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Prevent Emerging Fraud

Next-generation AI protects against new and existing fraud attacks before they become chargebacks.

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Accept More Good Orders

Improve the customer experience, increase order acceptance rates, and generate more revenue while reducing false positives.

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Reduce Manual Reviews

Lower operational costs and drive greater scalability to fraud operations teams by automating approve and decline decisions.

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Control Business Outcomes

Customize risk thresholds to achieve desired business outcomes: decline rates, fraud rates, and fraud operations costs.

AI That Simulates an Experienced Fraud Analyst

Kount’s AI simulates an experienced fraud analyst by weighing the risk of fraud against the value of the customer, but on a faster and more scalable basis.

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Unsupervised Machine Learning

Detects emerging fraud attacks

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Supervised Machine Learning

Learns from past decisions

Universal Data Network

Fuels machine learning models

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Control Center

Fine-tunes fraud prevention decisions

OmniscoreTM: AI-Driven Transaction Safety Rating

The score that catches more fraud

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Omniscore is the actionable transaction safety rating that is produced by Kount’s AI. It’s twice as effective than previous models at detecting payments fraud, while maintaining Kount’s 250 millisecond response rate.

The highly predictive score can be relied upon when decisioning orders, so that there is less reliance on manual review and reactive fraud rules. The result is less false positives and negatives, and more good transactions to generate revenue.

Unsupervised Machine Learning

Detects emerging fraud attacks

Kount’s unsupervised machine learning uses advanced algorithms and models to detect transaction anomalies much faster, more accurately, and on a more scalable basis than human judgment alone. It catches emerging fraud attacks that supervised machine learning models can’t catch before they result in chargebacks.

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Supervised Machine Learning

Learns from past decisions

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Kount’s supervised machine learning analyzes billions of historical transactions from our Universal Data Network and looks for signals that have predicted fraud in the past. This scales the process of an analyst drawing on their own experience and the company’s history to identify a trusted transaction.

Universal Data Network

Fuels machine learning models

Kount’s Universal Data Network includes 12+ years of comprehensive transaction and identity data that crosses 6,500 customers, 180+ countries and territories, and multiple payment networks. That analytical richness feeds into machine learning models so they are properly trained to accurately predict risk.

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Control Center

Fine-tunes fraud prevention decisions

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A Control Center that provides the ability to control fraud prevention decisions, conduct investigations, and monitor performance. It enables customers to create policies and customize risk thresholds based on desired business outcomes.

Self-Service Analytics

Actionable business intelligence reporting

Kount’s Datamart puts the rich data from payment transactions, customer interactions and outcomes into the hands of our customers to provide insights into business performance and enable strategic forward-looking decisions across the business.

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