How Katana Graph Fights Fraud and Cyberattacks

By: Katana Graph

April 25, 2022

How Katana Graph Fights Fraud and Cyberattacks

Fraud and cyberattacks are projected to become more frequent and pernicious in the next year. Attackers use increasingly sophisticated technology and continually adapt and evolve their techniques to nab as much as possible before detection.

The patterns of attacks that businesses saw in 2021 will likely morph as new technologies emerge and new opportunities arise. Data recently released by the Federal Trade Commission revealed that consumer fraud rose 70% during 2021, totaling $6 Billion. The FTC received 5.7 million reports of fraud in 2021. The actual cost of fraud to financial institutions has been much higher: for every dollar lost by U.S. financial services firms due to fraud, another three dollars is spent on claims, legal fees, investigation, and mitigation.

Fighting fraud is a never-ending battle that demands elevating our technological response with solutions that are smarter, faster to implement, and more affordable than earlier defense strategies. Detecting fraudulent activity is vital in avoiding security breaches, especially in the industries most attractive to fraudsters with access to exceptionally sophisticated cybercrime tools, networks, and technologies.

Fraud detection techniques must now incorporate advanced artificial intelligence; rule-based systems and traditional machine learning are no match for the innovative tactics of today’s bad actors in pursuit of fraud.

Past detection schemes have barely been able to keep up with even the most basic fraud detection tasks and are no longer sufficient. Due to their dependence on transaction threshold levels, processing a high rate of false-positive results, and continual manual rule review work, it’s time for a new solution to fraud detection.

In recent years, graph technology has demonstrated important improvements in fraud detection, but such systems have historically involved massive computing capability to achieve fraud detection at the scale necessary for today's online business needs.

Katana Graph has now built a graph intelligence platform that brings breakthroughs in data processing capabilities essential for anti-fraud applications. Katana Graph adroitly handles complex graph queries, algorithms, and deep learning tasks at massive scale and speed unmatched by other graph solutions.

Katana Graph overcomes the challenges of disparate systems being needed for different parts of a complete fraud analysis system with its all-in-one graph computing platform, integrating graph query, analytics, mining, and deep learning graph AI, at exceptional levels of performance and scale.

For more details, download the Fraud Detection datasheet.


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