The Earnix Blog: Resources for Insurance and Banking Leaders
November 18, 2024
By Earnix Team
The Earnix 2024 Industry Trends report reveals an industry at a crossroads: while insurers are eager to harness AI’s transformative potential, adoption lags behind ambition.
November 12, 2024
By Earnix Team
Earlier this fall, the Earnix Excelerate 2024 Conference was held in London, UK, attracting over 300 attendees from around the globe. This event has become a pivotal gathering for professionals in the property and casualty (P&C) and general insurance sector, providing a platform to discuss emerging industry trends, share innovative best practices, and learn about the latest technological advancements in pricing, rating and underwriting solutions.
November 4, 2024
By Earnix Team
Earnix is proud to announce the release of our third-annual insurance report, The Earnix 2024 Industry Trends report. This year’s report presents these findings and key insights in five different categories: modernizing operations, artificial intelligence and analytics, underwriting, regulatory compliance, and collaboration and innovation.
October 22, 2024
By Earnix Team
Modern pricing and rating solutions offer a wide range of advanced features and functionality that empower insurers to optimize pricing strategies with precision. From dynamic pricing to predictive analytics, today’s solutions provide leading carriers the tools they need for turning real-time insights into a new competitive advantage.
August 14, 2024
By Earnix Team
Pricing intelligence solutions, powered by artificial intelligence (AI) and machine learning (ML), are transforming insurance, enabling carriers to make smarter, data-driven pricing decisions in real-time to stay competitive and maximize profitability.
July 15, 2024
By Earnix Team
AI is revolutionizing the insurance industry today by enhancing underwriting, claims processing, customer service, and product development. Yet the rapid advancement and widespread of adoption of AI in the insurance industry leads to new questions about the potential for biases and discrimination – as well as AI’s overall implications for insurers.