What Modern Commercial Pricing Leaders Do Differently

April 20, 2026

By Earnix Team

Commercial insurers are shifting from static pricing processes to continuous, enterprise decisioning—improving speed, accuracy, governance, and cross-functional alignment in a more complex market.

Agentic AI for Insurance Agents and Bank Advisors: A Practical Guide

March 17, 2026

By Earnix Team

Agentic AI is reshaping financial services by going beyond answering questions to taking action. For bank advisors and insurance producers, it can automate routine tasks, deliver real-time insights, and enable more personalized client service while supporting compliance and productivity.

Will AI Replace Call Center Jobs in Banking and Insurance?

March 16, 2026

By Earnix Team

AI is reshaping call center operations in banking and insurance by empowering agents with real-time insights, automation, and personalized recommendations. The result is better customer experiences, greater efficiency, and stronger business performance - without removing the human touch.

Women in the Meeting Room

March 15, 2026

By Earnix Team

Bancassurance is not disappearing—it is evolving. As fintechs, neobanks, and embedded finance reshape customer expectations, banks and insurers must combine trusted advisory relationships, ecosystem partnerships, and intelligent technology to deliver more personalized, digital-first experiences.

The Anatomy of Modern Annuity Pricing: Closing the Gap Between Projection and Execution

February 25, 2026

By Earnix Team

Many pricing teams rely on advanced actuarial models capable of forecasting lifetime cash flows, capital impact, and profitability across multiple economic scenarios. The analytical capability exists. The difficulty arises when those projections must be translated into live pricing rules.

Colorful Cubes And Puzzle Piece

January 29, 2026

By Luba Orlovsky & Shilo Horev

Earnix Automatic GLM preserves the transparency and regulatory trust of traditional GLMs while automating complex feature engineering to capture non-linear effects, enabling explainable, auditable models with stronger predictive performance and faster deployment in regulated financial environments.