Scamalytics was initially conceptualized in 2012 when its founders were chatting at a dating conference. They decided that machine learning techniques could be leveraged to attempt to prevent fraud in online dating by detecting fake accounts.
The core principle behind Scamalytics lies in how dating fraud is perpetuated. Oftentimes, scammers create hundreds of fraudulent accounts to commit their crimes. With a goal of efficiency, these accounts can share similar images or phrases.
Scamalytics partners with dating app companies to use machine learning to analyze newly created user profiles. Algorithms take the data from users and check them for these common phrases and patterns. They also check the user’s IP address, a unique address that indicates what computer or network is creating the account.
