Jewelers Mutual is one of the United States’ and Canada’s most established and trusted providers of affordable and comprehensive insurance for jewelers and consumers. As a leader in driving customer-focused innovation and providing the latest technology to a long-standing industry, Jewelers Mutual uses 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 consumers. The H2O.ai platforms have helped the company build unique models and recalibrate its rating systems based on the additional customer data generated, making its insurance rates more competitive.
The leadership at Jewelers Mutual recognized the need to invest in analytics, AI and machine learning for improving overall customer experiences. Their business relies on being able to effectively protect their jeweler customers’ businesses as well as on providing personal insurance directly to consumers – both with innovative customer experiences. Jewelers Mutual has been at the bleeding edge in adopting AI. They collected data already available from losses, customers as well as multiple other sources which weren’t tapped into before. Using a combination of on-premises and public clouds (Google Cloud Platform & Microsoft Azure) they started their AI journey a few years ago by implementing Gradient Boosting Machine, and then moving to an AutoML solution from DataRobot. Jewelers Mutual realized that they needed greater transparency of a solution and needed to have an explainable AI component. They began a new vendor evaluation.
We chose H2O AI because it with the transparency we needed into our machine learning process, much more flexibility than the other tools we evaluated, and the strongest machine learning explainability capabilities on the market.
Andrew Langsner, Senior Manager, Embedded Analytics at Jeweler's Mutual
After evaluating multiple solutions, Jewelers Mutual determined that H2O Driverless AI offered the right level of transparency, and had the advanced capability to explain and understand their models, with machine learning interpretability. Their first deployed model helped commercial underwriters understand their customers better and provided the reason codes as to why decisions were made using the machine learning interpretability capability. These insights then were made available through a web app to the underwriters. The interpretability and explainability of Driverless AI was instrumental in convincing the business stakeholders and also in making their own data scientists understand the algorithms better. They also found the H2O.ai community very helpful through the journey. Lastly, they found that deploying models using Driverless AI’s automatic deployment capability (MOJOs) made their data science efforts faster and easier.
The success that Jewelers Mutual has seen in adopting Driverless AI in their business is a testament to the fact that regulated industries can achieve real competitive advantage using AI. Following are some key results they have achieved so far:
- 1. Jewelry Stores partner with Jewelers Mutual for the overall protection of their assets.
- 2. Jewelers Mutual has been able to offer more competitive jewelry protection insurance rates to its customers.
- 3. AI insights are leading to some interesting outcomes such as during recent California wildfires and power outages, the Jewelers Mutual team was able to identify Jewelers that would need additional physical security personnel to protect their properties and inventory.
With the results generated by H2O.ai’s automatic machine learning platform, Jewelers Mutual is planning to implement new use-cases that will have a positive impact on their business and their relationships with their customers. As an example, determining the lifetime value of a consumer benefits jewelers and consumers in innovative ways. Additional use-cases include loss prevention, customer 360, and improving the customer journey using AI are all instrumental in making Jewelers Mutual an AI company. They are looking to turn this AI effort into a core capability of the company with the ability to quickly deploy and manage models very rapidly, which in turn benefits their customer’s overall experience.
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