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

2020-09-25 · 82/93
ClassInterest computedInterest reportedPrincipal computedPrincipal reportedΔ
1-A117,761.0017,761.00152,141.39152,141.390.00
1-AX25,361.2025,361.23——0.03
2-A163,791.1563,791.151,724,363.661,724,363.670.01
2-AX62,513.5862,513.56——0.02
B-116,947.0916,947.09135,891.54135,891.540.00
B-211,298.0611,298.0690,594.3690,594.360.00
B-37,643.407,643.4061,289.1561,289.150.01
B-45,649.035,649.0345,297.1845,297.180.00
B-58,679.798,679.770.000.000.02

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.