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The ‘Agentic AI driven billing dispute resolution’ Catalyst shows how a multi-agent AI platform can help communications service providers detect billing anomalies, investigate root causes and resolve disputes before they escalate into customer complaints.
The best dispute is the one which never happens
Billing disputes remain a persistent source of operational cost, revenue leakage and customer dissatisfaction. They typically arise in fragmented environments spanning BSS, CRM, mediation platforms and external partner ecosystems, where data is distributed, not always synchronized and difficult to correlate quickly.
The Agentic AI driven billing dispute resolution Catalyst introduces an AI-powered autonomous billing dispute management solution to address this challenge. Handling disputes often involves customer care, billing, IT and finance teams, with repeated manual checks across systems and limited visibility of previous investigations. That creates duplicated effort, longer resolution times and inconsistent outcomes.
The commercial impact can be significant. Delayed or unclear resolutions increase churn risk, particularly in bill shock scenarios, while billing errors and write-offs contribute to lost revenue and higher operational costs.
The Catalyst uses a multi-agent AI platform in which specialized AI agents collaborate to detect anomalies, investigate root causes and recommend or execute resolutions across systems. This shifts billing dispute handling from a reactive, complaint-led process to a proactive, automated and scalable model.
The solution integrates with BSS and OSS using TM Forum Open APIs to access customer, billing and product data in real time. The questionnaire submission identifies TMF629, TMF620, TMF622, TMF678, TMF681, TMF634, TMF699 and TMF701 as the Open APIs supporting standardized, interoperable data exchange across CRM, billing, product, network and campaign systems.
By combining real-time anomaly detection with automated investigation and guided workflows, the platform can help teams resolve issues faster, reduce manual rework and provide customers with clearer outcomes. The use case-driven development approach is intended to connect the technical architecture directly to measurable business impact and faster time-to-value.
The project team expects the solution to reduce billing complaints by up to 35% through proactive anomaly detection and outreach to the customer, to accelerate resolution times by up to 40% through automation and guided workflows. It also aims to reduce operational costs related to billing complaint handling by up to 30%.
For operators, the benefits include improved first-contact resolution, better workforce utilization and more consistent investigation processes. For customers, the value lies in faster, clearer and fairer resolution of financial disputes.
Pooja Towakel, Principal Coordinator - Digital CX transformation at Mauritius Telecom, said the Catalyst represents “a key opportunity to transform billing dispute management by reducing manual effort and improving resolution speed and consistency.” She added that participation allows Mauritius Telecom to help develop “a scalable AI-driven approach that enhances customer trust and operational efficiency, while contributing to industry best practices.”
For the wider industry, the Catalyst demonstrates how complex, cross-system workflows can be automated using standards-based interfaces and AI-driven orchestration. The same approach could be applied to other customer operations where data is fragmented across domains and faster, more transparent decision-making is required.
