Robot Pointing on a Wall

March 4, 2024

By Luba Orlovsky

In the rapidly evolving world of ML and AI, the power of predictive analytics is undeniable. Yet as we harness this new power, we must also navigate the complex landscape of fairness and ethics. We must also do all we can to create equal opportunities and outcomes across different groups of individuals, regardless of their race, gender, age, or other sensitive attributes.

What I See for 2024 and Beyond

February 1, 2024

By Earnix-Team

As 2023 fades from view and 2024 comes into focus, Reuven Shnaps, Earnix Chief Analytics Officer, takes a step back to assess where pricing, rating, and underwriting stand today, and where they may be headed.

5 Key Lessons Learned for Maximizing the Value of AI in the Enterprise

October 22, 2023

By Earnix-Team

AI has captured imaginations, investments, and headlines around the world, from boardrooms to corporate strategy sessions to the popular media. It has already affected the way we do business, how we shop for goods and services, and the way live our daily lives.

Automatic Generalized Linear Models (GLM) in Insurance & Banking

March 28, 2023

By Luba Orlovsky

To make a cake, you need to have specific ingredients: eggs, milk, flour, etc. The same applies to a model, you need to have variables such as age, tenure, and price.

Earnix Summit 2018: Key Findings From The Industry Frontlines

November 19, 2018

By Jonathan Moran

Our annual Summit held two weeks ago in London was one of the most successful Earnix events ever! Over two days, 28 presentations were delivered that included financial services industry innovations, best practices, and customer successes. While most of the presentations focused on the future of the ...
DataRobot complements Earnix with Machine Learning Capabilities for Decision Support

October 1, 2018

By Jonathan Moran

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 m ...