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DataRobot complements Earnix with Machine Learning Capabilities for Decision Support

Jonathan Moran

October 1, 2018

  • AI
  • Customer Centricity

The Challenge

Many financial institutions today are looking to implement sophisticated machine learning models into their existing analytical systems – for use in analytical pricing and product personalization initiatives. They want to use machine learning libraries that they have often created in machine learning platforms, such as DataRobot.

The Partnership at-a-Glance

The newly announced Earnix and DataRobot partnership brings a new level of precision, insight, time to market, and competitive edge to professionals at financial institutions around the world.

The joint solution allows models created in DataRobot’s automated machine learning platform to be easily integrated into Earnix’s analytical platform. The combination empowers business analysts, data scientists, and actuaries of all skill levels to build and deploy state-of-the-art DataRobot machine learning models within Earnix’s pricing and risk modeling platform in a fraction of the time of traditional modeling methods. Users of the Earnix solution then combine these machine learning models with traditional regression analytical models for improved analytical insight.

For instance, a pricing professional can leverage a machine learning model from DataRobot inside of Earnix in place of or combined with a Generalized Linear Model (GLM) to more accurately model risk and demand. Combining traditional GLM with machine learning models is an industry leading capability Earnix refers to as hybrid modelling. An product professional can import a Gradient Boosting Machines or other machine learning models to create better tailored pricing or product packages to be deployed from Earnix.

How the Integration Works

In the latest version of Earnix, a user can easily leverage DataRobot models. To do this, a user downloads a codegen file of the model from their DataRobot environment and uploads it into Earnix using the “Import DataRobot Model” functionality in the “Create Model Version” wizard. After the import, models are fully available for scoring and can be used exactly like any other model built in Earnix. Additionally, they can be further explored and analyzed using the full Earnix modeling toolbox, used in pricing exercises, and in the Earnix real-time module.


Benefits of the Joint Solution

Leveraging DataRobot to automatically create machine learning models for use inside of Earnix delivers a number of benefits for pricing or product professionals at financial services institutions, including:

Use of Machine Learning Models for Analytical Decision Support. For organizations with limited exposure to machine learning, leveraging DataRobot for model creation provides the ease-of-use and automation needed for beginning your machine learning initiatives. For the more advanced organization, DataRobot provides a wide variety of model types and the breadth of model creation needed in today’s quick paced marketplace.

Acceleration of Time-to-Market and Insight. With the DataRobot integration, users can quickly take advantage of big data volumes, predict outcomes with added accuracy, and accelerate time-to-market insight. Agility and the ability to respond to market trends is essential in today’s fast paced business environments. With Earnix and DataRobot, you can join multiple DataRobot models inside of the Earnix system, allowing the user to take pricing projects from development to production in a matter of seconds via the Earnix rating engine capabilities. Building and deploying machine learning models can be completed in a fraction of the time it takes in manual coding platforms. With the ability to store and iterate upon existing models, less manual rework is required. This results in quicker time-to-insight.

Expanding Machine Learning Breadth and Depth in Your Organization. The joint solution makes it easy for organizations to evolve their use of machine learning for modeling risk, demand, and propensity. Analysts can create more precise and robust analytical models that determine the perfect price and product combination, not just the preferred one. The partnership between Earnix and DataRobot will add synergies and support to the unique strengths of each product.

Earnix and DataRobot in Action – Joint Use Cases

The two solutions can be used to accomplish many analytical tasks, including customer data enrichment and analytical boosting, the prediction of product choice and utilization, the ability to optimize competitive rank on aggregator portals, the analysis of customer Inquiries and interactions using natural language processing algorithms, predicting mid-term cancellations, and the improved prediction of actuarial costs.

Find Out More To find out more about the new partnership and the value it can provide to your organization, please review the additional materials below.

DataRobot webpage on Earnix Earnix and DataRobot Integration Demo
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Jonathan Moran