Earlier in October, U.S. lawmakers revealed how users of dating apps were being exposed to serious financial and physical risks. They pinned this to the outdated AI stack in these applications.
In an investigation centred around the Match Group, the lawmakers found that the algorithm matched U.S. users of dating apps like Tinder and Hinge with scammers. The report, titled ‘Outmatched: Tinder, Scammers, and Match Group’s Efforts to Catch Up’, highlighted that users connected with nearly 1.5 million scammers on these two popular dating applications in the first nine months of 2025.
At the core of these disturbing findings were outdated machine learning models installed to detect bad actors. These hadn’t been updated in years, per the report.
This information came from internal documents that the Match Group shared with the committee, led by senator Maggie Hassan. As the accuracy of scam detection dropped, Tinder began depending on other measures that it knew were often ineffective.
“In fact, Match Group knew that Tinder was more likely to show a profile if it belonged to a scammer or other bad actor rather than a regular user,” stated an official press release about the report.
However, the investigation acknowledged that the Match Group later put in place new safety measures, such as an AI model in Tinder this year that was designed to detect scammers and bad actors.
What kinds of scams were prevalent on the apps?
The report included statements from victims who described how romance scammers cheated them out of tens of thousands of dollars after building a relationship with them on the dating apps. A common trend was to cite a major emergency in order to pressure the victim into sending over money. Using the victims’ phone number and/or email ID, the scammers would proceed to harass them online until the victim sometimes paid them in the hopes of de-escalating their aggression.
Another type of scam involved the same malicious user operating as different people on the same dating app, to ensnare more victims.
The report pointed to an inconsistent dating app AI strategy, where patchy machine learning systems led to heavy caseloads and “overwhelmed” human moderators who were unable to focus on visibly risky accounts. Per a document from the Match Group itself, Tinder could have better tackled dangerous accounts by building better AI signals or reducing its reliance on manual rules.
“In practice, these moderation lapses meant that bad actors that reached moderation were not immediately banned and instead may have continued to interact with and harm legitimate users until the platform gathered additional evidence,” explained the report.
What is the takeaway for Indian dating app users?
A bouquet of dating apps come under the Match Group, including Tinder, Hinge, Match (formerly Match.com), Plenty of Fish, and more such offerings catering to users in diverse countries and cultural communities.
In other words, a security lapse in one app comes with serious implications for the users of other Match Group-owned apps. Tinder and Hinge are popular in India as well, claiming the top ranks in terms of downloads via app marketplaces.
According to the Match Group, Hinge is expected to reach $1 billion in revenue in 2027, while Tinder is expanding its in-person events that are already live in the U.S. and Europe.
Indian users often register with apps that suggest profiles and tout AI-powered matchmaking as a selling point. However, as the U.S. committee report noted, cutting-edge AI tools require constant upkeep, testing, and upgrades in order to ensure customers remain shielded from emerging threats.
Regulators must also play a larger role in monitoring dating app services.
How can users avoid scammers on dating apps?
Dating app users should first vet the platforms they register with, making sure they agree with how data is collected and processed. Users should also be aware of the reporting options they have in case an online or offline interaction turns unsafe. Customers can research the apps’ founders, investors, and brand ambassadors, to make sure there is an alignment of values.
Dating app users should promptly report fraudulent user profiles and cease interacting with them. AI-generated user photos and videos, even when posted as a joke, often violate platform policies.
Another red flag is a dating app user who becomes intimate too quickly or is eager to discuss finances early on. Furthermore, scammers often pressure dating app users to contact them on external sites, so they can view the user’s phone number or harvest other personal details.
Users must withhold personal phone numbers, email IDs, home addresses, private social media channels, and employer information until they meet a match in-person and feel comfortable proceeding.