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

2020-10-26 · 83/93
ClassInterest computedInterest reportedPrincipal computedPrincipal reportedΔ
1-A117,577.1617,577.16704,132.85704,132.850.01
1-AX25,071.1725,071.17——0.00
2-A161,125.5761,125.576,493,771.286,493,771.280.01
2-AX59,945.5059,945.49——0.01
B-116,535.1316,535.12490,374.67490,374.670.01
B-211,023.4211,023.42326,916.45326,916.440.01
B-37,457.597,457.59221,166.42221,166.420.00
B-45,511.715,511.71163,458.22163,458.220.00
B-512,604.4112,604.440.000.000.03

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.