Methodology

FunderKit builds foundation profiles by processing IRS Form 990-PF filings. Here's how we turn raw tax filings into actionable intelligence for nonprofit fundraisers.

Data Collection

We download bulk XML files from the IRS Tax Exempt Organization Search (TEOS) system. These files contain machine-readable versions of every electronically filed Form 990-PF. We process filings from multiple tax years to build historical trends.

Parsing

Each 990-PF filing is parsed to extract:

• Organization details — name, EIN, address, NTEE classification
• Grant information (Part XV) — recipient name, address, amount, and purpose for each grant awarded
• Officer data (Part VIII) — names, titles, and compensation of trustees, directors, and key employees
• Financial data (Part I) — total revenue, expenses, assets, and giving amounts

Organization Enrichment

We cross-reference parsed organizations with the IRS Business Master File (BMF) to add NTEE classification codes. NTEE codes categorize nonprofits into 26 major groups (e.g., B for Education, E for Health Care) and hundreds of subcategories.

Grant Recipient Resolution

Grant recipient names in 990-PF filings are free-text fields, which means the same organization may appear with different name variations. We use a multi-pass matching process:

1. EIN matching — when a grantee EIN is provided, we match directly
2. Exact name + state matching — matching on organization name and state
3. Normalized name matching — removing common suffixes (Inc, Corp, Foundation) and matching on normalized forms

Funder Profile Computation

For each grantmaking foundation, we compute a profile that summarizes their giving patterns:

• Grant statistics — average, median, min, and max grant amounts over the most recent 3-year period
• Geographic distribution — percentage of grants by state
• NTEE distribution — percentage of grants by recipient category
• Grantee analysis — number of unique grantees, repeat grantee percentage, new grantee percentage
• Giving trend — whether total giving is growing, stable, or declining based on year-over-year comparison

Limitations

Our data has some inherent limitations:

• Only electronically filed 990-PFs are available — paper filings are not included
• There is typically a 6-12 month lag between when a foundation files and when the filing appears in the IRS TEOS system
• Grant purpose descriptions vary in quality — some foundations provide detailed descriptions while others use generic language
• Name matching for grant recipients is not perfect — some grants may not be linked to their correct recipient organization

For details on the specific data sources we use, see our data sources page.