How We Follow the Money
Every dollar traced in our database is backed by a Bates-referenced court document. This page documents our sources, verification standards, and the methodology behind the forensic financial analysis of Jeffrey Epstein's financial network.
Last updated: March 27, 2026
Overview
The Epstein Exposed financial forensics database traces money movement through Jeffrey Epstein's network of shell companies, trusts, and personal accounts across seven banking institutions. Our data comes from two primary sources: court-filed exhibits from federal proceedings, and independent community research by volunteer analysts who transcribed bank statements from the EFTA document releases.
Unlike previous attempts to quantify Epstein's financial activity, we prioritize verifiability over volume. Every transaction in our verified dataset links to a specific Bates-referenced court document. Claims that lack documentary support are quarantined in a separate “Claims” tab with clear “UNVERIFIED” labeling, preserving them for future research without contaminating the verified record.
On March 26, 2026, we rebuilt the entire financial database from scratch after community researchers identified significant data integrity issues including double-counting, phantom NLP transactions, and inflated narrative summaries in the previous version.
Data Sources & Provenance
Five independent sources contribute to the database. Each source's methodology, coverage period, and confidence tier is documented below.
Master Wire Ledger
by R.S. Taylor — Independent researcher (not affiliated with Epstein Exposed)
Court-exhibit authenticated wires extracted from DOJ EFTA releases. 25-phase audit pipeline with amount dedup, date-aware census, and entity-pair resolution. Published as open data under CC BY 4.0.
Deutsche Bank & FirstBank USVI Transactions
by TS Whale — Epstein Exposed community researcher
Direct transcription from Deutsche Bank and FirstBank (USVI) statements filed as EFTA court exhibits. Every transaction has an EFTA Bates reference. Deutsche Bank data categorized by entity group (New York, Trusts, Aircraft, Florida/VI, Zorro Ranch) with 34 transaction categories. Also compiled 307 counterparty identifications with investigative context notes.
JPMorgan Transactions
by Anonymous Researcher — Epstein Exposed community researcher
Extracted from JPMorgan Private Bank and Classic Business Checking statements. Covers Jeffrey Epstein personal accounts, Darren K. Indyke PLLC, Southern Trust Company, and NES LLC.
Verification & Confidence Tiers
Every financial flow is assigned a confidence tier based on the strength of its documentary evidence. Higher tiers require stronger provenance.
Transaction appears in a court exhibit with a Bates reference number. Verified by judicial proceedings.
Example: Alfano exhibit wires with DB-SDNY Bates stamps
FinCEN SAR amount match, bank statement correlation, or multi-source cross-reference confirmation.
Example: FinCEN amount matches, audited fund flows with PROVEN/STRONG rating
Independently extracted from bank statements by community researchers with EFTA document references.
Example: Deutsche Bank wire transfers transcribed by TS Whale with EFTA citations
Automatically extracted from OCR text by the finance-extractor agent. Requires admin review before promotion.
Example: Pending extractions from 45,304 financial documents
Bank Coverage
The database covers transactions across seven banking institutions, spanning from 2008 to 2020. Coverage depth varies by bank — Deutsche Bank has the most comprehensive transaction-level data.
Deutsche Bank
FirstBank USVI
JPMorgan Chase
Bank of America
Citibank
Wells Fargo
Barclays
Coverage gaps: Pre-2012 records are limited to court exhibits only. Some banks may have purged records under retention policies. Sealed court documents (estimated $40–60M in additional flows) remain inaccessible.
Deduplication Methodology
Preventing double-counting is the single most critical integrity challenge in financial forensics. The same transaction can appear in multiple source documents, court exhibits, and researcher datasets.
Composite Dedup Key
Every flow has a dedup_key computed as MD5(source_entity + target_entity + amount + date + bates_ref). This is enforced as a UNIQUE database constraint — it is physically impossible to insert the same transaction twice.
Cross-Source Detection
When community bank transaction data overlaps with the master wire ledger, the system detects the match via dedup key comparison and links the records rather than duplicating them. The bank transaction record gets a promoted_flow_id reference to the existing verified flow.
Entity-Level Aggregation
Entity totals (inflows/outflows per entity) are computed via a PostgreSQL materialized view that aggregates only from the verified flows table — never from raw bank transaction records. This prevents the double-counting bug identified in the original database where entity totals counted both sides of each flow.
What We Excluded & Why
The following categories of data were identified as unreliable and removed from the verified dataset. Some are preserved in the Claims tab for research purposes.
