Back in the 1990s, the financial services sector adopted generalized linear models (GLMs) because of their accuracy and the increasing complexity of decision-making. But GLMs suffer from several disadvantages. Specifically, they can be resource-intensive and time-consuming to build. They cannot work with missing values, and they require data to be collected from rigorously conducted experiments.
Enter automated machine learning and DataRobot’s automated machine learning platform. Our solution not only surmounts these obstacles but also provides more accurate, human-friendly explanations for how it uses the data, the patterns found in the data, and the reasons for a specific decision or prediction.