Category: Fraud Fighting
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From Decision Trees to Rule-Based Systems: A Machine Learning Prototype
In the rapidly evolving landscape of AI and ML, the interpretability of models has become a vital aspect. Despite the accuracy of complex models, comprehending their decision-making process can be a challenge. This interpretability is critically important in scenarios like fraud detection, where clarity and transparency in decision-making are required for legal and ethical reasons.…
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Navigating the AI/ML Landscape: Risks, Threats, and Solutions for Fraud Prevention
TLDR As we forge ahead in the age of digital transformation, AI/ML have become powerful tools in the fight against fraud. However, as with any technology, they come with their own set of challenges and risks. It’s encouraging to see reputable organizations like the National Institute of Standards and Technology (NIST) acknowledging these challenges and…
Michael Kalika's Blog 