epstein-forensic-finance
Epstein Financial Forensics
Automated forensic financial reconstruction from 1.48 million DOJ EFTA documents + 503K cataloged media items.
LICENSE NOTICE (effective April 16, 2026): This repository is All Rights Reserved. The prior CC BY 4.0 grant no longer applies to new uses of this work. Copies made prior to April 16, 2026 were distributed under CC BY 4.0 and their status is governed by that license’s terms. All new reuse, mirroring, redistribution, or derivative works require written permission from R.S. Taylor.
We took the documents the Department of Justice released under the Epstein Files Transparency Act and built a forensic financial database from scratch. Wrote all the extraction code. Designed the schema. Built the classification pipeline. Ran the analysis. Team project, start to finish. AI tools helped us write code faster — same way you’d use a calculator. The analytical calls are ours.
Our team background spans multi-affiliate financial reconciliation, budget variance analysis, automated exception reporting at institutional scale, forensic financial analysis, and legal review. We applied those same methods here.
As far as we can tell, nobody else has tried to reconstruct the complete financial infrastructure in the EFTA corpus using quantitative forensic methods. Plenty of good narrative work out there. Plenty of search engines. This is the first attempt to model the full network — fund flows, entity relationships, shell trust hierarchies — at scale.
Project Links
- Website — the-projects.org
- Research Terminal — cloud-efp.com (credentialed access; request access)
- Live API — the-projects.org/api/pub/stats
- Contact — theproject@isipp.com
Current Status (April 16, 2026)
| Metric | Figure |
|---|---|
| Publication ledger records | 6,397 |
| Total dollar volume | $2.308 billion |
| Verified master wires | 481 |
| Documents indexed | 1,476,437 |
| Media items cataloged | 503,517 |
| SAR benchmark coverage | 122.9% |
| Datasets integrated | DS1–DS12, DS98–DS104 |
Confidence Tier Breakdown
| Tier | Records | Total | Description |
|---|---|---|---|
| T1 — Court-verified | 3,875 | $1,661.9M | Bates-stamped bank documents, court exhibits |
| T2 — Bank-verified | 956 | $375.8M | SAR narratives, statement line items |
| T3 — Multi-source | 93 | $12.8M | Two or more independent sources |
| T4 — Unclassified | 1,473 | $257.4M | Corpus-extracted, entity resolution pending |
| Total | 6,397 | $2,308.0M |
Four-Layer Canonical Evidence Model
| Layer | Records | Total | Description |
|---|---|---|---|
| L1 — Master wire ledger | 481 | $973.4M | Individual wire transfers, fully reconciled |
| L2 — Extracted payments | 3,876 | $529.2M | Pipeline-extracted transactions, tier-classified |
| L3 — Bank statements + court-verified | 1,267 | $512.0M | Multi-bank statement parse + Phase 5C/6 FirstBank |
| L4 — Audited fund flows | 773 | $293.4M | Curated from the NLP pipeline, hand-reviewed |
| Total | 6,397 | $2,308.0M |
The SAR benchmark ($1.878B) counts only transactions banks flagged as suspicious. The EFTA corpus holds the complete financial record — including legitimate activity like Sotheby’s auction proceeds, Tudor Futures returns, Kellerhals law firm settlements, and Blockchain Capital VC investments. Total financial flows exceed the suspicious subset. Standard forensic accounting: SAR ⊂ Total Financial Activity.
What Changed in April 2026
Phase 5C — Classified transaction integration. 438 additional records ($211.5M) from the pipeline extraction layer, classified against the publication ledger with full entity resolution.
Phase 5D — Court exhibit integration. 91 unique financial hits ($121.9M) with DB-SDNY exhibit numbers — including the Twitter call options purchases ($3.896M), Venezuelan PdV bonds ($2M), Blockchain Capital III ($1.875M), Joichi Ito transfers, and Leon/Debra Black trust transfers ($10M+).
Phase 6 — FirstBank USVI. 14 records ($4.855M) from FirstBank Virgin Islands accounts, previously identified in the corpus but not extracted.
April 14 corpus integrity audit. Removed $70M of noise from the ledger:
- 21 phantom summary-line records ($53.9M) — JPMorgan statement “Total Debits” rows misread by the OCR pass as transactions
- 341 reclassified interest payments ($4.0M) — moved out of the transaction ledger, into the interest ledger
- 8 cross-layer duplicates ($12.4M)
Net effect: 6,767 → 6,397 records, $2.378B → $2.308B total. Every removal is documented in the audit trail exposed at /api/pub/stats#audit_trail.
