Proxies for Insurance Quote Aggregation and Comparison Sites

Match what you are building to the line that fits, then read only the sections that matter to you.

The last row is the one that saves money. Teams routinely spend a quarter building a quote-funnel scraper before discovering the output is unusable for the product they are shipping.

Insurance data is not one target. It is four, and they have different block rates, different legal profiles and different correct answers.

Layers A and B carry most of the analytic value and almost none of the risk. That is an unusual shape for a data collection project, and it should change what you buy. A team that only needs A and B is a Starter-plan customer with money left over, not a six-figure residential-bandwidth customer.

In the United States, property and casualty rates are filed with state regulators before use. The System for Electronic Rate and Form Filing, operated by the National Association of Insurance Commissioners, is the pipe those filings travel through, and many states expose a public filing access view of it. California adds its own layer: under Proposition 103, most personal lines rates need prior approval, and the filing record, including intervenor participation, is public.

A rate filing frequently contains what a quote funnel will never hand you: the base rate, the class plan, territory definitions and the relativity factors applied to each rating variable. That is the rating algorithm, not one sampled output of it. With filings you can compute a premium for any hypothetical risk, offline, forever. With a scraped funnel you get one premium for one fabricated applicant, and you get it once.

Two honest caveats. Not every state publishes every filing, and some jurisdictions let carriers mark supporting exhibits confidential or trade secret, so coverage is uneven. And filings are effective-dated, so a series without the effective date attached to every row is worthless for trend work. The same discipline that applies to financial data collection applies here: store observation time and effective time as separate fields, always.

One structural detail breaks most first attempts. The unit of collection is not the carrier. A group writes through several licensed companies, often a preferred, a standard and a non-standard company, and each files its own rates in each state for each line. Your primary key is company, state, line and effective date, not the brand on the television advertisement. Get that wrong and your national average is an average of a naming convention.

This is the most expensive misconception in the category. Rating territory is determined by the garaging or property address you submit in the form, not by the geolocation of your egress IP. Nobody prices a policy off your exit node.

What the IP actually controls is narrower:

• Whether the site serves you a US experience at all, or a country splash page.
• Which state landing page or agent locator you get by default before you enter an address.
• Your bot score, since a request from an unexpected country to a state-licensed carrier is anomalous on its face.
• Availability of the funnel, since some carriers geofence entire regions.

So the requirement is a healthy pool of US IPs with clean reputation, plus correct address inputs, plus enough distinct IPs that no single one carries your whole crawl. It is not one IP per postal code. If you want the mechanics of what proxy geo-targeting does and does not control, this breakdown covers it. SparkProxy runs over 1,000,000 datacenter IPs across 80 or more countries, with 50,000 or more in the US alone, which is well past the point where per-ZIP thinking adds anything.

Reach for residential only when a specific target has demonstrably blocked datacenter address space and the data is worth the multiple. The datacenter and residential trade-off is really a trade of price predictability against ASN diversity, and for layers A and B that diversity buys you very little.

Concurrency, not IP count, is what you actually purchase on a thread-priced plan. The formula is unglamorous and correct:

threads = (pages per cycle x average seconds per request) / window in seconds

Then multiply by 1.4 to 1.5 for retries, slow tails, and the fact that your window is never really the full window.

Now the check almost nobody runs. Unlimited bandwidth still has a speed ceiling, and the ceiling binds before the data cap does. That middle row at roughly 250 KB per rendered page is about 75 GB per cycle. Spread across eight hours that is roughly 21 Mbps sustained, which sits right against a 25 Mbps plan ceiling. Size on average megabits per second, not on total gigabytes, or your nightly job quietly runs long. How concurrency behaves under load is covered in this piece on concurrent connections.

Put numbers on it. That 75 GB rendered cycle costs nothing extra on an unlimited-bandwidth thread plan. Priced per gigabyte it is a different conversation: published list prices on major residential vendors' own pricing pages, as of September 2026, mostly sit in the low single digits of dollars per gigabyte at entry tiers and fall with volume commitment, so the same cycle lands somewhere in the hundreds of dollars. Those pages get revised often, so check the vendor's current pricing page rather than trusting any figure in an article, including this one. Read the shape of datacenter proxy pricing models before you compare quotes across vendors, because the units are not the same units.

All four published plans include unlimited bandwidth and 30 days of validity. Threads are the variable.

Map that to the sizing table above. A filings and product-page tracker needs Starter. The 300,000 page rendered nightly fits Starter on threads but sits close to its speed ceiling, so Core is the honest recommendation. The national daily refresh at 389 threads needs Boost. Higher tiers exist in the fair usage policy above Plus, and they are quoted rather than listed. Treat every speed figure as a ceiling, not a promised rate.

