Location Risk Report

Location Risk Report gives you a comprehensive location risk assessment for any address, city, or coordinate pair in under two minutes. Feed it a location and it queries 15 public data sources in parallel — FEMA disaster declarations, USGS earthquakes, NOAA severe weather, EPA contamination records, air quality sensors, crime statistics, property data, and more — then scores and grades the location across five risk dimensions for insurance underwriting, real estate due diligence, and site selection.

The result is a composite risk score from 0 to 100 with an underwriting grade ranging from LOW RISK — PREFERRED RATE to UNINSURABLE / EXTREME RISK. Each of the five dimensions — multi-hazard exposure, environmental contamination, infrastructure quality, climate trajectory, and crime safety — is scored and explained in plain language, so you understand exactly what is driving the risk, not just the number. No code or GIS expertise required.

What data can you extract?

Why use Location Risk Report?

Manually assessing a location for natural hazards, contamination, crime, and infrastructure requires logging into six government portals, downloading ZIP files, cross-referencing FEMA's disaster database, querying the EPA ECHO system, checking USGS seismic history, and still producing no summary. A typical due diligence analyst spends 3–6 hours on a single location. At scale — evaluating 10, 50, or 200 properties — it becomes impossible without a data team.

This actor automates the entire process. One input, 15 data sources, one structured report. A commercial underwriter or acquisitions analyst gets a full risk briefing in under two minutes, with every signal explained and every source counted.

Beyond the automation itself, running on Apify gives you:

• Scheduling — run daily, weekly, or custom intervals to refresh risk profiles as new FEMA declarations or EPA enforcement actions are filed
• API access — trigger runs from Python, JavaScript, or any HTTP client to integrate with underwriting platforms, CRM systems, or internal tools
• Proxy rotation — all sub-actor calls use Apify's infrastructure with automatic error handling and retries
• Monitoring — receive Slack or email alerts when runs fail or when risk scores exceed a defined threshold
• Integrations — connect to Zapier, Make, Google Sheets, or webhooks to route high-risk alerts to your team automatically

Features

• 15 data sources queried in parallel — FEMA disaster declarations, USGS earthquakes, NOAA weather alerts, GDACS global disasters, UK flood warnings, weather forecasts, OpenAQ air quality, EPA ECHO enforcement records, UK police crime data, OpenStreetMap POIs, Open Charge Map EV stations, UK Land Registry, UK food hygiene ratings, Nominatim geocoder, and sunrise/sunset data
• Five-dimension risk scoring — each dimension uses its own calibrated 0–100 scoring function with explicit breakpoints and thresholds derived from real government data ranges
• Composite underwriting score with weighted combination: hazard exposure (30%), climate trajectory (25%), contamination (20%), crime safety (15%), infrastructure quality (10%, inverted)
• Four underwriting grades — LOW RISK / PREFERRED RATE, MODERATE RISK / STANDARD PREMIUM, HIGH RISK / ELEVATED PREMIUM, UNINSURABLE / EXTREME RISK
• Multi-hazard zone detection — flags locations where three or more hazard types (seismic, flood, FEMA, severe weather, global disasters) overlap
• FEMA disaster declaration history — scores based on declaration count: 1–5 declarations (5 pts), 6–20 declarations (15 pts), 20+ declarations (25 pts — extreme disaster zone)
• Seismic risk from USGS magnitude data — filters for M4.0+ events, scores 1–5 significant events at 10 pts, 5+ events at 20 pts
• NOAA severe weather alert filtering — distinguishes between severe/extreme alerts (8–15 pts) and minor alerts (3 pts)
• EPA ECHO contamination density scoring — 1–5 enforcement records (8 pts), 6–20 records (20 pts), 20+ records (35 pts — severe contamination zone)
• OpenAQ AQI thresholds — WHO-aligned scoring: AQI 50–100 (10 pts), 100–150 (20 pts), 150+ (30 pts — unhealthy)
• Infrastructure quality inversion — higher POI density, EV charging availability, property values, and food hygiene compliance all reduce the composite risk score
• Configurable search radius from 1 to 500 km, with a sensible 150 km default that captures regional hazard patterns
• Optional climate data — disable weather forecast and sunrise/sunset collection to reduce cost and run time
• Global address resolution via Nominatim — accepts free-text addresses, city names, or decimal degree coordinates
• Structured raw data excerpts — the top 10 records from each source are included in output for independent verification

