Building a Money Map

01How to trace a flow of political money end to end using public data — the sources, the joins, and the pitfalls

02Start With a Question, Not a Dataset

The temptation when building a money map is to open a spreadsheet and start downloading. Resist it. Public data on political money is abundant but deeply fragmented, and bulk downloads without a guiding question tend to produce a pile of numbers rather than a story. A workable starting point is a specific entity — a donor, a committee, a sector, an industry — and a direction of travel: where did the money come from, and where did it go?

From that anchor, the map grows outward in hops. A donor writes a check to a political action committee. The committee spends money on advertising, consulting and transfers to other committees. Each of those destinations is itself a disclosure filer. Each hop is a potential join between two datasets, and each join is where most mapping projects either succeed or break down.

03The Public Sources, and What Each One Covers

Three federal databases do the foundational work. The Federal Election Commission's electronic filings cover contributions, expenditures, debts and transfers for federally registered committees — campaigns, party committees, PACs and Super PACs. The Senate Office of Public Records hosts lobbying registrations and disclosure reports under the Lobbying Disclosure Act. The IRS publishes Form 990s for tax-exempt organizations, including the 501(c)(4) social-welfare groups that sit at the center of most dark-money flows.

None of these databases was designed to talk to the others. The FEC uses committee IDs as its primary key. The lobbying database identifies registrants by a separate system. The IRS uses employer identification numbers. A single organization can appear in all three under slightly different names — a common abbreviation in one place, a formal legal name in another, an acronym in a third. Name-matching across sources is painstaking, error-prone work, and it is the most common place where a money map goes wrong.

Several non-profit watchdogs — OpenSecrets, FollowTheMoney.org, the Campaign Finance Institute — have already done much of this reconciliation and publish cleaned, cross-referenced datasets. For most mapping projects, starting with these curated databases rather than raw agency filings saves weeks of work. The trade-off is that curated data reflects the choices those organizations made about classification and attribution; knowing those choices matters when the numbers look surprising.

Three federal databases do the foundational work.

04The Joins That Matter Most

Three connections recur in almost every money map. The first is donor to committee: a named individual or organization contributes to a registered committee, creating a disclosure record with amount, date and occupation or industry. The second is committee to vendor: expenditure records link committees to the firms and individuals they pay, which is how you trace ad buys, consulting contracts and legal fees. The third — and hardest — is the pass-through join, connecting a contribution to a 501(c)(4) or other non-disclosing entity that then funds a Super PAC or runs its own independent expenditures.

That third join is where dark money enters the map, and often where the map goes dark. A 501(c)(4) is not required to disclose its donors publicly, and its Form 990 reports spending in broad categories rather than by recipient. A Super PAC that receives a transfer from a 501(c)(4) discloses the transfer but not the original donors behind it. The money is traceable as far as the non-profit's treasury; after that, the trail requires cross-referencing incorporation records, state-level filings where they exist, and any voluntary disclosures the organization has made.

05Pitfalls Worth Knowing Before You Build

Timing is a chronic problem. Federal disclosure filings have quarterly, monthly or pre- and post-election deadlines depending on the committee type and the period. A contribution made late in a quarter may not appear in public data for weeks. Expenditures on credit can be reported as debts before they appear as payments. Any snapshot of a committee's activity is always a snapshot of what has been filed, not necessarily what has occurred.

Aggregation errors compound this. Small-dollar contributions processed through conduit platforms are often reported in bulk rather than itemized at the individual level, which makes donor-level analysis incomplete for committees that rely heavily on online small-dollar fundraising. Conversely, large bundled contributions can be attributed to the bundler rather than the original source, splitting a single influence relationship across multiple records.

Entity disambiguation remains the hardest sustained challenge. A retired executive who gives from three addresses across a decade, a PAC that changes its registered name mid-cycle, a lobbying firm that restructures as a new entity — all of these fracture what is really a continuous financial relationship into disconnected records. Serious mapping projects maintain internal entity tables that manually reconcile these splits.

The reward for working through the joins and the pitfalls is a map that genuinely tracks influence: who funded what, how the money moved through the system, and where it surfaced as ads, lobbying activity or direct contributions. Public data makes that map possible. Patience, source hygiene and a clear starting question are what make it accurate.

Who's who

Every figure here is an illustrative composite, rounded for clarity. See How We Count for the method — we model no single race, party, or candidate.