Fraud detection and prevention

Protect your applications, services, and operations from fraud using machine learning and decision automation. Our software provides real-time fraud analytics and prevention by integrating with your transactional systems and data streams.

Our clients

Retail
Hi-tech
Manufacturing
Finance
How our fraud detection solutions work
Risk evaluation and control
Our algorithms are design to find optimal trade-offs between false positive and false negative rates to minimize the effort spend on manual case review and investigation, minimize revenue losses, and reduce the impact on customer experience.
Wide range of algorithms for different use sases and industries
We are instrumental in building solutions that use or combine multiple algorithms for transaction analytics: We use deep learning algorithms to analyze non-aggregated event sequences and detect suspicious activities in early stages. This approach works bets for in-app and in-game fraud. We use graph-based machine learning methods to detect fraud patterns that span multiple entities or devices. This approach is typical for credit card fraud. We use anomaly detection algorithms when labeled transaction examples are not available.
Detection of rare events
One of the challenges with automatic fraud detection is a relative rarity of fraud events. We use specialized machine learning algorithms that handle rare events properly, and use the information about historical cases of fraud in the most optimal way.
Detection of classic and emerging patterns
Our solutions combine models that learn on large volumes of historical data and models that analyze ongoing data in real time. This approach helps to accurately detect classic fraud techniques, but also detect new patterns and types of fraudulent activities as they appear.
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We provide flexible engagement options to design and build a fraud detection and prevention solution for your company. Contact us today to start with a workshop, discovery, or POC

Workshop

We offer free half-day workshops with our top experts in supply chain analytics and optimization technologies to discuss your  supply chain management strategy, challenges, optimization opportunities, and industry best practices.

Proof of concept

If you have already identified a specific use case that needs to be solved, we usually can start with a 4-8 weeks proof-of-concept project to deliver tangible results and business value.

Discovery

If you are in the stage of requirements analysis and strategy development, we can start with a 2-3 weeks discovery phase to identify right use cases for supply chain analytics and optimization, design your solution using industry best practices, and build an implementation roadmap.