Use cases for location risk assessment

Insurance underwriting and pre-binding due diligence

Commercial and residential property underwriters need standardized risk data before binding coverage. This actor generates a pre-binding location assessment in under two minutes — covering the same data dimensions (natural hazards, contamination, crime, infrastructure) that underwriters check manually. Feed it a property address, receive a risk grade, and use the recommendation field to justify premium adjustments or declinations. Particularly useful for surplus lines underwriters handling unusual or high-risk locations.

Real estate investment screening

Acquisitions teams evaluating portfolios of 10–200 properties can run each address through the actor to screen out high-risk locations early in the pipeline. A composite score above 50 flags locations worth deeper investigation. The infrastructure quality score highlights underdeveloped areas that may carry hidden costs. The climate trajectory dimension surfaces locations facing rising physical risk — a growing concern for long-term property holds.

Corporate site selection and facilities management

Corporate real estate teams evaluating office, warehouse, manufacturing, or data center locations need to compare candidate sites on risk-adjusted terms. Run each shortlisted address through the actor, compare composite scores, and document the findings for board approval. The multi-hazard zone detection flag is especially relevant for business continuity planning — a distribution center in a zone with overlapping seismic, flood, and severe weather risks carries supply chain exposure that a score alone may understate.

Disaster preparedness and emergency planning

Emergency management teams use FEMA, USGS, NOAA, and GDACS data to identify areas with convergent hazard exposure. This actor aggregates all four sources in a single call, flags multi-hazard zones automatically, and outputs the specific hazard types driving risk. A county emergency manager can assess multiple communities in an afternoon rather than querying each federal database separately.

Environmental consulting and contamination screening

Environmental consultants conducting Phase I site assessments can use the EPA ECHO density score and OpenAQ air quality readings as a rapid screening layer before committing to on-site investigation. The contamination score thresholds — 1–5 records, 6–20 records, 20+ records — correspond to low, moderate, and high contamination concern zones, giving consultants a quick triage signal.

Mortgage lending and property valuation

Mortgage lenders and appraisers are increasingly required to disclose physical risk. This actor provides the underlying data signals — FEMA history, seismic proximity, flood warnings, air quality — needed to populate physical risk disclosures and inform loan-to-value adjustments in climate-exposed markets.

How to run a location risk assessment

1. Enter the location — Type any address, city name, or coordinate pair into the Location field. Examples: "Chicago, IL", "Tower Bridge, London", "40.7128,-74.0060". The actor geocodes it automatically.
2. Set the search radius — The default 150 km captures regional hazard patterns such as earthquake history and FEMA declarations. Use 25–50 km for urban site assessments where you want only nearby signals.
3. Choose climate data — Leave "Include Climate Data" enabled (default) for a full five-dimension report. Disable it to skip weather forecast collection and reduce run time by roughly 30 seconds.
4. Download your report — Click "Start" and wait approximately 60–120 seconds. Download the structured JSON report from the Dataset tab, or export as CSV or Excel.

Input parameters

Input examples

Standard location assessment (most common):

{
  "location": "Houston, TX",
  "radius": 150,
  "includeClimate": true
}

Precise coordinate input for a specific property:

{
  "location": "29.7604,-95.3698",
  "radius": 50,
  "includeClimate": true
}

Fast screening run without climate data:

{
  "location": "Miami, FL",
  "radius": 100,
  "includeClimate": false
}

Input tips

• Use 25–75 km radius for urban site assessments — a 150 km default captures state-level hazard patterns; tighten the radius when you need signals specific to a neighbourhood or industrial park.
• Coordinates give more precise results — for a specific property address, look up the decimal degree coordinates first and pass them directly to get the tightest data match.
• Disable climate data for batch screening — when scoring a large list of properties, set includeClimate to false to cut run time by about 20–30% and reduce cost.
• US locations return the richest data — FEMA declarations, NOAA alerts, USGS earthquake data, and EPA ECHO records are all US-centric. UK locations add crime, flood, land registry, and food hygiene data. Global locations are scored on USGS, GDACS, OpenAQ, and OSM POI data.

