Full Breakdown
Congress Probe Uncovers $100,000 Romance Scam on Dating Apps
By Drooid · · How we work
Core Event
In 2024, Mary—who asked that her last name be withheld—met a man on the dating app Plenty of Fish. Over weeks of constant contact, the fraudster pressured her into sending roughly $100,000 in cryptocurrency. After blocking his number, he returned with a new phone number, and Mary later discovered other profiles using the same photos. Her experience became part of a joint investigation by the Senate Joint Economic Committee, led by Senators Maggie Hassan (D-NH) and Marsha Blackburn (R-TN), into romance scams on platforms owned by Match Group.
Background & Context
Romance scams have risen to become a leading form of financial fraud in the United States, with the committee noting they cost Americans at least $1.3 billion annually. The inquiry, launched in September 2025, examined whether Match Group’s safety tools kept pace with evolving threats, especially as criminal networks begin to employ artificial intelligence.
Data & Statistics
- The report found that, as of the second half of 2025, Tinder had not updated most of its machine-learning models for years, reducing its ability to detect scammers.
Official Statements & Responses
- Senator Blackburn echoed the need for stronger safeguards, urging Match Group to act faster.
- He added that facial-verification and new AI models were already underway before the investigation.
Verbatim Quotes
- “There was a lot of conversation, and then it started with the constant contact, pressure and repeated asks for money,” — Mary
- “If you knew me, you would say she would never do that,” — Mary
What’s Next
In June 2026, Senators Hassan and Rick Scott (R-FL) introduced legislation to create a central portal for Americans to report scams and receive assistance from law-enforcement agencies. The committee’s report also notes that Match Group has rolled out a video selfie verification for all new Tinder users in the United States and deployed a new AI model in early 2025 to flag fraudulent profiles.
