ROLE
Value Across the Organization
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ROLE: CTO
CHALLENGE
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SOLUTION
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ROLE: Program Manager
CHALLENGE
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SOLUTION
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ROLE: Case Manager
CHALLENGE
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SOLUTION
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ROLE: Analyst
CHALLENGE
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SOLUTION
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ROLE: Data Scientist
CHALLENGE
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SOLUTION
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See Our Products
Tactical Attack Surface Intelligence
Description
Counter Insider Threat Intelligence
Description
Continuous Intelligence Examples
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Revealing Social Media Deepfakes
Problem
AI is a force-multiplier and more accessible than ever. Unfortunately, risks are as equally amplified as opportunities. We are now on the cusp of AI bot swarms overwhelming social media platforms (SMP), where YouTube and other providers now have nefarious deepfake comments promoting fraudulent information or financial scams. Besides impacting provider operations and costs, AI bot comments create a poor user experience, exploit customers, and damage reputations.
Solution
AI Bot Swarm Detection solution for Google was quickly developed in the Cogynt URP in an extensible CI model without requiring any code or storing terabytes upon terabytes of Google comment data. Beyond identifying conspicuous bot comments, Cogynt was able to detect (with irrefutable evidence) inconspicuous bot comments and associated accounts in real-time that human analysts and Google’s sophisticated filters would otherwise have failed to detect.
Bank Fraud
Problem
Bank fraud is a set of schemes that deceive a financial institution to obtain or avoid losing money, property, services, or advantage. While there are a wide variety of related financial fraud methods, criminal money laundering is an ongoing and pervasive worldwide economic threat. One popular method is using money mule, where illegally acquired money is transferred to another account on someone else’s behalf. It is easy to disguise and difficult to detect.
Solution
A Money mule detection and mitigation solution was developed in the Cogynt URP in an extensible CI model covering new accounts and transaction parameters and analyzing events and patterns of events (short-term and long-term). Emulating a real-world approach to fraud detection, Cogynt was able to identify (with irrefutable evidence) a wide variety of mule account usage in real-time that may otherwise would have evaded conventional fraud detection methods.
See How to Build Decision Advantage
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