AI for insurance
Dense documentation, regulated processes and high volume. It works well when done with control.
Where the problem is
Long policy documents, manual processing and regulation that leaves no room for error.
Where the problem is
Long policy documents, manual processing and regulation that leaves no room for error.
- Checking coverage takes experience and time.
- Document processing consumes hours of qualified people's time.
- Any automated answer has to be traceable back to the document.
- Personal data imposes clear limits.
How I approach it
Assistants with traceability, and automation with human review at the critical points.
- A coverage assistant that cites the policy document and version.
- Extraction and classification of claims paperwork.
- Service agents with immediate handover to a handler.
- Human approval before any action with real effect.
- A full conversation record for audit.
Three ways to see it working
Coverage lookup
An answer with the exact clause and its validity date.
Document processing
Extracting data from the claim form, validating it and recording it.
Call analysis
Classifying reasons and spotting complaints early.
From the first meeting to real use
In phases, with a decision at the end of each one. There is no need to commit to a year up front.
Phase 1
Selecting the corpus and the process with the best impact/risk ratio.
Phase 2
A closed pilot with full human supervision.
Phase 3
Evaluation on real cases and threshold tuning.
Phase 4
Gradual expansion with audit and cost control.
Indicators we agree on before starting
No invented percentages: the metrics are set at the start and measured with your own data.
Processing time
Across the covered case types.
Traceability
Every answer linked to its source document.
Administrative load
Freed up for work that needs judgement.
What it is built with
Other situations
Does this problem sound familiar?
Tell me how it shows up in your company and I will tell you whether it fits and where I would start.