Claims adjusters capture a significant amount of critical information within freeform claim notes throughout the lifecycle of a claim. These notes often contain observations, decisions, requests, follow-ups, risk indicators, customer commitments, medical updates, and next-step actions. Because this information exists as unstructured text, important tasks and commitments can be missed, delayed, or require manual review to identify and act upon. As claim volume increases, adjusters spend substantial time reviewing notes, determining required actions, and tracking follow-ups. This use case leverages AI and workflows to extract actionable information from adjuster notes and automatically generate tasks, reminders, follow-ups, recommendations, and workflow triggers.
Challenge
Critical information is often buried within adjuster notes, resulting in:
- Missed customer commitments
- Delayed follow-up actions
- Inconsistent claims handling
- Increased claim cycle times
- Higher supervisory review effort
- Reduced adjuster productivity
- Challenge Footer: Adjusters must manually review historical notes to understand what actions are needed, what commitments have been made, and what information is missing before progressing on a claim.
Solution
AI continuously analyzes adjuster notes and identifies:
- Action items and follow-up commitments
- Missing documentation