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

2015-04-27 · 17/93
ClassInterest computedInterest reportedPrincipal computedPrincipal reportedΔ
1-A1101,025.42101,025.422,327,026.642,327,026.640.00
1-AX146,345.63146,345.68——0.05
2-A1226,860.21226,860.2111,141,215.3611,141,215.360.00
2-AX227,056.74227,056.70——0.04
B-128,783.3628,783.3627,595.3727,595.370.01
B-219,188.9119,188.9118,396.9118,396.910.00
B-312,981.7312,981.7312,445.9312,445.930.00
B-49,594.459,594.459,198.469,198.460.01
B-512,698.6812,698.660.000.000.02

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.