AI in insurance
Insurance companies use AI to speed up underwriting and claims work. AI can also affect pricing and customer interactions. This page explains what “AI in insurance” means and where it shows up. This is educational only. It is not insurance advice.
What “AI in insurance” means
In insurance, AI often means models that score risk for underwriting and tools that process documents for claims. It can also mean generative AI that drafts summaries and emails (see NAIC’s overview).
Common uses (where it shows up)
- Underwriting support: estimate risk using application and history data.
- Claims triage: sort claims and extract key fields for an adjuster to review.
- Fraud detection: flag patterns that look suspicious for a human investigator.
- Claims review tools: speed up claims work with tools like Tractable or Sprout.ai (still needs human checks).
- Fraud signals: flag suspicious patterns with tools like Shift Technology or FRISS.
- Call/email summarization: turn long conversations into short notes.
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What AI is good at (and bad at)
- Good at: spotting patterns in claims and fraud signals. (NIST AI RMF)
- Good at: extracting key fields from documents.
- Bad at: making fair decisions on its own. People must stay accountable.
Risks you must take seriously
- Made-up facts: the model can sound confident and be wrong. (NIST AI 600-1)
- Unfair outcomes: a bad model can treat groups differently.
- Pricing harm: a wrong score can affect a real person’s cost.
How to use AI safely (simple checklist)
- Do not paste personal customer data into tools you do not control.
- Require human review for denials, pricing, and high-impact decisions.
- Test on edge cases and monitor errors. (OWASP LLM Top 10)
How rules and regulators think about it (high level)
- Old rules still apply (privacy, discrimination, record keeping). (OECD AI Principles)
- For high-impact uses, regulators expect transparency and controls.
Questions to ask before you trust a tool
- What data did it use, and can we audit it? (NIST AI RMF)
- Can a person appeal or override the result?
- Can we export our data if we switch tools?