Category: Machine Learning
Read and learn about Machine Learning in identity verification, fraud detection and more with these articles and posts.
Using Machine Learning for Rule Building
Many of our customers use rules in their fraud workflows to identify good and bad actors. These rules, which are combinations of conditional statements that operate as data filters, can be very effective, but formulating “the right rule” can be difficult. That’s where the Ekata Field Data Science (FDS) team comes in to help customers […]
Ekata Executive Series, Part IV: The Global Fraud Arbitrage Beast and the Necessity of Machine Learning
Good day and welcome to my last 2020 quarterly CEO synopsis, and what a year it has been. In this, I outline the dynamics I see developing in the global identity verification (IDV) market and highlight Ekata’s response to continuous market demands. I increasingly try to blend verified third-party research with our first-hand customer and […]
Delivering a Best-in-Class Customer Experience with Model Releases
As new fraud trends continue to emerge in the post-pandemic, digital world, we are constantly evaluating and updating our machine learning models to ensure they provide the most accurate and performant data for customers. Releasing new model versions to customers can present a few challenges: balancing frequency of updates with customer impact, timing of releases, […]