A leading regional telecom operator, managing multiple interconnect and wholesale partnerships, processed thousands of invoices and transactions every day. However, revenue leakage due to billing discrepancies, delayed settlements, and frequent disputes with partners had become a persistent challenge. Manual reconciliation processes, disparate data sources, and limited visibility into partner billing cycles further compounded the issue directly impacting profitability and trust.

The Challenge: Revenue at Risk from Manual Dispute Handling

The operator faced increasing complexity in managing partner billing and settlements due to high transaction volumes and diverse charge types. Key challenges included:

• Frequent Disputes: High volume of mismatches in roaming, interconnect, and wholesale charge records.

• Manual Verification: Time-consuming and error-prone reconciliation of large billing datasets.

• Delayed Settlements: Extended resolution cycles leading to strained partner relationships and delayed cash flow.

• Revenue Blockages: Millions in revenue held up in unresolved disputes.

• Lack of Real-Time Visibility: Disconnected systems prevented instant reconciliation and monitoring.

This manual, fragmented approach significantly increased operational costs (OPEX) and reduced financial agility.

The Solution: AI-Driven Automated Dispute Resolution

Amantra deployed an AI-powered Dispute Resolution Engine seamlessly integrated with the operator’s existing billing and reconciliation systems. The solution leveraged machine learning and intelligent automation to streamline end-to-end partner settlement processes.

Key solution components included:

• Automated Data Matching: Cross-verification of call detail records (CDRs), invoices, and settlement files to ensure accuracy and eliminate manual matching.

• Discrepancy Detection: Machine learning algorithms identified mismatched transactions and categorized them by error type and priority.

• Root-Cause Analysis: AI-driven insights pinpointed whether discrepancies stemmed from partner reporting errors, network anomalies, or internal billing inconsistencies.

• Smart Workflow Automation: Common disputes were auto-resolved, while complex exceptions were intelligently routed to finance teams for review.

• Audit-Ready Reporting: Consolidated, traceable records supported compliance audits and accelerated partner settlements.

This intelligent automation framework transformed dispute management from a reactive, manual function into a proactive, self-healing ecosystem, significantly improving speed, accuracy, and financial visibility.

The Results: Faster Settlements, Stronger Revenues

• 60% faster dispute resolution with automated workflows.
• 45% reduction in revenue leakage from unresolved or delayed disputes.
• 30% lower OPEX in finance and reconciliation processes.
• Improved partner trust and relationships due to faster settlements.
• Better cash flow predictability and stronger financial governance.

Bottom Line: By automating dispute resolution, the telecom operator not only protected revenues but also turned partner settlement into a faster, transparent, and strategic advantage.