Claims Adjusters and ExaminersvsInsurance Underwriters

until most of the change has landed

High adoption

until most of the change has landed

High adoption

Photo-based estimating, straight-through processing and AI triage are automating routine claims, leaving adjusters the complex, contested and human cases.

AI significantly automating risk assessment and decision-making.

1. Photo-based damage estimation
2. Straight-through processing
3. Predictive triage and fraud scoring
4. Document extraction and file summarisation
5. Claimant expectations for speed
6. Expense-ratio pressure

1. Availability of Vast Customer & Risk Data
2. Advancements in Machine Learning & Predictive Analytics
3. Demand for Faster Quoting & Policy Issuance
4. Competitive Pressures in the Insurance Market
5. Rise of Insurtech & AI-Native Competitors
6. Need for More Granular & Personalized Risk Pricing
7. Increased Computational Power
8. Improved Fraud Detection Capabilities
9. Regulatory Push for Data-Driven Decision Making (with caveats)
10. Desire to Reduce Manual Underwriting Costs

1. Liability investigation
2. Negotiation and settlement
3. Model oversight and audit
4. Medical and repair literacy
5. Claimant communication
6. Regulatory knowledge

1. Data Analysis & Interpretation
2. AI Model Understanding & Validation
3. Risk Assessment & Critical Judgment (for complex cases)
4. Communication & Negotiation Skills
5. Business Acumen & Industry Knowledge
6. Ethical AI & Regulatory Awareness
7. Adaptability & Continuous Learning
8. Portfolio Management & Strategic Thinking

1. Guidewire ClaimCenter
2. CCC Intelligent Solutions
3. Tractable
4. Shift Technology

1. Zesty.ai (for property risk)
2. Shift Technology (for fraud detection & claims automation)
3. Cytora (AI-powered commercial underwriting)
4. Guidewire Underwriting Management / Duck Creek Policy
5. Internal Proprietary AI Models