Tier Architecture — Shell Trust Hierarchy
Tier 1 — Holding trusts (received external deposits)
- Southern Trust Company Inc. — $151.5M in ← Black, Rothschild, Narrow Holdings
- The 2017 Caterpillar Trust — $15.0M in ← Blockchain Capital
Tier 2 — Distribution trusts (redistributed internally)
- The Haze Trust (DBAGNY) — $49.7M out → Southern Financial, Southern Trust
- The Haze Trust (Checking) — $21.8M in ← Sotheby’s, Christie’s
- Southern Financial LLC — $14.0M in ← Tudor Futures
- Southern Financial (Checking) — $32.0M in ← Haze Trust
Tier 3 — Operating shells (paid beneficiaries)
- Jeepers Inc. (DB Brokerage) — $51.9M out → Epstein personal account (21 wires)
- Plan D LLC — $18.0M out → Leon Black (4 wires)
- Gratitude America MMDA — $6.3M out → Morgan Stanley, charities
- Richard Kahn (attorney) — $9.3M out → Paul Morris, others
- NES LLC — $554K out → Ghislaine Maxwell
Tier 4 — Personal accounts (terminal destinations)
- Jeffrey Epstein NOW/SuperNow — $83.4M in ← Jeepers, Kellerhals, law firms
- Darren Indyke operating accounts — payroll + distributions
Methodology Highlights
- Bates-stamped sourcing. Every T1–T3 figure traces to a Bates-stamped DOJ source document. Any researcher can pull the original page by the number.
- Verification wall. T1–T3 figures are anchored to court exhibits and bank records. T4 holds corpus-extracted transactions where entity resolution is pending; tier labels are surfaced so readers can weight individual rows by source strength.
- NLP phantom autopsy. The
fund_flows_auditedpipeline generated 7,355 total records with 94.8% low confidence and $3.34 billion in phantom volume. Most of that came from emails — forwarded Bloomberg newsletters, news articles, legal memos — where the NER pass found names near dollar signs. Narrative 20 (The Verification Wall) documents which “hits” stand up and which collapse under Bates-stamp review. - Standard forensic accounting framework. GAAS/GAGAS reference standards, AICPA SSFS No. 100 for forensic services, consistent confidence tiers across all dollar attributions.
Where This Fits
Other projects in this space are doing solid work — narrative forensic reporting, searchable archives, community preservation. Our lane is systematic financial reconstruction at scale.
| Approach | Output | Our relationship |
|---|---|---|
| Narrative forensic reporting | Article-length investigations | We cite; we don’t duplicate |
| Searchable archives | Full-text search of the corpus | Complementary — different primitive |
| Network mapping | Who’s connected to whom | Complementary — we prove the transactions |
| This repo | Certified forensic ledger + entity-resolved fund flows | — |
Disclaimer
Findings are tier-labeled. T1–T3 figures are anchored to court exhibits and Bates-stamped DOJ source documents. T4 holds corpus-extracted transactions pending full entity resolution. See
COMPLIANCE.mdfor full professional standards disclaimers.
Analysis conducted under GAAS/GAGAS standards with reference to AICPA SSFS No. 100. All dollar figures are derived from publicly released DOJ documents and court filings.
Author
R.S. Taylor MS Applied Data Science — Syracuse University BS Network & Cyber Security — Wilmington University
Versioning Note
If you are forking, archiving, or citing this work: snapshots capture a moment in time. Do not treat cached versions as authoritative. Always reference the live repository at github.com/randallscott25-star/epstein-forensic-finance for current figures, or the live API at the-projects.org/api/pub/stats.
Last validated: April 16, 2026.
Citation
Taylor, R.S. (2026). Epstein Financial Forensics: Automated forensic financial reconstruction from 1.48 million DOJ EFTA documents. GitHub. https://github.com/randallscott25-star/epstein-forensic-finance#readme
License
All rights reserved. © 2026 R.S. Taylor.
This repository — including the methodology, findings, data narratives, workbooks, tables, figures, and accompanying prose — is original work and is fully copyright-protected. Reproduction, redistribution, repackaging, republication, commercial use, and use for training machine learning models are not permitted without prior written permission. Limited direct quotation for purposes of criticism, commentary, news reporting, or academic research is permitted with attribution.
The underlying DOJ documents are U.S. government publications in the public domain and are not covered by this license. This repository does not reproduce copyrighted source material.
For permission requests: theproject@isipp.com
See LICENSE for full terms.
For the girls.