The firm works with a number of group risk and healthcare insurers and will now incorporate this patented AI within its underwriting and risk-modelling.
This will integrate real-time health insights with predictive analytics, with the aim of improving the health and wellbeing of policyholders.
The company says this approach will benefit businesses, by supporting a healthier workforce, as well as improving underwriting precision for insurers.
It says traditional risk assessment tools rely on legacy datasets and backwards-looking models. In contrast YuLife’s preventive AI adopts a multi-layered approach that will stream biometric data from wearables, which include movements patterns, sleep cycles and heart rate variability.
This technology uses causal AI to infer relationships between behavioural signals and health outcomes and recommend early interventions. This approach will also use ‘reinforcement learning’ to adapt engagement strategies based on user response.
Once potential risks are detected, tailored interventions are offered to policyholders, from lifestyle recommendations and mental health support to pathways towards assistance from virtual GPs, EAPS and NHS services.
The technology also uses federated learning architecture to scale across populations, while preserving the privacy of individual data.
YuLife says this enables dynamic modelling of both individual and cohort-level risk enabling it to deliver hyper-personalised health recommendations at scale.
John Ronayne, lead data scientist at the provider, said: “This isn’t just AI on top of insurance, it’s a fundamental rebuild of the stack. We’ve designed an adaptive risk engine that continuously learns, engages, and optimises, which delivers value to users and underwriters in real time.”
Ronayne added that this preventative AI aligns with the UK government’s vision for a more proactive healthcare system. By integrating early risk detection and incentivised health improvements, it supports NHS efforts to reduce waiting lists and prioritise preventative care.
“We’ve trained our models on thousands of behavioural signals to answer a core question: what makes people stick with wellbeing habits?” said Ronayne. “The result is an AI engine that doesn’t just understand risk – it reshapes it.”
YuLife says it’s approach has been validated through its recent research project with the University of Essex, evidencing a direct correlation between increased engagement with its wellbeing features and reduced risk factors over time.
Ronayne says that by applying these findings, insurers using preventative AI can anticipate:
- Lower claims frequency and severity due to early intervention and risk mitigation.
- Enhanced underwriting models with predictive insights into mortality and morbidity trends.
- Increased policyholder engagement and retention, driven by a more interactive insurance experience.
Gen Re Life regional manager: UK and Ireland Jules Constantinou says: “The findings from YuLife’s study with the University of Essex and Innovate UK highlight an exciting evolution in how we think about workplace wellbeing and insurance risk.
“From a reinsurer’s perspective, the exploration of preventative behaviours and dynamic incentives offers promising signals for the future of group insurance—particularly in how we assess, engage with, and reduce long-term health risks. It’s encouraging to see how the firm is innovating in this space grounded in real-world data and academic rigour.”
Founder and CEO of YuLife Sammy Rubin added: “We’re building a system that doesn’t just help individuals live healthier lives, but also provides insurers with a more accurate, dynamic way to manage risk.”
“By continuously monitoring engagement and health data, preventative AI enables smarter underwriting decisions, more sustainable pricing models, and ultimately, lower claims costs.”
The provider says preventative AI can serve as a blueprint for the future of AI-integrated insurance and wellbeing, as both private and public sectors look to embed health AI at scale.
