E-commerce is experiencing a new phase, expanding beyond proprietary websites and migrating to high-engagement networks, such as theTikTokandInstagramThe growth of social commerce, with platforms like theTikTok Shopfor example, it challenges companies to rethink their sales strategies and digital security. According to Santander's projection, 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 sector — but also a new ground for fraudulent activities.
The fast and straightforward dynamics that drive conversion in social commerce also open critical gaps for fraudsters' actions. In 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 anti-fraud processes are necessary. 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 atNethonea Mangopay solution.
Next, the specialist highlights 3 key solutions to strengthen online sales security on social commerce platforms:
Behavioral biometrics
With real-time behavioral biometrics, companies can identify and block threats before they become a real risk. By mapping user behavior, this technology, combined with artificial intelligence, allows for accurate identity validation and predicts fraud attempts based on more than 130 unique signals. This approach, used by Nethone in digital fraud prevention, provides a comprehensive view of each interaction, enabling personalized security strategies that block suspicious activities without compromising the experience of genuine consumers.
Vector identifier
Technologies like Vector Identifier, a proprietary device fingerprinting solution, are capable of accurately recognizing devices even in situations where fraudsters delete browser data or use anonymous browsing, as they generate a stable and persistent ID for each digital environment, allowing the tracking of suspicious behaviors even in the face of masking attempts. By detecting complex patterns and malicious uses, the tool significantly reduces false positives and ensures greater accuracy in fraud prevention.
Use of Machine Learning for anomaly detection
Fraudsters use a variety of resources to bypass security systems, such as devices, disguised connections, and browsers. To confront them, it is essential to rely on machine learning-based solutions that analyze the digital environment and detect subtle signs of manipulation before the purchase is completed. Nethone's technology, for example, is capable of identifying the use of virtual machines, customized browsers, and inconsistent network patterns, which allows for 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 that these environments are secure, scalable, and reliable is a strategic asset in the digital space, as it prioritizes the purchase journey. Integrating anti-fraud solutions is not only a matter of mitigation but also of ensuring reputation, customer experience, and the sustainability of the digital business. "Consumer trust is not only born from brand communication but also from the technology that supports it. When security is integrated from the first click to the completion of the purchase, it becomes a competitive differentiator," he concludes.
