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AI and Machines Learning Innovations from H2O.ai Drive Personalized and Better Experiences for Jewelers and Consumers
MOUNTAIN VIEW, California, Dec. 18, 2019 /PRNewswire/ -- H2O.ai, the open source leader in artificial intelligence (AI) and machine learning (ML), today announced Jewelers Mutual, one of the United States' and Canada's most established and trusted providers of affordable and comprehensive insurance for jewelers and consumers, has chosen its award winning AI platforms to provide AI and machine learning capabilities to better serve its customers. As a leader in driving customer-focused innovation and providing the latest technology to a long-standing industry, Jewelers Mutual is using H2O-3 open source and H2O Driverless AI to deliver exceptional customer experiences, prevent losses, and provide better protection and policies for both jewelers and customers.
"We have been in the jewelry insurance business for over 100 years, and our leadership team has been looking to raise the bar for technology-driven innovation in the industry. After two years of experimentation with AI and machine learning, we came to place a high value on model transparency and explainability. Our business end-users demanded it. The initial AI platform we used was lacking in this area so we began searching for a new platform," said Andrew Langsner, Senior Manager, Embedded Analytics at Jewelers Mutual. "After evaluating several solutions in our search for the ideal AI platform, we chose H2O.ai because it provides us with the transparency we needed into our machine learning processes, much more flexibility than the other tools we evaluated, and the strongest machine learning explainability capabilities on the market. H2O.ai provides new avenues of innovation and allows us to build quality and insightful ML tools for our business stakeholders."
Since working with the H2O.ai platforms, the company has been able to build unique models and recalibrate its rating systems based on the additional customer data generated, making its insurance rates more competitive. In addition to its underwriting, customer experience and claims use cases, the company is also applying analytics to identify ways to improve security, particularly for commercial customers. For example, during recent California wildfires and power outages, the team was able to identify customers that would need additional physical security personnel to protect their inventory. These critical use cases have streamlined the data science process and helped the team save valuable time and resources.
"Jewelers Mutual is using H2O Driverless AI to automatically build machine learning models for predicting customer lifetime value and prevent high severity losses and suspicious claims, amongst other high value use cases," said Sri Ambati, Founder and CEO of H2O.ai. "Jewelers Mutual is the leader in jewelry and insurance, has been using data and predictive analytics to improve its customer experiences and is not new to AutoML. H2O Driverless AI provides an easy on-ramp to operationalize and explain its machine learning models, increasing the productivity of its data science teams. We are thrilled to be its team's chosen trusted partner in the AI transformation journey and hope to make them an AI company, further establishing their technological leadership in the space."
H2O-3, A Leading Open Source AI Platform
H2O-3 is the leading open source, scalable and distributed in-memory AI and machine learning platform. H2O-3 supports the most widely used statistical and machine learning algorithms including gradient boosted machines, generalized linear models, deep learning and more. H2O-3 also has an industry leading AutoML functionality that automatically runs through all the algorithms and their hyper-parameters to produce a leaderboard of the best models.
H2O Driverless AI: AI to do AI
H2O Driverless AI empowers data scientists to work on projects faster and more efficiently by using automation and state-of-the-art machine learning to accomplish tasks in hours instead of weeks and months. By delivering automatic feature engineering, model validation, model tuning, model selection and deployment, machine learning interpretability, time-series and automatic pipeline generation for model scoring, H2O Driverless AI provides companies with a data science platform that addresses the needs of a variety of use cases for every enterprise in every industry.
About H2O.ai
H2O.ai is the open source leader in AI and automatic machine learning with a mission to democratize AI for everyone. H2O.ai is transforming the use of AI to empower every company to be an AI company in financial services, insurance, healthcare, telco, retail, pharmaceuticals and marketing. H2O.ai is driving an open AI movement with H2O, which is used by more than 18,000 companies and hundreds of thousands of data scientists. H2O Driverless AI, an award winning and industry leading automatic machine learning platform for the enterprise, is helping data scientists across the world in every industry be more productive and deploy models in a faster, easier and cheaper way. H2O.ai partners with leading technology companies such as NVIDIA, IBM, AWS, Intel, Microsoft Azure and Google Cloud Platform and is proud of its growing customer base which includes Capital One, Nationwide Insurance, Walgreens and MarketAxess. H2O.ai believes in AI4Good with support for wildlife conservation and AI for academics. Learn more at www.H2O.ai.
About Jewelers Mutual
Jewelers Mutual Group was founded in 1913 by a group of Wisconsin jewelers to meet their unique insurance needs. Today, Jewelers Mutual offers products and services nationwide and throughout Canada that enable jewelry businesses to run safe, secure, and successful operations. Consumers also put their trust in Jewelers Mutual to protect their personal jewelry and the special moments it represents. The group's strong financial position is reflected in its 32 consecutive ratings of "A+ Superior" from A.M. Best Company. To learn more, visit JewelersMutual.com.
Media Contact:
Russ Castronovo
press@H2O.ai
408-391-9632
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