The Kount Difference
Kount’s award-winning payments fraud prevention solution protects digital commerce in hyper-competitive, high-risk environments, while enabling businesses to deliver a frictionless experience to legitimate customers. Kount does not over rely on any particular aspect of fraud prevention.
Universal Identity Network
With comprehensive transaction and identity data, Kount enables real-time decisioning on the level of trust appropriate for the level of risk presented.
This data crosses different transaction complexities, different verticals, and different geographies so machine learning models can be properly trained to accurately predict risk. That analytical richness includes data on physical real-world and digital identities creating an integrated picture of customer behavior.
This provides merchants—regardless of industry, customer base, or geography—insights to protect against fraudulent activities.
Advanced Machine Learning
Kount employs unsupervised as well as supervised machine learning models. These models lead the market in predictive ability because they are infused with 12 years of deep domain expertise and are trained on data from Kount’s vast Universal Identity Network.
To get the most out of machine learning, one has to know how to define the problems to be solved. This is where Kount’s fraud expertise comes into play, as a team of data scientists determine the most meaningful machine learning features for even the most sophisticated types of attacks and use those features to identify behavioral anomalies as well as common good behavior for a given identity or identity attribute.
Kount’s Control Center provides the ability to fine-tune fraud prevention decisions, conduct investigations, and monitor performance.
It enables customers to create rules and policies that meet their unique business needs (from promotions and policy abuse to non-fraud chargebacks) and customize their risk thresholds to address emerging attack methods, new use cases, and issues such as bad marketing affiliates and SKU-specific policies.
Critical tools are also available for investigation, rescoring, and reporting.
Self-service analytics allows for in-depth investigation into suspicious behavior as well as business performance. That learning can inform future rules and policies created within the Kount solution, but it can also provide a breadth and depth of customer knowledge.
That knowledge can lead to improved marketing activities, the introduction of new use cases, or the expansion of sales channels. The analysis possible with Datamart goes far beyond preventing fraud behaviors to providing insights into business performance.