(272) 202-7300
This number is considered as spam
Is this number a spammer?
Key Details About (272) 202-7300
Phone number (272) 202-7300 is registered in Pennsylvania, United States. This landline number was assigned in 2017 by the North American Numbering Plan Administration (NANPA). The area code 272 serves northeastern Pennsylvania, including Scranton, Wilkes-Barre, and surrounding areas. The carrier for this number is Verizon Communications. This number can be used for both personal and business purposes. The prefix 202 indicates it's located in the Scranton metropolitan area. The number is active and currently in service. Call patterns suggest regular usage during business hours. If you need more information, a detailed background search may provide further insights into its usage and history. For additional details, including the owner's full name, address, email, and job information, purchase the full report.
PhoneChecker AI Spam Detector Insights*
The phone number (272) 202-7300 has been thoroughly analyzed using PhoneChecker AI’s advanced spam detection algorithms. Our system evaluates various data sources, including user feedback, call patterns, carrier information, and historical usage trends, to assess the likelihood of the number being legitimate or linked to spam activities.
Is This Phone Number Safe ?
Based on user analysis, phone number (272) 202-7300 has been reported multiple times for making unsolicited calls offering fake insurance deals and credit card services.
Reasons for Flagging
The phone number (272) 202-7300 has been flagged as spam due to several detection signals that indicate potential unwanted or fraudulent activity. Users have reported receiving unsolicited calls from this number, which raises concerns about its legitimacy. Additionally, the call frequency appears abnormal, suggesting a pattern often associated with spam. This number may also be listed on third-party blacklists, further corroborating its classification. Lastly, there are indications of caller-ID spoofing, a common tactic used by spammers to disguise their true identity.
Possible Call Sources
Possible Call Sources for the number 272-202-7300 may include various entities that engage in high-volume calling practices. These sources could be involved in promoting products or services, collecting debts, or attempting to obtain personal information under false pretenses. The frequency of calls from this number suggests it may be linked to operations that prioritize outreach over compliance with regulations.
• Mass-market telemarketing vendors
• Automated robocalling services (“voice broadcasting”)
• Debt-collection firms or their subcontractors
• Phishing or tech-support scam operations
• Lead-generation agencies reselling data
Recommended Actions — How to Deal With Spam Calls
Here are 6 key steps to follow if you receive a call from a suspected spam number:
1. Don’t Answer Unknown Numbers
If you receive a call from a number you don’t recognize, let it go to voicemail. Many spam callers rely on you answering to confirm your number is active.
2. Block the Number
Immediately block the number on your phone to prevent future calls. Both iOS and Android phones offer easy options to block and report numbers.
3. Don’t Share Personal Information
Never provide personal or financial information to unknown callers. Legitimate companies will not pressure you into sharing sensitive data over the phone.
4. Report and Mark the Number on WhoCalledMeUS
Help others stay safe by marking the number as spam on WhoCalledMeUS. This will alert the community and improve the accuracy of the PhoneChecker AI Spam Detector.
5. Use Call-Blocking Apps
Install trusted apps to automatically detect and block spam and robocalls.
6. Enable Spam Protection on Your Device
Most smartphones and carriers offer built-in spam filtering tools—enable these features to automatically silence or block suspicious calls.
These simple actions can significantly reduce spam call risks and protect your personal information.
*Our AI spam detection system scans and analyzes data from various sources across the internet to identify whether a specific number is associated with spam activities. It then summarizes the results, providing insights into the potential risk of spam related to that number.
This AI-powered tool monitors patterns in online data and uses machine learning algorithms to detect associations with spam or malicious activities. By doing so, it helps users identify numbers that may be involved in spam, helping prevent unwanted communication.
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