AI & automation in claims
Key criteria to ensure AI works in claims through practical use cases and strong governance
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Identifying where automation can streamline claims processes and where AI can support better claims decisions, improving productivity, effectiveness and client outcomes
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Selecting practical use cases that balance quick wins with longer-term business value
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Avoiding common implementation traps, including poor data quality, weak workflow integration, unclear ownership and solving the wrong problem
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Designing governance and human oversight so accountability for decisions remains aligned to risk appetite
Followed by roundtable discussion and benchmarking






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