By utilizing Akur8's Core Platform technology, the partnership seeks to improve LWCC's predictive modeling framework and produce superior underwriting insights. This action is intended to support LWCC's continuous growth ambitions and commitment to innovation by improving the accuracy and effectiveness of their pricing procedures.

Akur8's cutting-edge range of pricing and reserving solutions is transforming the non-life insurance sector. Their platform offers speed, performance, transparency, and dependability to insurers globally by fusing cutting-edge technology with actuarial experience to maximize business value.

By means of this collaboration, LWCC will make use of Akur8's exclusive machine-learning technology, which expedites the process of developing models and yields transparent Generalized Linear Model (GLM) results. This technology has the potential to completely change how LWCC approaches risk assessment and insurance pricing.

The solution from Akur8 was specifically designed with insurers in mind, improving pricing procedures for a range of industry verticals, including workers' compensation. Serving more than 250 clients worldwide, including well-known companies in the sector like AXA and Generali, Akur8 has a noticeable influence and presence in the market.

LWCC Chief Actuary Angela McGhee stated, "We are excited to work with Akur8. We will be able to create predictive models more quickly and precisely with the aid of their clear and simple models. We think this relationship has a lot of potential to help us with our growth objectives and help us make better pricing decisions.

"We are excited to collaborate with LWCC, a forward-thinking leader in workers' compensation insurance," stated Akur8 CEO Samuel Falmagne. Our cutting-edge AI-powered pricing solution will enable LWCC's staff to attain previously unheard-of levels of precision and efficiency in their pricing procedures, complementing their dedication to innovation and first-rate customer service and aligning with their current growth plans.