Suspicious behaviour detection!
Monitor visible, hidden and cognitive behavioural patterns through keystrokes, time spent, ip, and device parameters.
How it Works?
Using Machine learning (ML) to protect and secure, digital transactions at scale.
Device Fingerprinting
Identify devices and browsers used by genuine users which can tackle suspicious behaviour and account takeover. We protect Android & Apple apps through SDKs while covering Desktops & Laptops through javascript libraries. The approach offers a lightweight form of fraud prevention against fraudsters who use identity concealing techniques like disabling cookies, surfing through a VPN, or using browsers in incognito mode.
Keystroke dynamics & Device Behaviour
Keystroke dynamics is a method of gathering and analysing speed and variation in typing behaviour to identify users. In mobile devices it also analyzes the angle at which the phone is held, finger pressure on the touchscreen, latency between keystrokes, duration of keystrokes, hold time and overall typing speed and frequency of errors.
Application interaction
Tracking application interaction involves monitoring a user’s journey in the application, the screens/page visits, frequency and duration of usage and thus the overall behaviour of a user.
Realtime
Explainable
Accurate
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IP Fingerprinting
Data elements derived from IP addresses are used to understand Geolocation mapping, ISP, VPN Settings as well as identify possible access from TOR/Dark web, IPs with high Threat level or IPs used in DDOS. These serve as markers to detect any anomalies in behaviour and thus detect fraud
Secure Innovative Products
Low value payments (UPI, Zelle, Faster Payments), BNPL, App based lending, P2P, P2M, P2A, RFP and a range of new products require models and rules customized to contain fraudsters & lower delinquency.
