Evolving risk eligibility, shrinking talent pools, and tedious back-and-forth communications are among the challenges autonomous AI assistants can address in commercial underwriting.
From large workflows to shifting capacity to a widening talent gap, commercial insurance organizations need help streamlining critical risk evaluation processes and priorities. On top of these challenges, insurers must navigate increasingly high policyholder expectations to receive a fast and seamless experience.
Challenges Faced by Commercial Insurance Organizations:
- Evolving Risk Eligibility – Insurers often have specific risk appetites, making manual application reviews time-consuming.
- Shrinking Talent Pool – Attracting and training qualified underwriters is becoming increasingly difficult.
- Tedious Communications – Incomplete or inaccurate information from agents can lead to back-and-forth communication delays.
How AI Assistants Can Help:
- Efficiently Manage Risk Appetite – AI assistants can quickly analyze applications, identify in-and-out-of-appetite risks, and adapt to changing guidelines.
- Bridge the Talent Gap – By automating more straightforward tasks, AI assistants free up underwriters to focus on complex cases and training.
- Streamline Communication – AI assistants can flag missing information, reducing back-and-forth communication and improving the customer experience.
Because of their ability to ingest and apply expansive information, learn from previous experience, and process vast data quickly, autonomous AI assistants can help overcome some of these challenges.
- So much opportunity, so little time – There is substantial market growth potential, especially in commercial lines. However, insurers are particular about the types of businesses they write. Some will only write restaurants that don’t serve alcohol. Others might prefer contractors who perform interior rather than exterior work. It’s all a question of appetite. Manually reviewing applications to determine in- and out-of-appetite risks can be time-consuming. Updating eligibility guidelines in underlying insurer systems and technology can be cumbersome if legacy processes are used for the review and there is a change in appetite. AI assistants can quickly ingest underwriting guidelines and determine in and out of appetite risk, requiring underwriters to review only those that fall into a gray area. If insurers change their appetite, the new guidelines can be easily uploaded and learned by the assistant and then applied to submissions.
- Growing talent gap – The growing talent gap continues to be an issue throughout the insurance industry. For underwriting, the problem is exponential: not only are insurance organizations having issues attracting the next generation of workers, but underwriting is also a specialized skill set, and it takes time to train young professionals. Autonomous AI assistants can be trained on more straightforward underwriting tasks, freeing human underwriters to focus on more complex cases and spend time training new team members.
- Discordant communications with agency distribution channel – Inefficient information collection during the underwriting process can increase the time it takes for clients to acquire their policy. If an agent or broker provides the underwriter with incomplete or inaccurate information, there could be a lot of back and forth between the insurer and the agent as well as the agent and the customer to get the needed information. Autonomous AI assistants can flag circumstances where further policyholder data is required from agents, helping to eliminate back-and-forth communication with the underwriter. The assistants can also scan structured and unstructured data sources, reducing the information agents need to collect from their clients. AI assistants can provide a tighter quoting process and a better overall experience for agents and their customers.
Click here to learn more about NeuralMetrics autonomous AI assistants and how they can solve commercial underwriting workflow challenges.