.3225,950.8025,950.800.00
B-220,056.2120,056.2117,300.5317,300.530.01
B-313,568.4913,568.4811,704.2111,704.210.01
B-410,028.1110,028.118,650.278,650.270.01
B-512,803.1212,803.190.000.000.07

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.