Matmut Derives Data Insights 3 Times Faster
Customer Company Size
Large Corporate
Region
- Europe
Country
- France
Product
- DataRobot AI Cloud
- MLOps
- AutoML
Tech Stack
- Jupyter notebook
Implementation Scale
- Enterprise-wide Deployment
Impact Metrics
- Productivity Improvements
- Customer Satisfaction
Technology Category
- Analytics & Modeling - Predictive Analytics
- Platform as a Service (PaaS) - Data Management Platforms
Applicable Functions
- Business Operation
Use Cases
- Predictive Maintenance
- Demand Planning & Forecasting
Services
- Data Science Services
About The Customer
The Matmut Group is a major player in the French insurance market with more than 3.9 million insured members and 7.4 million insurance policies under management. It offers a complete range of personal and property insurance products along with financial and savings services. The Matmut Group currently has 6,300 employees and generated a turnover of more than 2.4 billion euros in 2021. The company relies heavily on data to elevate nearly every area of the company, but was facing challenges in deriving insights within the limits of stringent privacy regulations.
The Challenge
Matmut, a major player in the French insurance market, relies heavily on data to elevate nearly every area of the company. However, the company was facing challenges in deriving insights within the limits of stringent privacy regulations. Matmut’s data lab was building predictive models with a single Jupyter notebook, a process that was manual and required considerable coding. This approach was not efficient and did not foster collaboration between data scientists and the business. The company was in need of a single solution that could reduce the effort and enable collaboration.
The Solution
Matmut deployed DataRobot AI Cloud to automate the end-to-end lifecycle, from data preparation to modeling to monitoring. The platform delivered efficiency gains across every step of the process. On the front end, Feature Discovery automatically generated new features based on the dataset, expediting data preparation. The platform also automated modeling with machine learning, along with deployment and updates. The combined time savings across the lifecycle amounted to a three times productivity gain over the team’s previously manual approaches. Matmut also embraced DataRobot University to increase users’ proficiency on the platform. On average, each team member has taken 10 courses covering various aspects of the solution.
Operational Impact
Quantitative Benefit
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