The UK MGA sector has built its reputation on agility, with businesses often identifying opportunities early, entering specialist markets, responding to emerging risks and bringing products to market faster than traditional insurers.
Earnix’s latest report argues that maintaining this advantage is becoming more challenging as underwriters face increasing data volumes, evolving risks, greater transparency requirements from capacity providers and rising regulatory expectations.
In an article by Andy How, director of insurance for the UK and Europe at Earnix, the company argues that generic AI tools designed to generate content or automate simple tasks do not address the complexity of insurance decision-making.
How highlights the need for insurance-native AI, technology designed specifically around insurance decisions, including risk, pricing, underwriting, governance and compliance, while working across existing insurance systems.
The article argues that the next generation of agile MGAs will use insurance-native AI to support the expertise that has traditionally driven their success. Rather than competing on the use of chatbots, How suggests MGAs will need to focus on making better underwriting decisions, responding to changing market conditions, pricing risk more accurately and supporting underwriters with greater confidence.
Insurance involves a constant series of decisions, from quotes and referrals to renewals, fraud assessments and claims outcomes. According to How, these decisions require balancing profitability, customer experience, compliance and risk appetite.
While generic AI can understand language, the article argues it does not understand delegated authority, underwriting philosophy, appetite management or regulatory accountability.
How also highlights the launch of Earnix’s AIOS, which introduces an insurance-native orchestration layer connecting models, AI agents, workflows, governance and human expertise around insurance decisions.
Rather than replacing existing platforms, the article states that AIOS is designed to work across insurance systems and support decision-making across areas including pricing, underwriting, distribution and claims.
The article concludes that speed without governance is not agility. Applying AI at the right decision point, with the right level of human oversight, will be critical as insurers look to strengthen decision-making.
According to How, the opportunity for MGAs is to combine their specialist expertise with insurance-native AI that understands not only data, but decisions.
For more, read the full story here.
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