Bumble Inc. (BMBL), the popular women-centric dating app, has announced its latest feature, Deception Detector™, aiding its decade-long priority of building kind, safe, and authentic connections. Deception Detector™ uses Artificial Intelligence (AI) to help identify spam, scams and fake profiles, aiming to take action before members see them. Within the first two months of the technology’s introduction, Bumble saw member reports of spam, scams, and fake accounts reduced by 45%.
Research from Bumble Inc. shows that globally, respondents cited fake profiles and the risk of scams as their top concerns when online dating. In India, 29% of respondents expressed keeping their personal data safer, and 28% expressed the risk of scams as their top concern when meeting or dating people online. This concern and anxiety can lead people to miss out on meaningful connections that can positively impact their lives.
Deception Detector™ introduces a fast, reliable machine learning-based model to assess the authenticity of profiles and connections on Bumble Inc.’s platforms. Of those accounts identified as spam/scam profiles, Bumble Inc.’s testing showed that Deception Detector™ supported blocking 95% of these accounts automatically. This automated and AI-based technology is used in conjunction with dedicated human support to prioritise a safe and empowering community.
Lidiane Jones, CEO at Bumble Inc., addressed,
“In recent years, the online landscape has evolved significantly, and we see a growing concern about authenticity. Bumble Inc. was founded to build equitable relationships and empower women to make the first move. Deception Detector™ is our latest innovation as part of our ongoing commitment to our community to help ensure that connections made on our apps are genuine.
With a dedicated focus on women’s experience online, we recognise that in the AI era, trust is more paramount than ever. We are being thoughtful about using new models best to reduce the anxiety of making connections and support our community, with AI as a main focus area.”