Output example

{
  "location": "Houston, TX",
  "coordinates": {
    "latitude": 29.7604,
    "longitude": -95.3698
  },
  "generatedAt": "2026-03-20T09:14:33.000Z",
  "overallRiskScore": 54,
  "grade": "HIGH RISK — ELEVATED PREMIUM",
  "recommendation": "Elevated risk location. Apply risk-adjusted premiums. Require additional inspections and mitigation measures before binding.",
  "dimensions": {
    "hazardExposure": {
      "score": 55,
      "riskLevel": "EXTREME RISK",
      "findings": [
        "24 FEMA disaster declarations — extreme historical disaster zone",
        "2 significant earthquake(s) (M4.0+)",
        "4 severe NOAA alert(s)",
        "Multi-hazard zone: FEMA disasters, seismic, severe weather"
      ],
      "hazardTypes": ["FEMA disasters", "seismic", "severe weather"]
    },
    "contamination": {
      "score": 28,
      "riskLevel": "MODERATE CONTAMINATION RISK",
      "findings": [
        "11 EPA enforcement records — moderate contamination risk",
        "Air quality index 62 — moderate air quality"
      ]
    },
    "infrastructureQuality": {
      "score": 68,
      "label": "GOOD",
      "findings": [
        "47 points of interest — well-developed area",
        "18 EV charging stations — excellent modern infrastructure",
        "Location successfully geocoded — well-mapped area"
      ]
    },
    "climateTrajectory": {
      "score": 46,
      "label": "ELEVATED CLIMATE RISK",
      "findings": [
        "2 extreme temperature forecast(s) — climate stress",
        "4 NOAA alert(s) active",
        "24 historical FEMA disasters — recurring climate pattern"
      ]
    },
    "crimeSafety": {
      "score": 0,
      "label": "LOW CRIME RISK",
      "findings": ["No crime data available for this location"]
    }
  },
  "dataSources": {
    "femaDisasters": 24,
    "earthquakes": 7,
    "noaaAlerts": 4,
    "gdacsDisasters": 0,
    "ukFloods": 0,
    "weatherForecasts": 7,
    "airQualityReadings": 8,
    "epaRecords": 11,
    "crimeIncidents": 0,
    "pointsOfInterest": 47,
    "evChargingStations": 18,
    "landRegistryRecords": 0,
    "foodHygieneRatings": 0
  },
  "rawData": {
    "geocode": [{ "lat": "29.7604", "lon": "-95.3698", "display_name": "Houston, Harris County, Texas, United States" }],
    "femaDisasters": [
      { "disasterNumber": "DR-4332", "declarationTitle": "Hurricane Harvey", "declarationDate": "2017-08-25" },
      { "disasterNumber": "DR-4485", "declarationTitle": "Tropical Storm Imelda", "declarationDate": "2019-09-19" }
    ],
    "earthquakes": [
      { "magnitude": "4.3", "place": "12km SE of Katy, TX", "time": "2023-08-14T12:33:00.000Z" }
    ],
    "noaaAlerts": [
      { "event": "Heat Advisory", "severity": "Moderate", "headline": "Heat Advisory until 8 PM CDT" }
    ]
  }
}

Output fields

How much does it cost to run a location risk assessment?

Location Risk Report uses pay-per-run pricing. Each run costs approximately $0.40–$1.00 in Apify platform credits, depending on how many data sources return results and whether climate data is included. Compute costs are included.

You can set a maximum spending limit per run to control costs. The actor stops when your budget is reached.

Compare this to dedicated property risk intelligence platforms that charge $500–$2,000/month for a fixed number of lookups — most users running 20–50 assessments per month spend $10–$25 with no subscription commitment.

