Why publish our numbers?
Industry trackers estimate robocall volume from carrier honeypots and third-party modelling. FilterMyCalls does something different: our AI answers every unknown call, asks the caller to state who they are and why they are calling, and hands that answer to the subscriber to decide. That means our data captures not only how many calls arrive — but what callers actually say when a machine politely questions them.
We publish these figures openly because callers are a shared problem: the more of us who screen, question, and report, the harder it becomes for scam operations to reach anyone at all.
Methodology
- Every count comes from production screening records in FilterMyCalls infrastructure — never from panels, polls, or estimates.
- Counts are aggregate and anonymized. No phone numbers, names, or transcripts are published.
- Data is refreshed weekly by an automated pipeline; the date above shows the latest refresh.
- Our system cannot catch every unwanted call, and caller statements are claims, not verified facts — the Index reports what is heard, not what is true.
What we are seeing in 2026
Two patterns dominate the screening sessions we observe: automation — robocalls that never answer the AI, confirming they are machines — and impersonation, where the caller claims to represent a bank, a government office, or a delivery service. As voice-cloning tools spread, the impersonation pattern is the one to watch: synthetic voices can imitate a real person convincingly, which is why FilterMyCalls is building verified-reason screening — checking not just what the caller says, but whether the voice and the network behind it are what they claim to be.
Read how verified-reason screening works →
For journalists and researchers
We can provide anonymized trend commentary and data for stories about spam, scam, and AI-voice calls in North America. Reach us at support@filtermycalls.com or 1-888-312-3688 (24/7). Our press kit has background and assets.