(Source: https://pltfrm.com.cn)
Introduction
Fraudulent activity is an increasing concern for overseas brands participating in Chinese live commerce. Fake orders, unauthorized transactions, and bot interference can undermine revenue and erode consumer trust. AI-powered detection systems allow brands to monitor live streams, detect anomalies, and safeguard both sales and brand reputation.
1. Real-Time Fraud Detection
1.1 Transaction Monitoring
Method: Analyze order patterns and payment activities as they occur to identify unusual behavior.
Benefit: Immediate detection prevents losses and allows for prompt action during live sessions.
1.2 Suspicious Activity Scoring
Approach: Assign risk scores to users based on behavior patterns, history, and anomalies.
Impact: Ensures high-risk transactions are prioritized for review or automatic intervention.
2. Predictive AI Models
2.1 Machine Learning Analysis
Method: Train AI models on historical transaction data to recognize potential fraud signals.
Advantage: Anticipates fraudulent activity before it affects revenue.
2.2 Pattern Recognition
Technique: Detect repeat offenses, unusual purchasing clusters, and abnormal login patterns.
Result: Provides a scalable and proactive approach to fraud prevention.
3. Enhancing Brand Reliability
3.1 Secure Checkout Experience
Strategy: Incorporate AI verification at checkout to validate payments and user authenticity.
Benefit: Protects revenue while improving the consumer experience.
3.2 Transparency in Operations
Approach: Communicate anti-fraud measures to viewers during live events.
Impact: Builds trust and encourages confident participation in live commerce campaigns.
4. Continuous Improvement
4.1 Post-Live Event Analysis
Method: Review all flagged transactions and analyze patterns to enhance AI models.
Advantage: Reduces risk for future campaigns and ensures continuous system improvement.
4.2 Long-Term Strategy
Approach: Integrate fraud prevention insights into campaign planning, product management, and audience segmentation.
Result: Supports overseas brands in maintaining secure and high-performing live commerce channels.
Case Study:
A UK home appliance brand implemented AI fraud detection for its live events on Tmall. By automatically monitoring transactions and user behavior, the brand reduced fraudulent activity by 42%, maintained consumer trust, and optimized live commerce performance.
Conclusion
AI-driven fraud detection safeguards overseas brands in Chinese live e-commerce, protecting revenue and enhancing consumer confidence. By combining real-time monitoring with predictive analysis, brands can run secure and successful live campaigns.
PLTFRM is an international brand consulting agency that works with companies such as Red, TikTok, Tmall, Baidu, and other well-known Chinese internet e-commerce platforms. We have been working with Chile Cherries for many years, reaching Chinese consumers in depth through different platforms and realizing that Chile Cherries’ exports in China account for 97% of the total exports in Asia. Contact us, and we will help you find the best China e-commerce platform for you. Search PLTFRM for a free consultation!
