February 12, 2024
By Earnix Team
Many insurers are now getting back on track after suffering some of the worst years in their history. Rate increases are also expected to play a role, especially for home insurance premiums. In 2024, many insurers are planning to increase national premiums in the low double digits. These gains can come at the cost of real pains for home and auto insurance customers. Policyholders will now face much higher, even exponential prices for home and auto insurance.
February 7, 2024
With seemingly optimistic conditions ahead, 2024 could be the year insurers get back on track. As they do, we predict they’ll take advantage of the following trends and technology developments.
February 1, 2024
By Reuven Shnaps PhD
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.
January 29, 2024
By Osnat Yanushevsky Yacoby, Chief Customer Officer, and Doug Wing, Head of Professional Services for North America, Earnix
We live in a world of high and ever-increasing expectations. In our personal lives, we expect products and services to meet and exceed expectations. In our professional lives, especially when dealing with vendors and partners, the same applies.
January 15, 2024
By Luba Orlovsky
In the bustling world of insurance, a quiet revolution is unfolding. It's not led by charismatic CEOs or flamboyant industry disruptors. Instead, it's powered by something far more enigmatic: machine learning (ML). But there's a catch – these oracles are often inscrutable, their predictions shrouded in mystery. This is where the concept of ML explainability enters the discussion, turning the spotlight on the inner workings of these digital soothsayers.
January 10, 2024
By Reuven Shnaps PhD, Earnix Chief Analytics Officer, and Chen Ben Gal, Industry Senior Data Scientist
We will focus on some of the technical aspects behind the generation of Synthetic Data, present some detailed information as to its effectiveness in mimicking original data statistical properties, and present some interesting applications which go beyond replication of the original data.