How does AI identify fields in a bordereau?
AI identifies fields in a bordereau by analysing column headings, values, surrounding context and relationships between data points. This allows it to recognise business concepts such as policy references, premiums, claims values and dates even when different coverholders use different terminology.
Key takeaways
- AI does not rely only on exact column-name matching.
- It uses context, examples and field values to infer business meaning.
- Ambiguous fields should be flagged for review rather than accepted silently.
- Field identification works best when paired with a defined target schema.
A large part of bordereaux processing is simply working out what each field means.
This sounds basic, but it is often where the work begins.
Different coverholders use different terminology, abbreviations and spreadsheet layouts. The same business concept may appear under several labels, and some labels may be unclear without looking at the values underneath.
AI can help because it can interpret the field in context rather than relying only on an exact match.
Field names are useful but not enough
Column headings are the obvious starting point.
If a column is called Policy Number, it is probably a policy identifier.
But delegated authority bordereaux rarely stay that simple.
The same concept may appear as:
- Policy Ref
- Certificate ID
- Contract Number
- Policy No
- Insured Reference
Traditional import routines often need each variation to be mapped manually.
AI can compare the label with the values in the column and the wider structure of the bordereau.
Values provide important clues
The contents of a field often reveal its meaning.
A column containing values such as GBP, USD and EUR is likely to represent currency.
A column containing dates may represent inception date, expiry date, transaction date or date of loss depending on the surrounding information.
A column containing positive and negative numeric values may require more interpretation before it can be mapped safely.
AI uses these clues to infer the likely business meaning.
Context matters
Field identification improves when AI can see relationships between fields.
For example, a date column next to premium values may represent a transaction or inception date. A date column next to claims reserves may represent date of loss or notification date.
Context does not remove the need for validation, but it improves the ability to handle unfamiliar formats.
Confidence and ambiguity
Some fields are obvious.
Others are not.
A field labelled Amount could refer to premium, commission, tax, claim paid, reserve movement or another financial value.
A good AI-enabled process should not pretend that every field is certain.
Where confidence is low, the field should be highlighted for review.
Operational considerations
Field identification should be linked to the organisation's target schema.
The question is not simply, "What is this column?"
The better question is, "Where should this column go in our required structure, and how confident are we?"
That framing keeps the process focused on delegated authority outcomes rather than technical extraction alone.
Example
A bordereau contains a column labelled Ref.
On its own, the label is ambiguous.
The AI reviews the values beneath it, sees that they follow the same pattern as policy references in previous bordereaux, checks the surrounding columns and maps it to the target Policy Reference field.
Because the confidence is high, the field is accepted, while other ambiguous fields are routed for human review.
FAQs
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Can AI identify fields with unusual names?
Yes, in many cases. AI can use the values and context around a field to infer its meaning even when the heading is unusual.
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What happens if a field is ambiguous?
A well-designed process should flag ambiguous fields for human review rather than silently mapping them to the wrong target field.
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Does AI need examples to identify fields?
Examples can improve consistency, but modern AI can often infer field meaning from context. Organisations should still validate outputs against their own business rules.
See it on your own bordereaux template
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