We extract carrier profiles, AM Best ratings, state-level premium averages, and coverage comparisons from Policygenius. Delivered as clean JSON, CSV, or Parquet to S3, BigQuery, or Snowflake on your cadence.
Structured, schema-consistent data across all major object types — delivered clean, typed, and ready to query.
Complete list of extractable fields for Carrier Profiles objects from policygenius.com. All fields typed and schema-versioned.
"carrier_id": "c_9482", "name": "Pacific Life", "insurance_types": "['Life']", "am_best_rating": "A+", "jdp_score": 812, "bbb_rating": "A+", "founded_year": 1868, "financial_strength": "Superior"
| # | carrier_id | name | insurance_types | am_best_rating | jdp_score | bbb_rating |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Average Premiums objects from policygenius.com. All fields typed and schema-versioned.
"state": "TX", "age_bracket": "35", "coverage_amount": 500000, "term_length": 20, "gender": "Female", "health_class": "Preferred Plus", "average_monthly_cost": 22.45, "insurance_type": "Term Life"
| # | state | age_bracket | coverage_amount | term_length | gender | health_class |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Carrier Reviews objects from policygenius.com. All fields typed and schema-versioned.
"review_id": "rev_39104", "carrier_name": "Progressive", "rating": 4.2, "review_date": "2026-02-14", "title": "Strong auto coverage options", "pros": "['Discount variety', 'App experience']", "cons": "['Customer service delays']", "verdict": "Good for drivers seeking digital first experience."
| # | review_id | carrier_name | rating | review_date | author | title |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Policy Features objects from policygenius.com. All fields typed and schema-versioned.
"carrier": "Brighthouse Financial", "policy_name": "SimplySelect", "min_coverage": 100000, "max_coverage": 2000000, "medical_exam_required": false, "issue_age_min": 25, "issue_age_max": 50, "convertibility": true
| # | carrier | policy_name | min_coverage | max_coverage | rider_options | medical_exam_required |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Coverage Guides objects from policygenius.com. All fields typed and schema-versioned.
"category": "Auto Insurance", "state": "FL", "average_cost": 2415, "legal_requirements": "['10k PIP', '10k PDL']", "recommended_coverage": "100/300/100", "common_perils": "['Hurricanes', 'Floods']", "discount_types": "['Safe driver', 'Multi-policy']", "last_updated": "2026-03-01"
| # | category | state | average_cost | legal_requirements | recommended_coverage | common_perils |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Our Policygenius scraper extracts structured carrier intelligence, state level premium averages, and policy comparison matrices. We handle the JavaScript rendering and anti-bot systems automatically.
Extract deep carrier profiles including AM Best ratings, NAIC complaint indices, financial strength grades, and founding history.
Capture average premium costs segmented by state, age, gender, coverage amount, and health classification.
Extract minimum and maximum coverage limits, rider availability, medical exam requirements, and issue age restrictions.
Scrape Policygenius editorial verdicts, pros and cons, and aggregated user ratings for major insurance providers.
Extract state minimum requirements, recommended coverage levels, and average costs across major auto carriers.
Capture peril coverage details, exclusion lists, and discount opportunities for property insurance lines.
Extract term length options, convertibility rules, and elimination period matrices for life and disability policies.
Scrape reimbursement percentages, annual limits, deductible options, and breed specific cost averages.
Run pipelines monthly or quarterly to track shifts in carrier ratings, premium averages, and editorial verdicts.
Brief in. Clean data out.
Specify insurance categories, states, or specific carriers. We design the extraction schema together.
We configure Scrapy and Playwright crawlers, proxy rotation, and session management for policygenius.com.
Schema validation, null-rate checks, and data normalisation before full launch.
JSON, CSV, or Parquet pushed to your S3 bucket, BigQuery dataset, or Snowflake stage on agreed cadence.
Modern financial aggregators use strict bot mitigation. Here is how we maintain reliable extraction.
Financial aggregators block datacentre IPs aggressively. Our crawlers use US residential ISP proxies with realistic browser fingerprints and randomised request timing to avoid triggering Cloudflare or DataDome blocks.
Many rate tables and carrier comparison grids are rendered client side. We run full Playwright browser sessions to hydrate dynamic components before extracting the DOM.
Policygenius updates its layout frequently for compliance and marketing reasons. We use multiple fallback chains per field, relying on structured data and predictable DOM patterns rather than brittle CSS classes.
We normalise financial ratings, state codes, and coverage amounts into strict types, ensuring your warehouse receives clean integers and standard ISO strings rather than messy text blocks.
Every run emits structured logs. We alert on null-rate spikes or missing carrier pages, adjusting selectors before they impact your downstream analytics.
Insurance carriers monitor competitor ratings, coverage limits, and editorial verdicts to position their own products.
Actuaries and pricing teams extract state-level premium averages to benchmark their own rate filings against market consensus.
Agencies track AM Best, J.D. Power, and NAIC complaint indices across the market to advise their clients.
Insurtech startups analyse existing policy features, rider options, and exclusions to design competitive new coverage products.
Financial publishers use aggregated carrier data and state averages to enrich their own comparison tools and editorial content.
Private equity and hedge funds track carrier visibility and consumer sentiment trends on major aggregators to inform investment theses.
"Policygenius aggregates the clearest baseline of insurance carrier ratings and average premium data available on the public web."
Extracting this data reliably requires navigating strict bot protection and heavy client-side rendering. DataFlirt manages the infrastructure, proxy rotation, and schema maintenance so your analysts can focus on actuarial research and market positioning rather than fixing broken web scrapers.
Everything supported by our policygenius.com scraper — rendered SPA elements, auth walls, rate-limit evasion and beyond.
Open-source tooling on proven cloud infra — no vendor lock-in, full observability.
Scrapy handles crawl orchestration and deduplication. Playwright handles JavaScript rendering and interaction flows for dynamic rate tables.
We maintain pools of US residential ISP proxies. Rotation happens per request to prevent IP bans from financial aggregator security systems.
Pipelines run on AWS Lambda and ECS. Airflow handles scheduling and dependency management. All state is stored in managed Postgres.
Data delivered to where your team already works — no new tooling required.
About policygenius.com scraping, legality, and pipeline operations.
Ask us directly →Scraping publicly available information is generally permissible. DataFlirt targets only public, non-authenticated carrier data, editorial reviews, and aggregate rate matrices. We do not extract PII or circumvent authentication walls. Clients should review terms of service and consult legal counsel.
No. Exact quotes on Policygenius require submitting Personally Identifiable Information (PII) such as Social Security Numbers, exact health histories, or driving records. We only extract the publicly available average rate matrices and baseline estimates.
We use US residential ISP proxies, full Playwright browser sessions with realistic fingerprints, and request timing modelled on human behaviour to avoid triggering Cloudflare blocks.
Insurance rates and carrier ratings change slowly. Most clients configure pipelines to run monthly or quarterly to capture updates to AM Best ratings, state averages, and editorial reviews.
Yes. We standardise AM Best, Standard & Poor's, and Moody's ratings into consistent string formats, and convert numerical scores like J.D. Power indices into clean integers.
Yes. We provide a sample run covering a subset of carriers or specific insurance lines during the scoping process, allowing you to validate the schema before committing.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need a one-off export of carrier profiles or a quarterly feed of state-level premium averages, we build and operate the pipeline. Tell us what you need.
