Akur8’s transparent AI revolutionises InsurTech in Latin America

Akur8’s transparent AI revolutionises InsurTech in Latin America

Akur8, renowned for its cutting-edge insurance pricing solutions, is making significant strides in Latin America.

This expansion is driven by Akur8’s transparent machine learning technology, specifically designed to enhance predictive actuarial risk and rate models. These advancements are pivotal for insurers to develop robust and high-performance pricing models.

The benefits of Akur8’s models for insurance companies are manifold. They offer enhanced predictive performance and accuracy, crucial for swift market reactions and immediate commercial impacts. Moreover, these models maintain a high level of transparency and control, essential in today’s dynamic market.

A testament to Akur8’s growing influence in the region is its partnership with GNP Seguros, a leading player in Mexico’s insurance market. This collaboration underscores Akur8’s commitment to strengthening its presence in Mexico and its broader expansion goals in Latin America.

Brune de Linares, Chief Client Officer of Akur8, highlights the mission of their alliance with GNP Seguros. “In its alliance with GNP Seguros, Akur8 has a very clear mission: to provide state-of-theart models that automate the pricing process, guaranteeing transparency and efficiency at all times.”

Akur8 is revolutionising the non-life insurance sector with its Transparent AI, significantly enhancing insurers’ pricing capabilities. The modular pricing platform offered by Akur8 not only automates technical and commercial premium modeling but also ensures a tenfold reduction in modeling time. The platform improves the predictive power of models by 10% and increases the potential for loss ratio improvement by 2-4%.

Keep up with all the latest FinTech news here

Copyright © 2023 FinTech Global

Enjoying the stories?

Subscribe to our weekly InsurTech newsletter and get the latest industry news & research

Investors

The following investor(s) were tagged in this article.