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Fraud Prevention Security Platforms

Clean the Sky - Positive Eco Trends & Breakthroughs

'SEON' Maintains Security for eCommerce Businesses

— December 29, 2016 — Tech
'SEON' is a way for eCommerce businesses to help detect and stop fraud from occurring to ensure that their site and shoppers remain secure.

Online shopping has become a widely accepted way of purchasing goods, but the imminent threat of being hacked or victim of fraud is constantly lingering for consumers and brands. As such, 'SEON' works with real-time data and machine learning technology in order to pinpoint ways to help prevent fraud from occurring before it turns into a problem for customers.

Although 'SEON' is ideal for eCommerce businesses, it's also great for virtually any online platform where authentication is key to ensuring that users remain secure. It features a simple interface that makes it quick to keep track of purchases and fraudulent ones that have been blocked.
Trend Themes
1. Real-time Data Analysis - 'SEON' utilizes real-time data and machine learning technology to prevent fraud, highlighting the opportunity for other industries to adopt similar data-driven approaches.
2. Machine Learning in Fraud Prevention - 'SEON's use of machine learning technology to detect and stop fraud presents opportunities for businesses across industries to leverage AI for enhanced security.
3. Streamlined Fraud Detection - 'SEON' provides a simple interface for tracking and blocking fraudulent purchases, suggesting opportunities for online platforms to improve their fraud prevention processes.
Industry Implications
1. Ecommerce - The 'SEON' platform is specifically designed for eCommerce businesses, showcasing the potential for industry-wide adoption to enhance security measures.
2. Online Authentication - 'SEON' can benefit any online platform where user authentication is crucial, creating openings for industries like banking, social media, and online marketplaces to bolster their security.
3. Data-driven Security Solutions - 'SEON's approach to fraud prevention through real-time data analysis and machine learning presents opportunities for the cybersecurity industry to develop innovative security solutions.
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