Cybertonica provides a machine learning-based fraud prevention solution that automates real-time risk monitoring and decision-making using behavioral biometrics. The platform reduces fraud and chargebacks by up to 70% while increasing revenue by up to 25% through enhanced customer experience and tailored integrations.
Funding
$7.3M raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
FOFounders
Product
Problem
E-commerce, payments, and FinTech businesses face increasing fraud and cyber threats, including account takeover, bot attacks, and chargebacks, leading to revenue loss and increased operational costs. Traditional fraud detection systems often rely on rigid rules that are easily bypassed by sophisticated fraudsters, resulting in high false positive rates and a degraded customer experience.
Solution
Cybertonica offers a real-time fraud prevention and risk management platform that leverages machine learning and behavioral biometrics to automate fraud detection and decision-making. The platform analyzes user behavior, device characteristics, and transactional data to identify and prevent fraudulent activities, such as account takeovers, bot attacks, and new account fraud. Cybertonica's solution provides a comprehensive view of risk, enabling businesses to reduce fraud losses, minimize chargebacks, increase revenue, and improve the customer experience through frictionless authentication and smooth user journeys. The system's rule editor and testing module allows businesses to customize and implement improvements in real-time.
Target Audience
Cybertonica primarily serves global acquiring banks, payment gateways, FinTech companies, and e-commerce businesses seeking to reduce fraud, manage risk, and improve customer experience.
Features
- Real-time fraud and risk monitoring with automated decision-making
- Behavioral biometrics analysis, including mouse movements, typing speed, and touchscreen usage
- Machine learning-based transactional risk scoring
- Device authentication and compromised device detection
- Real-time rules editing and testing
- AML (Anti-Money Laundering) alerts in less than one second
- Prediction of threats and chargebacks before they arise
- Dark web monitoring for compromised credentials
- Integration with Visa and Mastercard's Compelling Evidence 3 rules for chargeback representments