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

2016-03-25 · 28/93
ClassInterest computedInterest reportedPrincipal computedPrincipal reportedΔ
1-A181,249.1281,249.12797,022.22797,022.220.01
1-AX117,733.72117,733.67——0.05
2-A1175,462.45175,462.45831,916.91831,916.910.00
2-AX174,385.55174,385.48——0.07
B-127,784.5427,784.5328,904.0728,904.060.02
B-218,523.0318,523.0219,269.3819,269.380.01
B-312,531.2512,531.2513,036.1713,036.170.00
B-49,261.519,261.519,634.699,634.690.00
B-512,675.0912,675.230.000.000.14

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.