Enterprise MLOps: Boost model velocity, ease compliance
The insurance industry is rapidly changing. Connected homes, cars, and a variety of other devices have created an explosion of data. Small insurtech firms are leveraging AI/ML to exploit changing consumer preferences. As a result, insurance organizations are faced with increasing demands for AI/ML to drive new product offerings and operational enhancements, while still adhering to regulatory requirements.
Domino’s Enterprise MLOps platform helps actuaries and data scientists at the world’s largest insurance organizations:
- Increase operational efficiencies to reduce cost and improve customer experiences.
- Develop new products to adapt to changing consumer preferences such as recommendation engines and usage-based insurance products.
- Identify, test, and manage risk across the entire portfolio including underwriting, pricing, fraud detection, and regulatory compliance.
Why insurers depend on Domino
Domino helps leading insurance organizations industrialize their data science practices. The Domino Enterprise MLOps platform works within your complex infrastructure and abstracts away the complexities that get in the way of scaling data science. With Domino, your teams will be more productive and meet regulatory requirements that are time-consuming and difficult to achieve.
Governance and Reproducibility-+

Support governance and compliance without sacrificing speed
Domino centralizes quantitative research and data science on a governed platform providing full reproducibility to drive innovation while reducing operational and regulatory risk.
Benefits:
- Support good Model Risk Management practices to easily comply with regulatory and audit requirements
- Rapidly and easily validate model results prior to deployment
- Improve data scientist productivity by automatically capturing all model assets
Accelerate Research-+

Get more models into production
Domino safely and securely accelerates the data science lifecycle by making data scientists more productive, compounding knowledge and integrated workflows.
Benefits:
-
Collaborate with peers by easily comparing and iterating on results to rapidly innovate
-
Explore data, create, validate, publish and monitor models within a unified platform
-
Enable repeatable processes and workflows that get models into production faster, enable automated monitoring, retrain and republish models more often
Open and Flexible Tools-+

Use your preferred tools
Domino supports a wide variety of open-source and commercial tools and languages, including Python, R, SAS, and MATLAB. As technology changes, easily add new tools to future-proof your research platform.
Benefits:
- Onboard new users faster with an environment that's as familiar as their local laptop
- Utilize the latest open-source innovations to drive competitive advantage from data science
- Accelerate your migration to the cloud to be more agile, without sacrificing efficacy or safety
Scalable Infrastructure-+

Get more power on-demand
Domino provides self-service access to powerful, elastic infrastructure with just a few clicks. Easily access distributed compute frameworks and NVIDIA GPUs for the most computationally-hungry research.
Benefits:
- Handle any volume of data and code, with automatic and integrated version control
- Perform complex modeling on powerful machines using the most popular distributed frameworks, including Spark, Ray, and Dask, without having to perform DevOps activities
- Seamlessly integrate with internal or third-party systems via robust APIs

Support governance and compliance without sacrificing speed
Domino centralizes quantitative research and data science on a governed platform providing full reproducibility to drive innovation while reducing operational and regulatory risk.
Benefits:
- Support good Model Risk Management practices to easily comply with regulatory and audit requirements
- Rapidly and easily validate model results prior to deployment
- Improve data scientist productivity by automatically capturing all model assets

Get more models into production
Domino safely and securely accelerates the data science lifecycle by making data scientists more productive, compounding knowledge and integrated workflows.
Benefits:
-
Collaborate with peers by easily comparing and iterating on results to rapidly innovate
-
Explore data, create, validate, publish and monitor models within a unified platform
-
Enable repeatable processes and workflows that get models into production faster, enable automated monitoring, retrain and republish models more often

Use your preferred tools
Domino supports a wide variety of open-source and commercial tools and languages, including Python, R, SAS, and MATLAB. As technology changes, easily add new tools to future-proof your research platform.
Benefits:
- Onboard new users faster with an environment that's as familiar as their local laptop
- Utilize the latest open-source innovations to drive competitive advantage from data science
- Accelerate your migration to the cloud to be more agile, without sacrificing efficacy or safety

Get more power on-demand
Domino provides self-service access to powerful, elastic infrastructure with just a few clicks. Easily access distributed compute frameworks and NVIDIA GPUs for the most computationally-hungry research.
Benefits:
- Handle any volume of data and code, with automatic and integrated version control
- Perform complex modeling on powerful machines using the most popular distributed frameworks, including Spark, Ray, and Dask, without having to perform DevOps activities
- Seamlessly integrate with internal or third-party systems via robust APIs
One of our priorities is also how quickly we can update models. With Domino, we can make any necessary changes in just a day, compared to a month previously, which will enable faster innovation as well.
/admiral-group-logo.webp)

Pushing the Innovation Pedal in a Conservative Industry
Learn how Allstate increased model velocity while retaining full reproducibility to weave fact-based decision-making into the fabric of their organization.
Read the Allstate case study
Delivering New Fraud Detection Capabilities in Weeks, Not Months
A global Fortune 500 leader was able to improve fraud detection and risk management while also increasing data science productivity—ultimately paving the way toward faster innovation at scale.
Read the case study
Personalized Recommendations, Real-Time Claims Processing and Pricing
Learn how ConTe.it delivers €2 Million in Incremental Annual Profit with Domino while also increasing model velocity.
Read the ConTe.it case studyRecommended resources
"If we hadn't invested in Domino first, I wouldn't have been able to set up a team at all, because you can't hire a high-skilled data scientist without providing them with the state of the art working environment."
Chief Analytics Officer, Large Insurance Organization
Anju Gupta, VP Data Science & Analytics at Northwestern Mutual, is a big believer in establishing model governance practices early, and she shares her thoughts on the topic in the episode. Plus, she talks about some surprising roles on her data science team and the unique value that comes from pairing actuaries with data scientists.
In this panel discussion, hear from Meg Walters, who leads Allstate’s Analytics Center of Excellence, as she talks about how Allstate has scaled the Analytics CoE into a model building factory using Domino’s Enterprise MLOps platform to deliver massive productivity gains for data scientists.