Askhedi provides a real-time fraud detection platform that uses adaptive machine‑learning models to monitor transaction streams and flag emerging fraudulent behavior. The solution delivers actionable alerts and visual risk dashboards, enabling financial institutions, payment processors, and e‑commerce platforms to reduce manual investigation time and mitigate losses while staying compliant.
Funding
Funding not disclosed
Founders
Product
Problem
Organizations face increasing financial losses due to rapidly evolving fraudulent transaction patterns, and traditional detection methods often lag behind new fraud techniques, leading to delayed response and compliance risks.
Solution
Askhedi offers a real-time fraud detection platform that leverages advanced analytics and machine‑learning models to continuously monitor transaction streams. The system identifies emerging fraudulent behaviors as they occur and generates actionable alerts for security and compliance teams. By automating pattern analysis, the platform reduces manual investigation time and helps organizations mitigate loss while maintaining regulatory standards.
Target Audience
Primary customers are financial institutions, payment processors, and e‑commerce platforms that need to detect and respond to fraudulent activity in real time.
Features
- Real-time ingestion and analysis of transaction data across multiple channels
- Machine‑learning models that adapt to new fraud patterns without extensive re‑training
- Configurable alerting engine that delivers actionable notifications to relevant teams
- Dashboard visualizations of risk scores, trend analytics, and incident timelines
- API integration for seamless embedding into existing payment and monitoring systems