How can artificial intelligence improve insurance pricing transparency and competitive positioning?

The insurance industry is under increasing pressure: a lack of transparency in competition, rising distribution costs and shrinking margins are hindering sustainable growth. At the same time, it is becoming clear that traditional approaches to product development and pricing are often too slow and not data-driven enough. This is precisely where a technology comes in that has already been validated in the market and is now entering a new phase.

At the centre is finsago, a fully developed AI system that can precisely replicate insurers’ pricing logic—without APIs or direct partnerships. Based on publicly available and lawfully collected data, pricing models from other providers are accurately simulated and made available in real time—with a forecasting accuracy of around 98 per cent. The system is scalable across markets like insurance, banking and energy, and offers high-impact applications or modules for pricing, product development and sales for insurers, banks, software companies, consultancies, broker pools and tech companies.

How are AI agents transforming insurance advisory, lead generation and sales conversion?

All price simulations, for example, feed an AI agent that bridges the gap to the end customer. As an intelligent, dialogue-based assistant, it combines advice with integrated pricing simulations and competitive comparisons. Users receive real-time indicative prices as well as transparent initial evaluations of offers. For insurers and sales partners, this means significantly improved pre-qualification, more efficient advisory processes and rising conversion rates. At the same time, risk selection can be carried out more precisely, which has a positive effect on the loss ratio.

Additional use cases for sales include a metasearch engine as a lead generator similar to “Google Flights for Insurance,” along with an advisor guide to support offline sales powered by metasearch.

How can insurers use AI to optimize pricing, improve combined ratios and accelerate product launches?

The system particularly demonstrates its strengths also in the area of Pricing & Product: Insurers can compare their own rates with the entire market in real time and immediately identify where price or benefit discrepancies exist. Product managers and actuaries are thus provided with a tool that not only creates transparency but enables concrete optimisation.

New rates can be simulated prior to launch—including their impact on volume, margin and risk. This data-driven decision-making framework significantly reduces uncertainty and drastically shortens development cycles. Reference benchmarks show that the Combined Ratio can be improved by several percentage points through targeted price optimisation, while simultaneously reducing the time-to-market for new products by up to 80 per cent.

  • Insurers can compare their own rates with the entire market in real time and immediately identify where price or benefit discrepancies exist.

Why is validated AI pricing technology becoming a strategic opportunity for insurers and technology partners?

The underlying technology has already been validated prior to 2026 by over 30 insurers, numerous market partners and more than 100 stakeholders involved.

The architecture is deliberately designed as a white-box system: full access to the code, modular integration into existing IT environments and maximum flexibility for custom development. Companies are thus acquiring not just a tool, but a scalable asset with long-term strategic value.

The fact that this technology is currently available is not due to a lack of market relevance. Rather, it is the result of follow-on financing that was not finalised in time and the ongoing restructuring of Mount ONYX GmbH and its brand finsago.

However, this very situation has created a unique opportunity: the fully developed and validated assets are now available under individual country licences. This gives companies the opportunity to build upon an existing system—without long development times, development risk and with immediate market access.

The message is clear: The journey of this technology continues and is entering a new phase—backed by solid fundamentals, proven use cases and concrete economic potential. For market participants looking to rethink their pricing and sales strategies, now may be the right time to get on board.