E-commerce is entering a new phase, expanding beyond proprietary websites and migrating to high-engagement networks like TikTok and Instagram. The growth of social commerce, with platforms such as TikTok Shop, for example, challenges companies to rethink their sales and digital security strategies. According to Santander’s projections, this new TikTok feature could capture between 5% and 9% of all Brazilian e-commerce in the next three years, becoming a major competitor in the national digital retail market — but also a new ground for fraudulent activities.
The fast and simplified dynamics that drive conversion in social commerce also open critical gaps for fraudsters. On these channels, the creation of fake profiles, purchases with leaked cards, bot attacks, and social engineering have become increasingly frequent. ‘In the dynamics of social commerce, more than traditional antifraud processes is needed. Solutions that use adaptive intelligence and deep behavioral analysis are more effective, as they can protect without harming the user experience,’ explains Thiago Bertacchini, fraud prevention specialist and Head of Sales at Nethone, a Mangopay solution.
Below, the expert highlights 3 key solutions to strengthen online sales security on social commerce platforms:
Behavioral biometrics
With the use of real-time behavioral biometrics, companies can identify and block threats before they become real risks. By mapping user behavior, this technology, combined with artificial intelligence, enables precise identity validation and predicts fraud attempts based on more than 130 unique signals. This approach, used by Nethone in digital fraud prevention, provides a complete view of each interaction, enabling personalized security strategies that block suspicious activities without compromising the experience of real consumers.
Vector identifier
Technologies like Vector Identifier, a proprietary device fingerprinting solution, can accurately recognize devices even in situations where fraudsters erase browser data or use anonymous browsing, as they generate a stable and persistent ID for each digital environment, allowing tracking of suspicious behavior despite masking attempts. By detecting complex patterns and malicious usage, the tool significantly reduces false positives and ensures greater accuracy in fraud prevention.
Using Machine Learning for anomaly detection
Fraudsters use a range of resources to bypass security systems, such as disguised devices, connections, and browsers. To counter them, it is essential to have machine learning-based solutions that analyze the digital environment and detect subtle signs of manipulation before purchase completion. Nethone’s technology, for example, can identify the use of virtual machines, customized browsers, and inconsistent network patterns, which allows differentiation between legitimate customers and users with suspicious activities, increasing the security of real purchases without any friction for legitimate users.
According to Thiago, in the current scenario of new sales channels, ensuring these environments are secure, scalable, and reliable is a strategic asset in the digital space, as it prioritizes the purchasing journey. Integrating antifraud solutions is not just a matter of mitigation but also of ensuring reputation, customer experience, and digital business sustainability. ‘Consumer trust does not only come from brand communication but from the technology that supports it. When security is integrated from the first click to purchase completion, it becomes a competitive differentiator,’ he concludes.
