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Comprehensive Risk Control Decision Engine
Integrate internal and external data, user device information, and user behaviour using various rules and techniques such as blacklist rules, association rules, frequency rules, time rules, device fingerprinting, biometric probes, and proxy IP detection to effectively identify all types of risks.
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Customised Monitoring Model
Tailor risk control strategies to cover the entire user lifecycle based on the risk profiles of e-commerce clients. Combine the actions of risk control operators and system automation to meet current and future business risk control needs.
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Global User Profiling
Gather risk indicators from IP addresses, phone numbers, emails, and physical addresses to create comprehensive fraudster profiles. These profiles include tags for various risks such as promotion abuse and fake registrations, enabling precise targeting of fraudulent activities.
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Risk Profiling Using Alternative Credit Data Insight
We integrate multi-source data, including behavioural patterns, social media insights, and device information, to enhance profile credit risk. This holistic approach helps banks reach underserved and unbanked populations while improving credit assessments and reducing default rates. By analysing customer behaviours and leveraging alternative data, we enable more inclusive and informed credit decisions, enhancing financial inclusion, especially in emerging markets.
