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

2016-02-25 · 27/93
ClassInterest computedInterest reportedPrincipal computedPrincipal reportedΔ
1-A183,225.0683,225.061,635,263.821,635,263.820.00
1-AX120,447.96120,447.92——0.04
2-A1178,100.69178,100.691,706,678.921,706,678.920.00
2-AX176,904.87176,904.93——0.06
B-127,859.1927,859.1929,025.2129,025.210.00
B-218,572.7918,572.7919,350.1419,350.140.00
B-312,564.9212,564.9213,090.8113,090.810.00
B-49,286.409,286.409,675.079,675.070.00
B-512,669.1712,669.130.000.000.04

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.