Location risk assessment using the API

Python

from apify_client import ApifyClient

client = ApifyClient("YOUR_API_TOKEN")

run = client.actor("ryanclinton/location-risk-report").call(run_input={
    "location": "Houston, TX",
    "radius": 150,
    "includeClimate": True
})

for item in client.dataset(run["defaultDatasetId"]).iterate_items():
    print(f"Location: {item['location']}")
    print(f"Risk Score: {item['overallRiskScore']}/100")
    print(f"Grade: {item['grade']}")
    print(f"Recommendation: {item['recommendation']}")
    hazard = item['dimensions']['hazardExposure']
    print(f"Hazard Exposure: {hazard['score']}/100 — {hazard['riskLevel']}")

JavaScript

import { ApifyClient } from "apify-client";

const client = new ApifyClient({ token: "YOUR_API_TOKEN" });

const run = await client.actor("ryanclinton/location-risk-report").call({
    location: "Houston, TX",
    radius: 150,
    includeClimate: true
});

const { items } = await client.dataset(run.defaultDatasetId).listItems();
for (const item of items) {
    console.log(`Location: ${item.location}`);
    console.log(`Risk Score: ${item.overallRiskScore}/100 — ${item.grade}`);
    console.log(`Hazard: ${item.dimensions.hazardExposure.score} | Contamination: ${item.dimensions.contamination.score}`);
    console.log(`Infrastructure: ${item.dimensions.infrastructureQuality.label}`);
    console.log(`Recommendation: ${item.recommendation}`);
}

cURL

# Start the actor run
curl -X POST "https://api.apify.com/v2/acts/ryanclinton~location-risk-report/runs?token=YOUR_API_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{"location": "Houston, TX", "radius": 150, "includeClimate": true}'

# Fetch results (replace DATASET_ID from the run response)
curl "https://api.apify.com/v2/datasets/DATASET_ID/items?token=YOUR_API_TOKEN&format=json"

How Location Risk Report works

Phase 1: Geocoding and coordinate resolution

The actor first passes the input location to the Nominatim geocoder (ryanclinton/nominatim-geocoder) to resolve the address or place name into decimal degree coordinates. Free-text addresses, city names, landmark names, and pre-formatted coordinate strings (e.g., "40.7128,-74.0060") are all accepted. If geocoding succeeds, the resolved latitude and longitude are used for radius-based queries in all subsequent steps. If geocoding fails, the original location string is passed to text-based sources (FEMA, NOAA, EPA ECHO) while coordinate-dependent sources return limited results.

Phase 2: 14 parallel data source calls

With coordinates resolved, the actor fires up to 14 sub-actor calls simultaneously using Promise.all, with a 120-second timeout per call. Each sub-actor is a purpose-built wrapper around a public government or open data API:

• Natural hazards: FEMA disaster search (text query, maxResults: 20), USGS earthquake search (coordinate + radius, maxResults: 20), NOAA weather alerts (text query, maxResults: 15), GDACS global disaster alerts (coordinate-based, maxResults: 10), UK flood warnings (text query, maxResults: 10)
• Environmental: EPA ECHO enforcement search (text query, maxResults: 20), OpenAQ air quality (coordinate + text, maxResults: 15)
• Crime and safety: UK police crime data (coordinate-based, maxResults: 50)
• Geospatial and infrastructure: OSM POI search (coordinate-based, maxResults: 30), Open Charge Map EV stations (coordinate-based, maxResults: 20), UK Land Registry (text query, maxResults: 15), UK food hygiene ratings (text query, maxResults: 20)
• Climate (conditional): weather forecast (coordinate-based, maxResults: 7), sunrise/sunset data (coordinate-based)

Sub-actor failures return empty arrays and are logged without aborting the run. Missing data sources simply produce zero contribution to the affected dimension's score.

Phase 3: Five-model scoring

Each dimension is scored independently before the composite is calculated:

Multi-Hazard Exposure (weight: 30%) — FEMA declaration count is the primary driver (up to 25 pts for 20+ declarations). USGS earthquake count is filtered for M4.0+ events (up to 20 pts for 5+ significant events). NOAA alerts are split into severe/extreme (up to 15 pts) vs. non-severe (3 pts). GDACS proximity adds 10 pts. UK floods add up to 15 pts for 5+ warnings. Multi-hazard zone detection triggers when 3+ hazard type categories are present.

