Today’s complex online fraud threats and countermeasures call for a team of experts to manage your exposure to loss. Fraugster’s proprietary technology allows us to use state-of-the-art big-data analytics to pinpoint threats and isolate them from the rest of the user population.

Our core proprietary technology is a massive parallel in-memory database, designed for extremely complex big data calculations in real time. How it works is as follows:

1. An incoming event is sent to Fraugster via a simple RestAPI integration with the relevant datapoints. The data is then enriched with both external data sources and our own risk analytics science developed by a veteran fraud risk team.

2. After the data is enriched it is sent to the Fraugster engine itself which looks for statistical twins within our records, both from the client's historical data as well as our overall data-pool.

3. The event is compared then only to the relevant cluster of historical data (which grants far better an...
Today’s complex online fraud threats and countermeasures call for a team of experts to manage your exposure to loss. Fraugster’s proprietary technology allows us to use state-of-the-art big-data analytics to pinpoint threats and isolate them from the rest of the user population.

Our core proprietary technology is a massive parallel in-memory database, designed for extremely complex big data calculations in real time. How it works is as follows:

1. An incoming event is sent to Fraugster via a simple RestAPI integration with the relevant datapoints. The data is then enriched with both external data sources and our own risk analytics science developed by a veteran fraud risk team.

2. After the data is enriched it is sent to the Fraugster engine itself which looks for statistical twins within our records, both from the client's historical data as well as our overall data-pool.

3. The event is compared then only to the relevant cluster of historical data (which grants far better and more accurate results than from comparing to the entire dataset) and returns the final fraud probability in a score format. No pre-defined models or rules are needed!

There are multiple advantages which derive from our technology and make Fraugster the better choice for managing fraud risk:

Reducing false positives - as Fraugster is able to make out the smallest behavioral patterns that usually disappear within the noise of big-data pools, it allows for better fraud detection and prevention as well as lowering the overall false-positive rate.

Ever-learning engine - our engine gets better with each new transaction, allowing us to keep toe-to-toe with evolving fraud patterns.

Flexibility & customization - as Fraugster’s engine doesn’t rely on pre-defined models, it means that every decision is tailor-made for that event. Are you a travel merchant with unique datapoints like ‘Destination City’ or ‘Number of Guests’? We can instantly use this valuable data based on your own historical records to boost your performance.

Multi-dimensional score - another aspect of our engine’s flexibility is its capability to produce a score that predicts the user’s behavior in more than just ‘fraud/legit’ semantics. Fraugster can calculate for each transaction the probability of signup, predict future engagement or even future revenues.
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