As the adoption of generative AI and large language models (LLM) is expanding, insurance organizations must pinpoint the use cases where these technologies will have the most impact.
Generative AI and large language models (LLM) have been the buzz in every industry, with insurance organizations in 2024 exploring ways to leverage this technology for business improvement. According to a recent piece by Mitch Wein of Datos Insights, insurers have four paths to consider when opting for generative AI:
- Develop and build their own LLMs.
- Collaborate with partners to refine a pre-existing LLM.
- Leverage LLM capabilities from an insurance solutions provider.
- Forgo LLMs and instead build a small language model.
Datos suggests that most insurers will opt for route number three, partnering with solution providers to integrate LLM capabilities into their workflows. To benefit from LLMs and generative AI capabilities, Datos advises that decisions on technology incorporation should be strategic, with specific use cases outlined to add substantial value.
At NeuralMetrics, we apply AI-generated data across the policy lifecycle, enabling insurance organizations to identify and price risk effectively, improve productivity, and sustain competitive differentiation. Our key use cases include:
– Predictive Underwriting: Evaluate risk quality and make informed decisions about premium, policy issuance, and terms and conditions.
– Lessors’ Risk Assessment: Verify business conditions at a specific property with just an address, confirm hours of operation, and assess risk-appetite fit in seconds.
– Book Roll Analytics: Identify in-appetite accounts and facilitate efficient due diligence of books of business by validating business classification with the bulk upload feature.
– Business Acquisition: Drive sales by identifying suitable and profitable leads, and prequalify accounts before they become policyholders.
– Exposure Monitoring: Pinpoint exposure changes in the insured’s business operations and circumstances by closely monitoring the book of business.
– Premium Audit: Support premium audit and portfolio integrity with transparent risk insights – to verify the classification of policyholder operations quickly, accurately, and cost-effectively.
– Renewal Support: Ensure no significant changes to insureds’ risk profiles before auto-renewing policies, gain insights into cross-selling opportunities, and minimize premium leakage.
For more information on NeuralMetrics’ use cases, check out our information sheet.