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AI-Powered Solutions, AI-Empowered Clients

DataVisor Quick Takes

By Christopher Watkins May 8, 2019

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about Christopher Watkins
Christopher Watkins is Senior Creative Writer at DataVisor. He brings 10+ years of writing, editing, and strategy experience to his role. He was previously Senior Writer and Chief Words Officer at Udacity. He holds an MFA in Creative Writing from the University of Southern Maine.

Leveraging the power of machine learning to build intelligent solutions that empower organizations to proactively defend their businesses, their customers, and their data.


There are many ways to understand AI and machine learning, and as many definitions of each as you might care to research. In the fields of security and fraud protection, our interest is primarily in machine learning as an application of AI, as it is by leveraging the power of machine learning that advanced fraud solutions are able to “learn” in real-time. This is the capability that makes it possible to reveal previously unknown fraud patterns—a quantum leap forward from reactive approaches and strictly rules-based systems that can only capture what’s already been previously discovered.

AI-powered fraud solutions

What does it mean for a solution to be “AI-powered?” In the same way a car is able to fulfill its intended function by virtue of the fact that it is powered by its engine, a comprehensive fraud management solution like dCube is able to deliver on its promise to detect known and unknown fraud because it is “powered” by artificial intelligence in the form of applied machine learning. The solution itself is an “intelligent” one because it can perform intelligent functions—analyze data, draw conclusions, and take action—and its proficiency increases with exposure to data; that is to say, the machine “learns.”

The need for AI and machine learning

Advanced AI-powered solutions are critical in a world where everything from finance, healthcare, and politics, to communication, education, and commerce, happens online. When it comes to fraud, success means meeting scale with scale, because modern fraud is complex, coordinated, and massive.

As detailed in DataVisor’s Q1 2019 Fraud Index Report, the consequences of failing to fight fraud effective are getting exponentially more severe, and legacy detection solutions are too easily outmaneuvered by increasingly sophisticated fraudsters armed with rapid-fire technologies and swarms of invasive bots. Simply detecting known fraud is not enough, and success means uncovering cleverly-disguised patterns and correlating seemingly disparate events. This is why organizations across the business spectrum are embracing a new generation of proactive fraud management solutions, and leveraging the power of AI to prevent financial and reputational damage before it happens.

AI-empowered enterprises

As described previously, to be AI-powered is to essentially “run” on AI. However, when something or someone is AI-empowered, they are imbued with new capabilities because of AI. To extend the car metaphor from above:

An engine makes it possible for a car to run. Having a car makes it possible to travel.

This is what we mean when we speak of “AI-empowered clients.” An organization that integrates and deploys a robust, fully-featured, AI-powered fraud management solution can do something previously not possible—it can move faster than the speed of fraud.

Real-world results for AI-empowered clients

What does “move faster than the speed of fraud” mean in actual practice?

Top online marketplace defeats mass registrations and fake listing scams
For one client that was plagued by mass registrations and fake listing scams, it meant a 20% lift in detection accuracy, with nearly 90% of all fraudulent accounts caught even before the first scam. The problems were so massive that one single fraud ring comprised almost 70K accounts! Incredible as this may sound, that’s not unusual for a large enterprise.

The client is a global online marketplace operating in 40+ countries, with over 350 million monthly active users, but their previous fraud solutions could not identify cross-account linkages and were not able to reliably detect large-scale fake listings due to an inability to analyze unstructured data and metadata. That all changed when they became an AI-empowered organization. Not only did detection performance improve dramatically, but the majority of the work was automated—auto-actions were successfully taken on over 65% of detections.

DataVisor - Case Study - Results

Leading U.S. credit card issuer reduces application fraud losses
For another client—a top U.S. credit card issuer processing more than 20 million card applications every year—AI-empowerment resulted in 25% more fraud captured, at a detection rate of over 94%, with savings of over $15 million.

These results represent a seismic transformation for the organization. Prior to embracing the DataVisor approach, sophisticated fraudsters were using stolen and synthetic identities to apply for hundreds of new cards at a time. Fraud alerts were piling up, and the need for intensive manual review was overwhelming the operational team. Today, they are proactively detecting coordinated and unknown frauds with high accuracy, and making bulk decisions that can be applied with high degrees of confidence.

At DataVisor, it is our mission to empower every client to achieve results like those presented above, and in every case study we publish, we are proud and honored to chronicle the successes of our AI-empowered clients.


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