Connection is through one gateway host on three ports, chosen by what the job needs:

# Rotating HTTP/HTTPS, a fresh IP per request, for filing index sweeps
curl -x http://USER:PASS@gateway.sparkproxy.io:11000 \
     "https://filing-portal.example/search?state=TX"

# Sticky session, same IP held across a multi-step public flow
curl -x http://USER:PASS@gateway.sparkproxy.io:11002 \
     "https://filing-portal.example/document/12345"

# SOCKS5 for tooling that expects it
curl --socks5-hostname USER:PASS@gateway.sparkproxy.io:13000 \
     "https://filing-portal.example/"

Port 11002 matters more here than in most verticals. Filing portals are frequently multi-step, with a search, a result list and a document viewer that all expect the same session. Rotating mid-flow drops you back to the search form with an expired token. If sticky behaviour is new to you, this explainer covers when to hold an IP and for how long.

If you would rather not run headless browsers, the Scraping API bills per credit: 1 credit for a plain fetch, 5 for a JavaScript render, 10 for a screenshot or PDF. Growth at $99 is 1,000,000 credits with 100 concurrent requests, which is 1,000,000 plain fetches or 200,000 rendered pages a month. There are 1,000 free credits with no card, enough to run the test in the next section properly. The API versus self-managed proxies decision comes down to whether rendering and retries are your problem or someone else's.

# Rendered comparison page, US egress, via the Scraping API
curl -G "https://scrape.sparkproxy.io/api/v1" \
  -H "X-API-Key: YOUR_API_KEY" \
  --data-urlencode "url=https://aggregator.example/auto/tx" \
  --data-urlencode "render_js=true" \
  --data-urlencode "country_code=US"

Insurance is a regulated industry, and the review is more serious than in retail. Have answers ready for these:

• Is the source public and unauthenticated? Regulatory filings and carrier marketing pages generally are. An agent portal is not. Under hiQ Labs v. LinkedIn (9th Cir. 2022), collecting data open to the public does not run into the Computer Fraud and Abuse Act's authorization gate, which Van Buren v. United States (2021) had already read narrowly. Neither case blesses breaking a contract you signed, and neither of these paragraphs is legal advice.
• Are you submitting anything into a funnel? Entering fabricated applicant details into a quote flow is a different act from reading a page. Depending on the state it can implicate insurance misrepresentation provisions, and it can trigger real consumer report or motor vehicle record pulls against invented or borrowed identities. Motor vehicle records are federally restricted by the Driver's Privacy Protection Act, 18 U.S.C. 2721.
• Does anything you store touch personal data? Gramm-Leach-Bliley Title V and the state insurance data security laws modelled on the NAIC Insurance Data Security Model Law govern nonpublic personal information. Filing data does not contain it. Quote outputs tied to a real consumer do.
• Are you using credit-based scores or their proxies? Those sit in Fair Credit Reporting Act territory, and several states, including California, Hawaii and Massachusetts, prohibit credit-based insurance scores in personal auto rating. A model trained on national data will be wrong in those states.
• Operating in the UK or EU? The Financial Conduct Authority's general insurance pricing remedy, in force since 1 January 2022, bans charging a renewing customer more than an equivalent new customer, which changes what a renewal price observation even means. Distribution sits under the Insurance Distribution Directive, (EU) 2016/97.
• Can you prove who ran what? Whitelisted IP authentication gives you attribution by source host, and SparkProxy plans carry 5 to 25 whitelist slots depending on tier. Separate credentials per environment beat one shared account when an auditor asks.

Rate-limit yourself below what the target tolerates, honour published crawl guidance, and keep the collection defensible. The practices in ethical scraping and rate limiting are what a procurement questionnaire is really probing for.

Vendor benchmark pages are marketing. Run your own, on your own targets, before the card comes out.

1. Pick 20 real URLs across five jurisdictions: two filing portals, ten carrier pages, eight comparison pages. Include at least one PDF.
2. Send 200 requests through the trial and record the non-2xx rate, median time to first byte, and the 95th percentile. The tail is what breaks your window, not the median.
3. Re-run at your actual planned concurrency. A pool that looks perfect at 5 threads can fall apart at 80, and 80 is the number you are buying.
4. Repeat once at 03:00 in the target's local time. Overnight behaviour on regulator infrastructure differs from midday behaviour.
5. Confirm the state distribution of your egress IPs if any target geofences by region.
6. Get the replacement and refund terms in writing before renewal, not after a bad night.

Score the result on success rate at your concurrency and on cost per successful page, not on advertised pool size. Pool size is the least predictive number on any proxy pricing page. For an adjacent buying pattern in a similar structured-listing market, price comparison site collection is the closest neighbour to this workload.