The Earnix Blog: Resources for Insurance and Banking Leaders

Mercedes Benz Parked in a Row

June 4, 2026

By Will Ely

Auto lenders can no longer treat pricing and credit as separate decisions. This post explores why modern risk-based pricing requires a connected, full-funnel approach that balances affordability, portfolio risk, profitability, and customer behavior - and how unified analytics, simulation, and personalized offer structures can help lenders compete more effectively.

Colorful Cubes And Puzzle Piece

April 28, 2026

By Yuval Ben Dror

Discover how KPI-focused data monitoring helps insurers and banks distinguish statistical noise from real business risk by connecting data drift directly to outcomes like loss ratio, conversion, and profitability.

Selective Focus Photography of Train

April 15, 2026

By Earnix Team

Part 2 of our agile pricing series shows how lenders can turn pricing strategy into execution through automation, predictive analytics, and integrated technology that speeds deployment and improves performance.

Men on Horses

March 18, 2026

By Earnix Team

Lending markets are changing faster than traditional pricing processes can handle. In Part 1 of this series, we outline a practical blueprint for consumer and auto lenders to begin building agile pricing operations, from foundational data and demand models to quick wins that create momentum for long-term pricing sophistication.

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.

Wooden Blocks Men Stack on Top of Each Other Making a Pyramid

October 19, 2025

By Yuval Ben Dror & Eyal Bar Natan

Discover how Earnix’s Hierarchical Level Selector intelligently merges categorical hierarchies to create cleaner, faster, and more accurate predictive models. This innovative feature helps insurers and banks simplify complex data structures, improving both model performance and explainability.