A Gulf telecom operator's finance function - Contract intelligence
Telecommunications / Finance · Gulf
The shape of this problem
A human reads it and types it in again
The problem
Billing teams needed to validate invoices and partner revenue shares against complex contracts. The terms that determine a settlement are written in prose, negotiated per partner, and amended over time, so the correct figure is not derivable from the billing system alone - someone has to read the contract and apply it. At partner-portfolio scale that stops being verification and becomes sampling, and revenue leakage lives in the unsampled remainder.
What we built
We built a workflow that interpreted contract terms and applied them to customer billing and partner-settlement records, surfacing the exceptions for human review.
What moved
| Measure | Before | After |
|---|---|---|
| Partner settlements verified against contract terms | ~15% sampled | 100% |
| Analyst time per settlement review | 40 minutes | ~6 minutes, on flagged exceptions only |
| Discrepancy rate surfaced in the first full-coverage cycle | no prior measure | 2.3x the previously sampled rate |
Partner settlements verified against contract terms
The remainder is what sampling was hiding.
Figures are from the practice's own delivery records for the engagement named, measured against the process that preceded it.
What it turned on
Surfacing exceptions rather than recomputing settlements kept commercial judgment with the billing team while removing the reading burden that made full coverage impossible in the first place. Relevant to any operator whose revenue assurance is bounded by how many contracts a person can read.
- Service line
- AI Document Intelligence
Start here
Which of the four is yours?
Tell us the documents and the monthly volume and we will send the two closest records, with the figures behind each and what it would take to repeat them on your material.
You get a reply within one working day, from the engineer who would do the work.