Autonomous AI assistants can help insurance organizations by speeding up and automating key processes so underwriters can boost their capacity. Here are three practical ways insurers can use AI assistants in underwriting workflows.
Much of the discussion around AI assistants' impact on different processes is still high-level. However, NeuralMetrics has ready-to-deploy autonomous AI assistant solutions to help expedite and automate key commercial underwriting functions. Here are several ways insurance organizations can use them.
1. Automate Risk Analysis for Commercial Applications
AI assistants can analyze large datasets to identify risk factors and exposures, going beyond subjective assessments. They can automatically construct and apply risk models, improving the accuracy and efficiency of risk analysis.
For processing commercial applications, it is critical to identify potential risks and pitfalls of a business before determining underwriting eligibility. Often, insurers rely on agents to answer risk questions, making the process subjective and dependent on the agents' and the insured’s understanding of potential exposures. Adding risk signals is time-consuming, and effectively integrating and evaluating new risks across the portfolio can pose a significant challenge.
An autonomous AI assistant can be deployed to identify and capture the risks or exposure signals associated with specific businesses. The digital assistant can automatically construct a model using synthetic and user-provided data to capture risk factors, then analyze subsequent submissions once the insurer confirms the model’s efficacy.
2. Determine Commercial Underwriting Risk Appetite
AI assistants can be trained on underwriting guidelines and assign business description codes automatically. They can assess risk and determine appetite, ensuring consistency and adherence to guidelines.
Commercial application submissions require assigning business description codes — based on NAICS, SIC, or custom codes. Those codes and further risk analysis determine whether a business is eligible for coverage. For both manual and straight-through processing, it is crucial to determine if an insurable business falls within or outside the insurer’s risk appetite. This information is dispersed across multiple sources and relies heavily on individual abilities to recall and accurately apply the guidelines.
An AI assistant can ingest various underwriting guidelines and learn how to evaluate submissions effectively. It automatically assigns business description codes according to the insurer’s guidelines and assesses risk to determine appetite. The assistant can be trained with new guidelines — similar to underwriter training — and automatically apply those to future submissions.
3. Streamline Premium Audit for Commercial Policies
AI assistants can automate the premium audit process by reviewing documents, identifying missing information, and ensuring compliance with state regulations. This reduces manual effort and improves audit accuracy.
Commercial audits require manual processing and review, involving auditors to meticulously examine state guidelines and documents provided by policyholders. An AI assistant can be equipped with comprehensive knowledge of state regulations and submission documents. Using the submitted documents and learning from them, it can autonomously conduct audits and identify incomplete or missing information.