Environmental Contamination (weight: 20%) — EPA ECHO records are the strongest signal (up to 35 pts for 20+ enforcement records). OpenAQ readings are averaged across all returned sensors and scored against WHO AQI thresholds: good (<50), moderate (50–100, +10 pts), unhealthy for sensitive groups (100–150, +20 pts), unhealthy (150+, +30 pts). UK food hygiene low ratings (score ≤2) serve as a secondary sanitation proxy.

Infrastructure Quality (weight: 10%, inverted) — Scored on abundance and quality: OSM POI density, EV charging station count as a modern infrastructure proxy, food establishment hygiene pass rate (ratio of establishments rated 4+), UK Land Registry average sale price, and geocoding resolution. This dimension is inverted before combining — a score of 70 (EXCELLENT) contributes only 30 points of composite risk, while a score of 20 (POOR) contributes 80 points.

Climate Trajectory (weight: 25%) — Weather forecast extremes (temperature >40°C or <-20°C, storm/hurricane/tornado/blizzard descriptors, wind >50 km/h) contribute up to 45 pts. Active NOAA alert volume adds 5–15 pts. Historical FEMA count serves as a recurring climate pattern indicator (up to 15 pts). Extreme day length (< 8 h or > 16 h via sunrise/sunset data) flags harsh latitude climate (+10 pts).

Crime Safety (weight: 15%) — Total UK crime incident volume drives the base score (5+ incidents: +12 pts, 30+ incidents: +25 pts, 100+ incidents: +40 pts). Violent crime proportion (incidents categorised as violence, robbery, or weapons offences comprising >30% of total) triggers an additional 30-point penalty.

Composite formula: total = hazard×0.30 + climate×0.25 + contamination×0.20 + crime×0.15 + (100−infrastructure)×0.10, capped at 100.

Phase 4: Output assembly

The structured report is assembled and pushed to the Apify dataset as a single JSON record. It contains the composite score, grade, recommendation, all five scored dimensions with their findings arrays, a dataSources count object for every queried source, and rawData excerpts (top 5–10 records) from each source for independent verification or downstream processing.

Tips for best results

1. Use the search radius to control signal scope. A 150 km default captures regional earthquake history and FEMA declarations. For a specific property or urban block, a 25–50 km radius isolates local signals (POIs, EV charging, crime) without noise from distant hazards that won't affect the property directly.

2. Run US locations for the fullest report. FEMA declarations, NOAA alerts, USGS earthquake data, and EPA ECHO records are all US-centric APIs. A US location returns data from 12–14 of the 15 sources. A non-US location outside the UK typically returns data from 6–8 sources.

3. Combine with Company Deep Research for corporate site selection. Run Location Risk Report on a candidate site address, then run Company Deep Research on the operator or tenant to get both physical and commercial risk in one workflow.

4. Disable climate data for large batch screening. When evaluating 50+ locations, set includeClimate: false to skip two sub-actor calls per run. You lose the climate trajectory dimension but cut cost and run time meaningfully. Re-enable it for the top 10–20 shortlisted locations.

5. Use the findings arrays for narrative reporting. Each dimension's findings array contains human-readable sentences explaining the signals detected. These are designed to be pasted directly into a due diligence memo or underwriting file without reformatting.

6. Cross-reference EPA ECHO records with the raw data. The rawData.epaEcho field includes facility IDs and violation details. For locations with contamination scores above 30, check the raw EPA records to determine whether violations are active or historical.

7. Store reports for trend analysis. Run the same location monthly or quarterly and compare composite scores over time. Rising hazard or climate trajectory scores may indicate increasing physical risk that warrants insurance review or lease renegotiation.