Narrative Summaries
Aggregate claims without individual transaction documentation (e.g., '$1.08B JPMorgan suspicious transactions'). These were editorial assertions, not verified transactions. Quarantined to the Claims tab for transparency.
NLP Phantom Transactions
Automated NLP extraction from news articles and emails incorrectly identified dollar amounts near person names as transactions. Examples: '$64.7M attributed to Donald Trump' from news coverage, '$36.6M to Bill Gates' from a journalist's mention. All $0 verified.
Possessive Grammar Artifacts
NLP misinterpreted possessive constructions like 'Donald Trump\'s $3.4M settlement' as self-transfers. Identified and removed during Phase 22 audit.
Chain-Hop Inflation
Internal→Internal transfer chains created 4x multiplier effects where the same money was counted at each hop through shell companies. Identified in Randall Scott\'s Phase 22 audit.
Brokerage Noise
Automated brokerage account movements (margin calls, rebalancing) miscategorized as intentional transfers. Filtered via BROKERAGE_NOISE regex patterns.
ICIJ Offshore Leaks Cross-Reference
We cross-reference all persons in the database against the International Consortium of Investigative Journalists (ICIJ) Offshore Leaks database, which includes the Panama Papers, Paradise Papers, Pandora Papers, and Bahamas Leaks.
955 total matches across 342 unique persons, with 7,273 relationship chains connecting officers to offshore entities. Matches use a minimum fuzzy threshold of 85% and are available via the Offshore API.
Automated Discovery Pipeline
A dedicated AI agent continuously scans court documents for undiscovered financial transactions, feeding a human-review pipeline before any data enters the verified database.
Community Contributions
Independent researchers can submit structured financial transaction data for review and inclusion in the database. All submissions go through admin review before promotion.
Submission Format
POST /api/financial/submit
Content-Type: application/json
{
"contributor": "Your Name / Discord Handle",
"source": "Bank statement transcription",
"transactions": [
{
"from_entity": "Jeffrey Epstein",
"to_entity": "Southern Trust Company",
"amount": 50000,
"date": "2015-03-15",
"bank": "Deutsche Bank",
"transaction_type": "wire",
"efta_ref": "EFTA01234567",
"description": "Wire transfer"
}
]
}Required fields: from_entity, to_entity, amount (min $100)
Optional: date (YYYY-MM-DD), bank, transaction_type, efta_ref, description
Max 500 transactions per submission. All submissions require admin approval.
Attribution & Licensing
This forensic financial analysis is built on the work of independent researchers who donated their time and expertise to public accountability. Proper credit matters.
Eric Keller
Creator — Epstein Exposed Forensic Finance System
Built the 14-tab forensic financial analysis system, designed the v2 database architecture with dedup-key integrity, imported and verified all community-contributed data, created the automated discovery pipeline, and developed the community submission API. Founder and lead developer of Epstein Exposed.
epsteinexposed.comR.S. Taylor
Independent Researcher — Master Wire Ledger (not affiliated with Epstein Exposed)
Created the foundational 481-wire master wire ledger through a 25-phase audit pipeline processing 1.48 million DOJ documents. Published as open data. Self-described as a data scientist whose "day job is multi-affiliate financial reconciliation at institutional scale." Explicitly notes: "I am not a forensic accountant. I am not a prosecutor. I don't hold a CPA or a CFE."
github.com/randallscott25-star/epstein-forensic-financeTS Whale
Community Researcher — Deutsche Bank, FirstBank & Counterparty Data
Independently transcribed 17,613 bank transactions from Deutsche Bank and FirstBank USVI court exhibits, covering 2012 through 2020. Compiled 307 counterparty identifications with investigative context notes. Identified critical data integrity issues in the original database that prompted the full rebuild.
Anonymous Researcher
Community Researcher — JPMorgan Data
Extracted 784 JPMorgan Chase transactions from Private Bank and Classic Business Checking statements, plus monthly financial summaries for the 2013–2014 period.
Disclaimer: This analysis does not constitute an audit, examination, or review performed in accordance with GAAS, GAGAS, or AICPA SSFS No. 1. All financial amounts are sourced from court-filed documents and community research. Entity classifications are analytical, not legal determinations. Appearance in this database does not imply wrongdoing.
The database excludes verified victims and survivors in accordance with our data policy. For questions about the methodology, contact the research team via Discord.
Data built with transparency. Every claim is verifiable.