Right at the moment a user clicks “pay” or confirms an important transaction, that's where we run a statistical
analysis that takes less than a human's blink. We check millions of incoming data points every day against millions
of existing others to understand every shopper's risk. We do this through what is known as Big Data architecture.
We deliver a decision to reject, accept or review every transaction depending on the level of risk, along with an explanation of such decision.
We explain each decision and our team build the decision logic along with your team, so they understand what is going
onin the back. This helps calibrate data models faster and better: our clients contribute very good ideas by understanding what is behind it.
Through a REST API or e-commerce platform plugins. Our technical installation requires following a 4-step guide, something way faster than other tools. Some clients take just a couple of hours to install.Through a REST API or e-commerce platform plugins. Our technical installation requires following a 4-step guide,
Less than 250 milliseconds on average, so we do not mess with your shopper experience.En promedio, menos de 300 milisegundos para no entorpecer la experiencia de compra.
Our solution was developed in a region with the largest number of fraud attacks: Latin America. It's designed for the most difficult markets. We specialize in companies with large transaction volumes but lower margins. To prevent fraud, we mix innovative tools with tried-and-true methods. For example, rule-based decisions -to act fast, Machine Learning models -to learn with each transaction, or Graph Analysis -to leverage our clients' collective intelligence.Desarollamos esta solución en una región con los mayores ataques de fraude: América Latina. Está diseñada para mercados
It is possible to compare results with other solutions running Bayonet as a “mirror” alongside another tool. This way you can test by yourself the improvement in your numbers. If you're a company with a high-volume or lower-margin business model, we can certainly help you.Es posible comparar nuestros resultados ejecutando Bayonet como "espejo" junto a otra herramienta. De este modo, puedes