The most common form of machine learning requires huge quantities of data for training models, and customer data is particularly highly valued.
But with growing sensitivities over data privacy and breaches, organizations are under regulatory and consumer pressure to have processes in place safeguarding assets such as customer data.
Under the General Data Protection Regulation, organizations are required to develop a strategy to prove compliance or face hefty fines.
The DataRobot EU Cloud ensures European organizations adhere to enhanced data sovereignty requirements without sacrificing any enterprise-grade capabilities.
“The combined power of DataRobot and AWS have transformed our ability to build and deploy models in a fraction of the time, allowing us to deliver customer-based pricing when underwriting insurance policies,” said Paul Davies, Data Science Manager at UK-based Domestic & General in a statement.
The Ireland-hosted cloud platform, built on AWS, provides full transparency into the automated machine learning process and full compliance with GDPR in four ways: prediction explanations; model documentation; safeguards to prevent bias; and feature effects.
Feature effects is a straightforward way to explain to stakeholders and regulators how a specific feature impacts the overall prediction from the model and is based on a partial dependence analysis technique.
Aside from the AWS clouds in EU and North America, DataRobot can also be installed on-prem or on private clouds.
In April, Saudi SME financier AlRaedah Finance announced it will be using automated machine learning from DataRobot to develop and deploy predictive models for AI without the data scientists.