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

2021-08-25 · 93/93
ClassInterest computedInterest reportedPrincipal computedPrincipal reportedΔ
1-A112,838.0312,838.0310,624,573.1310,624,573.170.05
1-AX17,702.2117,702.22——0.01
2-A121,864.3121,864.3114,144,030.4914,144,030.480.01
2-AX21,214.4121,214.39——0.02
B-17,915.057,915.052,667,766.062,667,766.060.00
B-25,276.705,276.701,778,510.711,778,510.680.03
B-33,569.813,569.811,203,202.981,203,202.970.01
B-42,638.352,638.35889,255.35889,255.350.00
B-516,175.9516,176.034,178,279.004,178,278.950.13

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.