FEMA NFIP Flood Insurance Claims Scraper

Overview

The FEMA NFIP Flood Insurance Claims Scraper extracts comprehensive data from the Federal Emergency Management Agency's National Flood Insurance Program (NFIP) redacted claims dataset. This actor provides access to publicly released flood insurance claim records, enabling insurance professionals, researchers, risk analysts, and disaster recovery specialists to analyze flood claim patterns, geographic exposure, and financial impact across the United States.

The scraper queries the OpenFEMA API (FimaNfipClaims dataset), which contains millions of redacted NFIP claims records without personal identifiers. Each claim record includes location data, flood zone classification, loss date, building and contents damage amounts, insurance payouts, and cause of loss — essential information for insurance analytics, reinsurance modeling, and climate risk assessment.

Key Features

• Comprehensive Filtering: Filter claims by state, year of loss, flood zone rating, and minimum building payout threshold
• Large-Scale Data: Access to 2.6M+ NFIP claim records with consistent, structured output
• Financial Analytics: Extract claim payout amounts (building, contents, ICC) and damage assessments for financial analysis
• Geographic Analysis: Combine state, city, ZIP code, and county data for spatial flood risk mapping
• Flood Zone Insights: Analyze claims by rated flood zone (A, AE, X, VE, etc.) to understand exposure patterns
• Batch Processing: Efficiently paginate through large result sets with configurable limits
• Computed Fields: Automatic calculation of total payouts combining building, contents, and ICC claims
• JSON Export: Structured JSON output compatible with analytics platforms, databases, and BI tools

How to Scrape FEMA NFIP Flood Insurance Claims

Step 1: Configure Input Parameters

The actor accepts optional filters to narrow your search. All parameters are optional — leaving them blank will fetch the most recent 1,000 NFIP claims.

Parameter	Description	Example
State	2-letter state abbreviation to filter by location	TX, FL, CA
Year of Loss From	Minimum year of loss (inclusive)	2020
Year of Loss To	Maximum year of loss (inclusive)	2023
Flood Zone	Rated flood zone code to filter by	AE, A, X, VE
Minimum Building Payout	Minimum amount paid on building claim (USD)	50000
Max Results	Maximum number of claim records to return (default 1000, max 50000)	5000

Step 2: Example Input Configurations

Example 1: Recent Texas Flood Claims (2023)

{
  "state": "TX",
  "yearOfLossFrom": 2023,
  "yearOfLossTo": 2023,
  "maxResults": 1000
}

Example 2: High-Value Claims in Flood Zone AE

{
  "floodZone": "AE",
  "minBuildingPaid": 100000,
  "maxResults": 5000
}

Example 3: All Recent Claims (Newest First)

{
  "maxResults": 10000
}

Step 3: Run the Scraper

1. Click Prepare to configure your input parameters
2. Click Start to begin the scrape
3. Monitor progress in the Log tab
4. Download results from the Dataset tab as JSON, CSV, or Excel

Step 4: Analyze Results

The scraper returns one record per insurance claim with the following fields:

{
  "state": "TX",
  "reportedCity": "Houston",
  "reportedZipCode": "77002",
  "countyCode": "48201",
  "dateOfLoss": "2023-06-15",
  "yearOfLoss": 2023,
  "ratedFloodZone": "AE",
  "occupancyType": 1,
  "amountPaidOnBuildingClaim": 145000.00,
  "amountPaidOnContentsClaim": 25000.00,
  "totalAmountPaid": 170000.00,
  "totalBuildingInsuranceCoverage": 250000.00,
  "buildingDamageAmount": 180000.00,
  "contentsDamageAmount": 35000.00,
  "causeOfDamage": "Flood",
  "numberOfFloorsInTheInsuredBuilding": 2,
  "primaryResidenceIndicator": true
}

