We extract modular insurance quotes, extreme sports riders, and destination-based pricing matrices from Battleface. 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 Quote Pricing objects from battleface.com. All fields typed and schema-versioned.
"quote_id": "BF-9921-A", "destination_country": "Japan", "origin_country": "UK", "traveler_age": 34, "trip_duration_days": 14, "base_premium": 45.5, "total_premium": 82.0, "currency": "GBP"
| # | quote_id | destination_country | origin_country | traveler_age | trip_duration_days | base_premium |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Modular Coverage objects from battleface.com. All fields typed and schema-versioned.
"module_name": "Baggage Delay", "coverage_limit": 2500.0, "deductible": 50.0, "premium_impact": 12.5, "is_mandatory": false, "waiting_period_hours": 12
| # | module_name | coverage_limit | deductible | premium_impact | is_mandatory | waiting_period_hours |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Activity Riders objects from battleface.com. All fields typed and schema-versioned.
"activity_name": "Scuba Diving", "risk_category": "Water Sports", "requires_rider": true, "rider_premium": 28.0, "max_depth_meters": 30, "excluded_regions": "['Polar']"
| # | activity_name | risk_category | requires_rider | rider_premium | max_altitude_meters | max_depth_meters |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Destination Intelligence objects from battleface.com. All fields typed and schema-versioned.
"country_code": "JP", "country_name": "Japan", "risk_tier": 1, "fco_advice_status": "Green", "medical_multiplier": 1.2, "evacuation_required": false
| # | country_code | country_name | risk_tier | fco_advice_status | medical_multiplier | evacuation_required |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Policy Terms objects from battleface.com. All fields typed and schema-versioned.
"policy_version": "v2025.1", "effective_date": "2025-01-01", "underwriter": "Spinnaker Insurance", "governing_law": "UK", "claim_filing_window_days": 30, "emergency_contact_number": "+44 20 3322 1100"
| # | policy_version | effective_date | underwriter | governing_law | cancellation_terms | claim_filing_window_days |
|---|---|---|---|---|---|---|
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Our Battleface scraper automates multi-step quote forms, fuzzes pricing parameters, and intercepts underlying API responses to build complete premium matrices across all traveler demographics.
Submit permutations of age, destination, and duration to extract exact premium matrices across all traveler profiles.
Capture pricing impacts for adding or removing baggage, cancellation, and medical modules.
Map the specific premium add-ons for high-risk activities like mountaineering, scuba diving, and winter sports.
Track how Battleface categorises country risk and applies geographical pricing multipliers.
Extract the inverse relationship between chosen deductible amounts and final policy premiums.
Identify the backing insurance entities per region and policy type.
Extract structured data from policy wording regarding pre-existing conditions and excluded events.
Capture quotes in GBP, USD, EUR, and AUD based on the origin country parameters.
Maintain stateful sessions to progress through multi-step quote forms without triggering rate limits.
Brief in. Clean data out.
Provide origin-destination pairs, traveler demographics, and trip durations. We design the extraction schema together.
We configure Playwright crawlers, manage form states, and handle session tokens for battleface.com.
Schema validation, null-rate checks, premium-outlier detection, and quote sample verification before full launch.
JSON / CSV / Parquet pushed to your S3 bucket, BigQuery dataset, or Snowflake stage on agreed cadence.
Insurance quote engines use session validation and rate limiting to prevent automated benchmarking. Here is how we maintain data flow.
Battleface quotes require sequential form submissions. We use Playwright to manage complex state transitions and capture the final pricing payload.
Instead of parsing HTML, we intercept the underlying GraphQL/REST responses during the quote generation process to extract clean, structured pricing arrays.
Quote APIs require valid CSRF tokens and session cookies. Our infrastructure maintains active session pools to execute parallel quote requests.
Generating thousands of quotes triggers volumetric blocks. We distribute requests across residential ISP proxies to maintain a low profile.
To build complete pricing matrices, we systematically fuzz input parameters (age 18-99, durations 1-365 days) ensuring exhaustive coverage.
Travel insurance aggregators monitor Battleface premiums against market averages to optimise their own pricing engines.
Insurtech analysts extract destination-specific pricing multipliers to reverse-engineer risk models.
Underwriters identify underserved niches by analysing Battleface's modular coverage offerings and activity riders.
New travel insurance entrants study age and duration pricing curves to structure competitive base premiums.
Brokers adjust their commission structures based on real-time shifts in Battleface's base rates.
Compliance teams track changes in terms, conditions, and exclusions across policy versions.
"Travel insurance pricing is highly dynamic. Without systematic extraction of quote permutations, understanding a competitor's risk model is impossible."
Most teams underestimate the investment required: reliable quote extraction requires managing multi-step forms, handling session tokens, intercepting API payloads, and executing thousands of parameter permutations. DataFlirt absorbs that complexity so your actuaries can focus on the analysis — not the infrastructure.
Everything supported by our battleface.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.
Playwright handles the complex multi-step quote flows, maintaining session cookies and CSRF tokens across the funnel.
We bypass DOM parsing by intercepting the raw JSON payloads returned by Battleface's internal pricing APIs during quote generation.
Airflow distributes millions of parameter permutations across AWS Lambda workers to build complete pricing matrices in hours.
Data delivered to where your team already works — no new tooling required.
About battleface.com scraping, legality, and pipeline operations.
Ask us directly →Scraping public, non-authenticated quote forms is generally permissible. We do not use PII, complete purchases, or bypass authentication walls. DataFlirt extracts only publicly available pricing logic.
We use Playwright to simulate user journeys, sequentially inputting destination, dates, and ages, while intercepting the final pricing payload from the network layer.
Yes. We can automate the selection of specific activity riders (e.g., winter sports, scuba diving) to isolate the premium impact of each activity.
We systematically fuzz the input parameters. If you need rates for ages 18-65 across 50 destinations for 7, 14, and 21-day trips, our orchestrator generates and executes all permutations.
Yes. We extract the links to policy documents and parse the structured text regarding pre-existing conditions and regional exclusions.
Pipelines can be configured to run daily or weekly. A full parameter sweep of 100,000 quote permutations typically completes within 4-6 hours.
20-minute scoping call. Pilot dataset within the week. Production within two. From single-destination trackers to global actuarial matrices, we build and maintain the infrastructure. Define your parameters today.
