In the Media

In a Target Markets InfoSeries session, NeuralMetrics technical co-founder Marcus Daley talks about the impact of gen AI and role-based AI assistants on the underwriting processes of commercial program administrators and MGAs.

PropertyCasualty360 Insurance Luminary honorees cast aside dated industry stereotypes and push for innovation and fresh thinking around the most impactful issues of our time.

Chris Schrenk, NeuralMetrics chief underwriting officer, discusses how integrating AI technologies requires a shift in operational philosophy and some IT updates to optimize the value of generative AI.

With AI assistants GIA and ARKUS, insurer and MGA underwriting teams can efficiently refine in-appetite risk selection, enrich exposure analysis, improve pricing and quoting accuracy, and enhance service to agents and policyholders.

AI’s role in insurance represents a paradigm shift in how insurers approach risk assessment and other key processes. Open-source AI solutions, in particular, has been transformative, offering a new level of transparency and collaboration for insurers.

NeuralMetrics CTO Sathish Manimuthu lists four ways commercial insurance organizations can use role-based AI assistants in their underwriting processes to boost capacity and strengthen data-driven risk evaluation.

AI agents can support underwriters with nuanced logic to quickly accomplish a range of risk-assessment tasks. According to Sathish Manimuthu, NeuralMetrics CTO, AI assistants help to increase the precision and productivity of underwriting teams.

In commercial insurance, unintentional misinformation for underwriting is more common than fraud and can have significant consequences, such as inadequate coverage or inaccurate policy pricing. NeuralMetrics discusses how AI tools can help insurers reduce misinformation during risk analysis and selection.

Marcus Daley, technical co-founder of NeuralMetrics, discussed the transformative role of artificial intelligence in insurance underwriting — by generating accurate insights and risk assessments from sparse data.