PhoneLookup
Trust

Methodology

This page documents exactly how PhoneLookup turns a raw phone number into the country, carrier, line-type, timezone, spam signals and community context you see on a number page.

1. Number parsing

We parse every number with Google’s libphonenumber, the same library used inside Android and by most major carriers. From the E.164 form we derive:

  • Country and region (ISO 3166-1 alpha-2)
  • National significant number and formatted national / international display
  • Line type (mobile, fixed-line, VoIP, toll-free, premium, shared-cost, pager, UAN)
  • Original carrier at the time of allocation (where the mapping is public)
  • Primary timezone(s) served by the numbering block

We do not perform an HLR/live-network lookup and do not claim to know the current subscriber, current carrier after porting, or physical location of the handset.

2. Spam & risk signals

A number’s risk indicator is a transparent composite — not a black-box AI score — built from the following signals, each of which is separately visible on the number page:

  1. Report volume: total community reports, log-scaled to avoid new-number bias.
  2. Report recency: reports in the last 30 / 90 / 365 days weighted higher.
  3. Report agreement: the share of reports that agree on a category (e.g. “bank fraud”).
  4. Search velocity: unique lookups over the last 7 days.
  5. Range signals: known spam density of the parent numbering block.
  6. Regulator lists: presence on public advisories from I4C, TRAI, FTC, Ofcom, ACMA where applicable.

We ignore single-reporter reports until at least one independent report agrees, and we rate-limit reports per IP + per number to reduce brigading and reputation attacks.

3. Category assignment

Category pages (Bank Fraud, WhatsApp Scam, Delivery Scam, Loan Scam, Job Scam, etc.) are assigned when at least three independent reports agree on the same category and the number is not on a regulator whitelist. Categories are re-evaluated nightly — a number can move in or out of a category as new reports arrive.

4. What we never do

  • We never display the name, address, email, Aadhaar / PAN / SSN or any KYC data of a private individual.
  • We never sell personal data. We do not run people-search products.
  • We never accept payment to remove a legitimate report or to whitelist a number that has genuine community complaints.
  • We never fabricate reports. Reports come only from real submissions through the site.

5. Business & official numbers

A business, government agency or bank whose real customer-service number is being mistagged can request a review through the contact form. If we verify the number is genuinely operated by the claimed organisation (via a listing on the organisation’s own official website), we add a verified-owner banner to the page.

6. Transparency & changes

Any material change to this methodology — new signals, new weightings, changed thresholds — is logged on the Corrections page with the date of the change.