We extract premium calculations, coverage limits, network hospital lists, and claim settlement ratios from Policybazaar. 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 Health Insurance Quotes objects from policybazaar.com. All fields typed and schema-versioned.
"insurer_name": "Star Health", "plan_name": "Comprehensive Insurance", "sum_insured": 1000000, "annual_premium": 14592.0, "network_hospitals_count": 8400, "claim_settlement_ratio": 99.1
| # | insurer_name | plan_name | sum_insured | monthly_premium | annual_premium | network_hospitals_count |
|---|---|---|---|---|---|---|
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Complete list of extractable fields for Term Life Quotes objects from policybazaar.com. All fields typed and schema-versioned.
"insurer_name": "Max Life", "plan_name": "Smart Secure Plus", "life_cover_amount": 10000000, "cover_upto_age": 70, "annual_premium": 11240.0, "claim_settlement_ratio": 99.5
| # | insurer_name | plan_name | life_cover_amount | cover_upto_age | monthly_premium | annual_premium |
|---|---|---|---|---|---|---|
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Complete list of extractable fields for Motor Insurance Rates objects from policybazaar.com. All fields typed and schema-versioned.
"vehicle_make": "Hyundai", "vehicle_model": "Creta", "idv_amount": 850000, "comprehensive_premium": 18450.0, "zero_dep_cover": true, "ncb_discount": 20
| # | vehicle_make | vehicle_model | registration_year | rto_code | insurer_name | idv_amount |
|---|---|---|---|---|---|---|
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Complete list of extractable fields for Network Hospitals objects from policybazaar.com. All fields typed and schema-versioned.
"insurer_name": "HDFC ERGO", "hospital_name": "Apollo Hospitals", "city": "Bengaluru", "pincode": "560076", "cashless_facility": true, "accreditation": "NABH"
| # | insurer_name | hospital_name | hospital_type | address | city | state |
|---|---|---|---|---|---|---|
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Complete list of extractable fields for Insurer Metrics & CSR objects from policybazaar.com. All fields typed and schema-versioned.
"insurer_name": "ICICI Lombard", "category": "General", "claim_settlement_ratio": 97.8, "average_settlement_days": 14, "solvency_ratio": 2.5, "market_share_pct": 8.4
| # | insurer_id | insurer_name | category | claim_settlement_ratio | claims_paid_count | total_claims_received |
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Our Policybazaar scraper handles the complexity of insurance aggregators: multi-step lead forms, asynchronous API payloads, session token injection, and schema normalisation across dozens of insurers.
Extract premiums dynamically calculated based on age, gender, lifestyle inputs, and geographic location.
Capture historical and current CSR data published across all major life and general insurers.
Scrape city-wise cashless hospital directories for health insurance providers, including specialty and accreditation details.
Extract granular costs for zero-depreciation, accidental death, critical illness, and waiver of premium riders.
Extract structured text regarding pre-existing conditions, maternity waiting periods, and specific disease exclusions.
Automate complex multi-step lead forms required to generate accurate quote grids.
Download and extract tabular data from policy wording and brochure PDFs into structured formats.
Capture age-based co-payment percentages, deductible tiers, and room rent capping rules per plan.
Support for Term, Health, Motor, Travel, and Corporate insurance funnels via a unified API.
Track competitor pricing adjustments, promotional discounts, and regulatory price hikes at hourly cadences.
Brief in. Clean data out.
Provide insurance categories, target demographics, and required coverage parameters. We design the schema together.
We configure Playwright crawlers, proxy rotation, and form automation to bypass quote generation walls.
Schema validation, null-rate checks, and premium outlier detection before full launch.
JSON / CSV / Parquet pushed to your S3 bucket, BigQuery dataset, or Snowflake stage on agreed cadence.
Insurance aggregators gate data behind complex forms and session tokens. Here is how we extract quotes reliably.
Quote generation requires multi-step form submissions with valid Indian phone numbers and OTP verification. We manage session tokens and inject pre-verified session cookies to access the quote grid without manual intervention.
Policybazaar fetches quotes via asynchronous API calls after form submission. We intercept XHR and Fetch requests directly to capture raw JSON payloads, bypassing fragile DOM scraping entirely.
Aggregators block datacenter IPs aggressively to prevent competitor scraping. We route requests through residential Indian ISP proxies to mimic genuine consumer traffic and avoid geographic restrictions.
Every insurer formats policy features differently. We normalise room rent limits, waiting periods, and CSR percentages into a strictly typed schema, ready for actuary models.
High-velocity quote requests trigger Cloudflare and custom bot challenges. We integrate CapSolver and 2Captcha for automated token generation and challenge clearance without dropping requests.
Insurance underwriters monitor competitor premiums across specific age and geographic cohorts to optimise their own pricing models.
Actuaries analyse rider availability and waiting periods to design new insurance products that fill market gaps.
Healthcare consultants map cashless hospital networks to identify coverage density and negotiate better TPA contracts.
Analysts track claim settlement ratios and grievance metrics to evaluate insurer reliability and operational health.
Independent insurance brokers use aggregated quote data to build custom comparison tools for their high-net-worth clients.
Compliance teams audit aggregator displays to ensure mandated disclosures and accurate premium representations.
"Policybazaar holds the most comprehensive pricing matrix in the Indian insurance sector, but extracting it requires navigating complex form state and session walls."
Most engineering teams fail at insurance scraping because they treat it like a static catalogue. Extracting quotes requires managing multi-step lead forms, intercepting asynchronous API payloads, and handling strict rate limits. DataFlirt absorbs this complexity. We manage the proxies, the form state, and the schema normalisation, delivering clean premium data directly to your warehouse.
Everything supported by our policybazaar.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.
We use Playwright to navigate complex multi-step lead forms, handle OTP modals via session injection, and trigger the asynchronous quote generation process.
Instead of scraping the DOM, our crawlers intercept the raw JSON payloads returned by backend APIs, ensuring perfect data fidelity for premium calculations.
Pipelines run on Kubernetes with Airflow handling scheduling and dependency management. All state and session tokens are stored in managed Redis.
Data delivered to where your team already works — no new tooling required.
About policybazaar.com scraping, legality, and pipeline operations.
Ask us directly →Scraping publicly accessible quote data is generally permissible for market research. We do not extract personally identifiable information (PII) of actual users or bypass authenticated user accounts. Clients should consult legal counsel regarding their specific use cases.
We utilise session injection and maintain pools of verified session tokens to access the quote grid without triggering new OTP requests for every crawl.
Yes. You define the matrix of parameters (age, gender, smoking status, pre-existing conditions) and we programmatically generate quotes for every combination.
We support Term Life, Health, Motor (Car and Two-Wheeler), Travel, and Corporate insurance funnels available on the platform.
We extract structured text from the policy details section and apply NLP models to normalise waiting periods, sub-limits, and standard exclusions into queryable fields.
Pipelines can be configured for daily or weekly runs depending on the size of your parameter matrix. Insurer price changes are detected and pushed in the next scheduled run.
We capture the current CSR published on the platform. Historical time-series data is built from the day your pipeline is commissioned.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need a daily premium benchmark across 10,000 demographic profiles or a complete network hospital catalogue, we build and operate the pipeline. Tell us what you need.