Combine with other Apify actors

Limitations

• Crime data is UK-only. The UK police crime API covers England and Wales. US, EU, and global locations return no crime data, and the crime safety dimension scores 0 — it does not inflate the composite risk, but it is also absent. For US crime data, supplement with external sources.
• FEMA and NOAA data are US-only. Non-US locations will not produce FEMA disaster declaration history or NOAA severe weather alerts. The hazard exposure score for international locations relies on USGS earthquake data, GDACS alerts, and UK flood warnings only.
• UK-specific sources require UK locations. UK Land Registry, UK food hygiene, and UK flood warnings return empty results for non-UK addresses. Infrastructure quality scoring is therefore less precise outside the UK.
• No probabilistic flood or wildfire maps. The actor uses flood warning counts (active warnings at query time) and FEMA declaration history, not official FEMA flood zone maps (SFHA zones) or USFS wildfire hazard potential rasters. It provides a risk signal, not a regulatory flood zone determination.
• Air quality is a point-in-time reading. OpenAQ returns recent sensor data, not annual averages or health-adjusted AQI computed by the EPA. Readings can vary significantly by season and day. High-stakes contamination assessments should supplement with EPA AQS annual summaries.
• Sub-actor failures are silent. If an upstream API is unavailable during a run, the affected sub-actor returns an empty array and the dimension is scored with zero contribution from that source. The report does not flag which sources failed. Check dataSources counts — a value of 0 for FEMA in a US location likely indicates a source issue, not genuine absence of disaster history.
• Infrastructure quality uses proxy indicators, not official ratings. POI density, EV station count, and food hygiene scores are indirect measures of infrastructure maturity. Areas with dense commercial activity may score "EXCELLENT" on infrastructure while still lacking basic utilities or transport.
• Run time is 60–150 seconds depending on how many sub-actors return results. Large radii on active locations generate more data and take longer to process. The actor cannot be run in under 30 seconds.

Integrations

• Zapier — trigger a location risk report when a new property record is added in your CRM, then post the grade to a Slack channel
• Make — build a multi-step underwriting workflow that runs location risk, formats the report, and emails it to the assigned underwriter
• Google Sheets — export batch location assessments to a spreadsheet and use conditional formatting to highlight HIGH RISK and UNINSURABLE grades
• Apify API — integrate directly into underwriting platforms, property management software, or loan origination systems via REST
• Webhooks — receive a POST notification when each run completes, including the risk score and grade, to trigger downstream alerts
• LangChain / LlamaIndex — feed location risk reports into RAG pipelines for AI-powered property briefings or underwriting decision support tools

Troubleshooting

• Report shows 0 for FEMA and NOAA but location is in the US — FEMA and NOAA text-based queries are sensitive to location string format. Try a more specific address (e.g., "Houston, Harris County, TX" instead of "Houston") or pass explicit coordinates as the location input. Check the dataSources.femaDisasters count to confirm whether data returned at all.

• All data source counts are 0 — The geocoding step likely failed. The actor logs a warning when Nominatim cannot resolve the location. Verify that the location string is a real, recognisable place. Coordinates in decimal degree format (e.g., "29.7604,-95.3698") bypass the geocoding step and are the most reliable input for unknown or ambiguous locations.

• Run is taking longer than 150 seconds — This typically happens when several sub-actors are slow to respond from upstream APIs. Reducing the radius parameter decreases the result volume from USGS and GDACS, which are the heaviest queries. Setting includeClimate to false removes two additional calls.

• Infrastructure quality shows POOR for a known urban area — The infrastructure score depends on OSM POI density, which varies significantly by how completely the area has been mapped in OpenStreetMap. Dense, well-known cities are well-covered. Suburban, rural, or rapidly developing areas may be under-mapped, deflating the POI count and therefore the infrastructure score.

• Crime safety is 0 for a US location — Crime data is sourced exclusively from the UK police API, which only covers England and Wales. A score of 0 for crime in a non-UK location means no data is available, not that the location is crime-free. The composite score weights crime at 15%, so the absence of crime data reduces the composite score slightly compared to a UK location.

Responsible use

• This actor queries only publicly available government and open data sources. No private or proprietary data is accessed.
• FEMA, USGS, NOAA, EPA ECHO, and OpenAQ are US federal and public international data sources made freely available under government open data policies.
• UK Land Registry, UK police crime, and UK food hygiene data are published under the Open Government Licence.
• Risk scores are model outputs, not regulatory determinations. Do not use this actor's output as a substitute for a formal FEMA flood zone determination, licensed environmental site assessment, or official insurance risk rating.
• Comply with applicable data protection and fair use requirements when incorporating location risk data into lending, insurance, or employment decisions.
• For guidance on web scraping and API data use, see Apify's guide.

