How DataRobot Automates Pricing Optimization at Domestic & General
Businesses around the world are leveraging machine learning to become AI-driven enterprises and stay ahead of the competition. The use cases for automated machine learning continue to grow and span all industries ranging from fraud detection in banking, patient readmissions for hospitals, machine maintenance in manufacturing, and much more. Our latest customer case study focuses on a common challenge for insurance companies: price optimization and how automated machine learning helps solve this business problem.
At AI Experience London, Paul Davies, Head of Data Science at Domestic & General (D&G), spoke about how leveraging machine learning enabled his team to provide a better and more personalized experience to their 16 million customers.
“There’s no way we can be as personal or customer-focused as we would like without the help of machine learning.” — Paul Davies, D&G
His team automates the building of their predictive machine learning models in order to successfully deliver high quality customer experience. Automation is the key that enables them to effectively manage each and every customer.
With DataRobot, D&G was able to successfully address pricing optimization for the company’s customer base, resulting in more than double the revenue uplift (from 1.5% to 4%). They’re currently looking into expanding the company’s use of automated machine learning.
“Very soon, all pricing throughout D&G – not just for renewals – will go through price optimization in real-time underpinned by models built in DataRobot. So, that will be 500,000 to a million price quotes a month.” — Paul Davies, D&G
Read more from Domestic & General in the case study, DataRobot Helps D&G Find Success When the Price is Right.