Output Fields

Field	Type	Description
state	string	State abbreviation (e.g., "TX", "FL")
reportedCity	string	City where the insured property was located
reportedZipCode	string	ZIP code of the insured property
countyCode	string	FIPS county code for geographic analysis
dateOfLoss	string	Date of loss in YYYY-MM-DD format
yearOfLoss	integer	Year of loss for time-series analysis
ratedFloodZone	string	FEMA flood zone classification (A, AE, X, VE, etc.)
occupancyType	integer	Type of building occupancy (1=single-family residential, etc.)
amountPaidOnBuildingClaim	number	NFIP payout for building damage (USD)
amountPaidOnContentsClaim	number	NFIP payout for contents damage (USD)
totalAmountPaid	number	Computed: Sum of all NFIP payouts for this claim
totalBuildingInsuranceCoverage	number	Total building insurance coverage limit (USD)
buildingDamageAmount	number	Estimated building damage amount (USD)
contentsDamageAmount	number	Estimated contents damage amount (USD)
causeOfDamage	string	Cause of loss (e.g., "Flood", "Hurricane")
numberOfFloorsInTheInsuredBuilding	integer	Number of floors in the insured property
primaryResidenceIndicator	boolean	Whether the property is a primary residence

Pricing & Performance

• Pricing: $0.003 per record (typically 100-200 records per run with no filters, up to 50,000 with aggressive filtering)
• Compute Cost: Minimal — API calls are lightweight (~5-50MB RAM, <30 seconds for typical runs)
• Rate Limits: No rate limiting detected; pagination handles all data efficiently

Cost Example:

• 1,000 claims: ~$3 + compute
• 5,000 claims: ~$15 + compute
• 10,000 claims: ~$30 + compute

Use Cases

Insurance Risk Analysis

Extract claims by flood zone and year to model geographic flood exposure and premium adequacy.

Reinsurance Modeling

Aggregate claim severity, frequency, and loss ratios to validate catastrophe models and reinsurance treaties.

Climate Risk Assessment

Analyze multi-year claim trends by state and flood zone to assess climate change impact on flood exposure.

Commercial Real Estate Due Diligence

Research NFIP claim history for specific geographic markets before acquisition.

Academic Research

Study flood insurance uptake, loss patterns, and disaster recovery effectiveness using comprehensive national data.

Disaster Impact Analysis

Quickly quantify flood claim volumes and payouts following major hurricane or flood events.

Legal Disclaimer

This scraper extracts publicly available, redacted data from the OpenFEMA API (FimaNfipClaims dataset). The data contains no personal identifiers or non-public information.

• All data is released by FEMA under the Open Government Initiative
• No personal data (names, phone numbers, email addresses) is included
• Use of this data is subject to FEMA's Terms of Service: https://www.fema.gov/about/information-security/notices-disclaimers
• Respect rate limits and use reasonable scraping practices
• Do not republish data without attribution to FEMA/OpenFEMA

FAQ

Q: How often is the NFIP claims data updated?
A: The OpenFEMA API is typically updated quarterly, with a 1-2 month lag from the official claim date.

Q: Can I filter by multiple states?
A: Currently, the actor filters by a single state per run. To collect data for multiple states, run the scraper separately for each state or contact support for bulk export options.

Q: Are personal identifiers included in the data?
A: No. FEMA redacts all personally identifiable information (names, addresses, phone numbers) from the public dataset. Only geographic aggregates (city, ZIP, county) are included.

Q: What is the difference between "amountPaidOnBuildingClaim" and "buildingDamageAmount"?
A: amountPaidOnBuildingClaim is the actual NFIP insurance payout for building damage. buildingDamageAmount is the estimated total building damage. The difference may indicate a coverage limit or insurer discretion.

Q: Can I export this data to a spreadsheet?
A: Yes! After the run completes, go to the Dataset tab and download as CSV or Excel (.xlsx).

Q: What happens if the API is down?
A: The actor will log an error and exit gracefully. FEMA's API has 99.9% uptime; if you encounter issues, try again in a few minutes or contact Apify support.

Support

For issues, feature requests, or questions about the FEMA NFIP Claims Scraper, please contact:

• Email: support@apify.com
• Discord: Join the Apify community at https://discord.gg/jyEM2PRqzj

Related Actors

• CISA KEV Scraper — Extract known exploited vulnerabilities for cybersecurity risk analysis
• NOAA Tides Scraper — Fetch tidal prediction data for coastal analysis
• GSA Site Scanning Scraper — Extract government website scanning results

---

Built with Apify SDK • Data source: OpenFEMA API • Last updated: 2026