The Kount Difference
The Kount difference is the approach to safely linking real-world & digital identities. Kount’s adaptive intelligence analyzes digital risk signals along with real-world identity artifacts to ascertain the appropriate response for new account creation.
This analysis includes third-party data callouts from an orchestration hub for real-world identity verification, scoring, and complex decisioning.
Identity Trust Global 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 Identity Trust Global 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 and customize risk thresholds to address emerging attack methods and new use cases.
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.