Billpay wanted to know if they could improve their fraud detection algorithm. In less than a week, we created a state-of-the-art benchmark model and identified the most important improvements.
At Billpay, we already understand the value of machine learning, but we’re always looking for ways to improve our risk scores. Data Revenue offered a cost-effective solution that allowed us to test our system against what they could build. Markus and his team were able to give us a comparison in just a few days. Their algorithms were much more advanced; Markus is clearly an expert. The outcome was interesting, and we definitely learned something. The process was very smooth, and the results were well worth the time, effort, and money.