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AI use case · Revenue & billing

Interconnect Billing Reconciliation & Revenue Leakage Detection

Interconnect billing discrepancies between domestic and partner operator records go undetected for weeks, causing revenue disputes, delayed settlements and significant leakage.

Anomaly DetectionRecord Matching
HighBusiness priority
Revenue & billingDomain
4Main data sources

The problem

Interconnect billing discrepancies between domestic and partner operator records go undetected for weeks, causing revenue disputes, delayed settlements and significant leakage.

The AI approach

ML-driven matching of inbound and outbound interconnect CDRs. Anomaly detection on settlement volumes. Automatic dispute identification with evidence packaging for partner resolution.

How it works

  1. 1
    Match

    Match own traffic records with partner invoices and settlement files.

  2. 2
    Score

    Score differences by size, partner and route.

  3. 3
    Explain

    Point to the routes, periods or rates driving the gap.

  4. 4
    Dispute

    Raise evidence-backed disputes with partners.

Data it uses

Interconnect Billing SystemMediationCDR RepositoryPartner Settlement Data

How to measure value

Practical tips

Standards & references

Data governanceUse governed, consented data only
Responsible AIExplainable, monitored, human-in-the-loop

Related pages

This page describes generic industry practice and public standards. It is not based on, and does not describe, any particular vendor's product or operator's systems.