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Enterprise fraud management, AI and data visualization

Cambridge Intelligence

Surging fraud volumes and sophisticated AI tools have changed the dynamics for anti-fraud teams. While it has always been a data-intensive process, enterprise fraud management today is more complex and more important than ever. An AI-powered fight back? Automation is nothing new in enterprise fraud management.

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AI and data visualization: Powering the intelligence cycle

Cambridge Intelligence

Artificial intelligence is changing the way organizations think about data analysis. AI and data visualization can do a lot of the heavy lifting for analysts and investigators working with connected data – helping them detect, understand and even predict risks and threats.

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Eight financial services trends driving the need for better data visualization

Cambridge Intelligence

We’ve recently explored the huge impact of AI in fraud detection – in this post, we’ll look at eight other trends driving demand for better data visualization in the financial services sector. Download our white paper on network and timeline visualization for cloud security to find out more about this use case.

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3 new & easy ways to simplify complex data visualizations

Cambridge Intelligence

Rectangular combos offer a clear, space-efficient option for complex infrastructure networks Another key part of modern cloud security applications is their use of AI and machine learning to create timely and accurate alerts. A key part of the process is resolving multiple identifiers into single entities, often stored in different datasets.

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Responsible AI Relies on Data Literacy

DataRobot

Data literacy is a key component for any organization to be able to scale responsible and trusted artificial intelligence technology. Because of the multidisciplinary nature of AI products, stakeholders across an entire organization must share a common understanding of each project’s scope, deployment, governance , impact, and projected risk.

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Graph visualization use cases

Cambridge Intelligence

The challenge to understand hidden relationships and uncover actionable insights from data is universal, across countless data visualization use cases. In this blog post, we focus on seven of the most popular: Why visualize data as a graph? Data visualization makes it easy for us to identify trends and outliers.

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Misinformation and disinformation analysis with data visualization

Cambridge Intelligence

It looks at the role data visualization plays to detect, investigate and prevent misinformation and disinformation, and keep digital spaces safe. They exploit new technologies to create AI-generated false information, and harness the power of global social media platforms to spread their messages far and wide.