H2O.ai Benefits

Rahul Koduru
Director of Data Engineering at Transamerica
One example, we are able to automate life insurance. We have to underwrite policies. When somebody applies for a policy, we take their blood, then assign them a risk: substandard, standard, preferred, etc. Depending on this, we price our products. Usually the process is that you take the blood, then it goes to a lab and we get the lab results back, then an underwriter takes a look at the lab results. This is usually done in a two week time frame to get a rating. We were able to build models to automate all of this, and now, it happens in real-time. Somebody can apply online and get issued a policy right away. View full review »
MvpOfMac4841
Managing VP of Machine Learning at a financial services firm with 10,001+ employees
It has enabled our work force to be more efficient. View full review »
DataScie1afc
Data Scientist with 51-200 employees
We are using it for prototype projects. We have not deployed it. View full review »
Find out what your peers are saying about H2O.ai, Knime, Microsoft and others in Data Science Platforms. Updated: June 2020.
425,773 professionals have used our research since 2012.
reviewer1007100
Supervisor in Research and Development Area with 1,001-5,000 employees
Still on it. The idea is to save the cost of internal development but keeping enough flexibility to choose ML techniques and performance indicators. View full review »
Find out what your peers are saying about H2O.ai, Knime, Microsoft and others in Data Science Platforms. Updated: June 2020.
425,773 professionals have used our research since 2012.