With AI and automated machine learning, retail banks, commercial banks, and wealth managers can drive revenue growth, differentiate themselves through a superior client experience, and reduce operational costs, while improving quality and improving the effectiveness and efficiency of risk management.
There are hundreds of opportunities to leverage AI and machine learning in every line of business and function. From prepayment risk and price elasticity of demand to needs-based recommendations and loan pricing optimization, tangible business value is being realized from the deployment of AI models. LendingTree is achieving success by matching borrowers with the highest value offers with an increase in acceptance rates.
Eight of the world’s top ten financial institutions use DataRobot to scale data science. As front-runners in AI adoption, they are seeing their early efforts fund additional use case deployments. DataRobot is trusted by PNC, USBank, LendingTree, FreddieMac, and TD Ameritrade, among others, partnering with these organizations to not only automate machine learning but accelerate and operationalize AI.
I’ve never had so much ease explaining the inner workings of my models as I do with DataRobot.
DataRobot justifies its place by providing value and returning significant ROI immediately.
DataRobot's platform allows users to build and deploy highly accurate machine learning models in a fraction of the time it takes using traditional data science methods.
What DataRobot was able to accomplish in the first hour was more thorough and accurate than models we had built over the prior month.