FAQ

How accurate is the location risk assessment for my specific property? The actor produces a risk signal based on publicly available data within the specified radius, not a formal property-level inspection. FEMA disaster history and USGS seismic data are highly accurate for the region; POI-based infrastructure scoring is directionally correct but depends on OpenStreetMap coverage quality. Treat scores as a screening tool and follow up high-scoring locations with authoritative sources.

Does location risk assessment work for addresses outside the United States? Yes, with reduced data depth. US locations benefit from FEMA, NOAA, USGS, and EPA ECHO data — typically 12–14 active sources. UK locations add crime, flood, land registry, and food hygiene data. International locations outside the US and UK typically get data from USGS earthquakes, GDACS disasters, OpenAQ air quality, OSM POIs, and EV charging — around 6–8 sources.

How many location risk reports can I run in one month on the free tier? Apify's free tier includes $5 of monthly platform credits. At approximately $0.50 per run, that is around 8–10 location risk assessments per month at no cost.

How is this different from a FEMA flood zone map or official risk rating? FEMA flood zone maps (SFHA determinations) are legal regulatory tools. This actor provides a multi-source risk signal drawing on FEMA disaster declarations, USGS seismic history, NOAA weather, EPA contamination, and more — it covers more dimensions than a flood zone map but is not a regulatory determination. Use it for screening and initial due diligence, not for flood insurance compliance.

Can I run location risk assessments on a list of 100 properties at once? The actor processes one location per run. To assess 100 properties, schedule 100 sequential or parallel runs via the Apify API. Use includeClimate: false to reduce cost per run when screening at volume.

How long does a typical location risk report run take? Between 60 and 150 seconds. The actor fires up to 14 sub-actor calls in parallel and waits up to 120 seconds for each. Most runs complete in 90–100 seconds. Disabling climate data (includeClimate: false) reduces this by 20–30 seconds.

What does the UNINSURABLE / EXTREME RISK grade mean? It means the composite weighted risk score reached 70 or above out of 100. This typically requires severe signals across multiple dimensions — for example, 20+ FEMA declarations, 5+ significant earthquakes, and 20+ EPA enforcement records all coinciding. The recommendation field provides the specific narrative: "Location presents extreme risk. Multiple hazard types, environmental contamination, or severe climate exposure. Decline coverage or apply maximum surcharges."

Is it legal to use government data from FEMA, USGS, and EPA for commercial purposes? Yes. FEMA, USGS, NOAA, and EPA ECHO data are published under US federal open data policies and are explicitly made available for public and commercial use. UK government data is published under the Open Government Licence. There are no legal restrictions on using this data for risk assessment, insurance, or real estate applications.

Can I schedule the actor to re-run monthly for properties I already have reports for? Yes. Use Apify's built-in scheduler to run the actor on a recurring interval. Store the historical scores in your own system to track risk trajectory over time. Rising scores in the hazard or climate dimensions may indicate increasing physical exposure.

Why does the crime safety score show 0 for my US location? Crime data is sourced from the UK police API, which covers England and Wales only. A score of 0 for a US location means no crime data was available from this source — not that the location is crime-free. The composite scoring accounts for this: missing crime data contributes 0 to the 15% crime weight, slightly reducing the composite score compared to a UK location with measured crime.

How is the infrastructure quality score different from the other risk dimensions? Infrastructure quality is the only dimension where a higher score is better, not worse. A score of 70 (EXCELLENT) means the area has dense amenities, strong EV charging infrastructure, high-quality food establishments, and good property values. This dimension is inverted before combining into the composite — so excellent infrastructure actively lowers the overall risk score.

Can I use the output with AI tools like ChatGPT or Claude for report generation? Yes. The structured JSON output is well-suited for LLM processing. Feed the report to an AI model with a prompt asking it to generate a narrative underwriting memo or executive briefing. The dimensions[*].findings arrays contain pre-written human-readable signals that can be incorporated directly.

Help us improve

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1. Go to Account Settings > Privacy
2. Enable Share runs with public Actor creators

This lets us see your run details when something goes wrong, so we can fix issues faster. Your data is only visible to the actor developer, not publicly.

Support

Found a bug or have a feature request? Open an issue in the Issues tab on this actor's page. For custom solutions or enterprise integrations, reach out through the Apify platform.