Incandor provides a behavioral intelligence platform that continuously maps user activity to create unique fingerprints for each account, detecting takeover, mule handoffs, and shared operators in real time. Its AI-driven analysis distinguishes human sessions from bots and visualizes fraud rings, enabling fraud teams at banks and digital commerce platforms to investigate and stop abuse quickly.
Funding
Funding not disclosed
Founders
Product
Problem
Financial institutions and online platforms struggle to detect when an account is transferred to a new operator, when a single individual controls multiple accounts, or when automated bots mimic human behavior, leading to fraud losses and regulatory risk.
Solution
Incandor delivers a behavioral intelligence platform that continuously maps user activity into a multidimensional behavioral space. By tracking the evolution of each account’s behavioral fingerprint, the system flags the exact moment a new person takes control, indicating a takeover or mule handoff. It also identifies shared operators across accounts, enabling the reconstruction of fraud rings from a single confirmed case. Advanced AI distinguishes human sessions from bot-driven agents, isolating automated activity that evades traditional rule‑based detection. The platform provides investigators with visual maps and timelines to quickly prioritize and investigate suspicious accounts before financial damage occurs.
Target Audience
Primary customers are fraud prevention teams at banks, payment processors, and digital commerce platforms that need to detect account abuse, mule activity, and bot fraud at scale.
Features
- Real‑time behavioral mapping that creates unique clusters for each human operator based on interaction patterns
- Automated detection of account takeover and mule handoff events when a session shifts to a new behavioral region
- Shared operator identification linking multiple accounts to the same individual across the ecosystem
- Fraud ring reconstruction that visualizes coordinated activity and reveals the full network from a single seed case
- Bot and AI‑agent detection that separates automated sessions into distinct clusters separate from human behavior
- Interactive dashboards with timeline visualizations and cluster maps to support rapid investigation