Company News

Fadata, a global provider of core software solutions for the insurance industry, has unveiled its latest AI strategy, aimed at reshaping how insurance firms adopt and benefit from artificial intelligence.

UK-based startup Novee AI has raised £1.6m in pre-seed funding to expand its generative AI platform for commercial and specialty insurance underwriting.

Commercial auto InsurTech Cover Whale Insurance Solutions, a US-based provider of connected insurance for the commercial auto sector, has raised $40m in equity financing.

The insurance industry’s digital transformation is now a necessity. According to insights from Comarch, a leading digital transformation specialist, the decision to embrace change...

DXC Technology has now introduced DXC Assure Illustrations, a next-generation AI-powered SaaS product designed to revolutionise life insurance policy illustrations.

The Plan Group (TPG), a leading provider of insurance solutions focused on innovation and technology, has launched a new brand, eavi, to serve electric and autonomous vehicle technology providers.

The London Market’s enduring strength lies in its unique DNA, centred on expertise, face-to-face collaboration, and bespoke problem-solving. Novidea, a prominent technology provider within the market, highlights how this ecosystem’s future depends on combining tradition with innovation to stay competitive amid rising pressures from rival hubs like Frankfurt and Paris post-Brexit.

Venbrook Group, a fast-growing, independently owned insurance brokerage and risk management firm based in the United States, has entered into a strategic partnership with DB Insurance to launch a specialty habitational insurance product for multi-unit residential properties in California.

Honeycomb Insurance, a Chicago-based InsurTech company, has announced the expansion of its non-admitted insurance programme, Honeycomb Specialty, across all 18 states in which it currently operates.

Insurers and banks increasingly face complex analytical challenges as they strive to build accurate, transparent, and scalable predictive models. From managing high-dimensional data to avoiding overfitting, finding the right balance between model performance and interpretability is no small task, especially when dealing with categorical features.