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

2021-03-25 · 88/93
ClassInterest computedInterest reportedPrincipal computedPrincipal reportedΔ
1-A114,255.4314,255.43137,919.59137,919.590.00
1-AX20,502.8620,502.90——0.04
2-A138,677.6138,677.611,725,318.951,725,318.950.01
2-AX37,593.2037,593.17——0.03
B-112,288.0812,288.09210,440.27210,440.260.01
B-28,192.068,192.06140,293.51140,293.510.01
B-35,542.115,542.1194,911.7594,911.750.01
B-44,096.034,096.0370,146.7670,146.750.01
B-512,565.8812,565.870.000.000.01

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.