Build fraud detection models your way – programmatically, visually or AI-assisted – with IBM

Every year consumers and businesses lose billions of dollars to fraud; however, machine learning is becoming a major weapon in the battle to combat it.  Building the right model is challenging, and there are several different ways to approach it.  Are you a visual modeler?  Prefer open source?  How about leveraging AI to build models?

Join us to see how IBM Watson Studio’s versatile tooling supports all three machine learning approaches to classify an imbalanced binary target.  We will demonstrate how users can leverage Jupyter, SPSS Modeler and AutoAI to combat the challenges of predicting a skewed target using techniques such as generating synthetic samples, tuning misclassification costs, and building model ensembles to produce high-performing fraud detection models all within the same platform.

This special webinar will also highlight the new release of Watson Studio and Watson Machine Learning along with a new packaging of SPSS Modeler, which will allow SPSS Modeler customers to leverage the power of Watson Studio.  It is a must-see webinar for existing SPSS Modeler and Watson Studio customers as well as those who are brand new to IBM. 

Speakers

Graham Turney
Product Marketer, Watson Studio Desktop & SPSS Modeler
IBM