We see reports of dating-related crimes every day. FBI warns of dating site scams, as many people are losing their money. But even if one does not lose the money after communicating with a fake person, it can still lead to disappointment and discourage people from coming back to your site again.
So what do you do?
You can help your dating service members by doing (a part of) the vetting job for them. Use technology to make sure that your users are genuine people, who are really interested in what your service is about.
In comes Scamalytics, the shared blacklist of scammer profiles and network data. The system uses machine learning, image recognition, and other methods to identify suspicious behaviour and protect your users from bad actors.
How does it work?
The Scamalytics API evaluates user behaviour and responds with a score in real time which allows the system to automatically remove fraudulent users, even when moderators are away.
Checking images against millions of blacklisted images to make sure they are instantly eliminated from going live on your site and putting real people off.
Detecting scammers and differentiating between custom scammer signals and scammer trends that are emerging globally.
-Text Pattern Analysis
Looking for patterns in freeform text and messages that detect “scammer grammar” vs normal local use of grammar.
Watch this interview with the service founders.