How to Supercharge Roaming Settlement with AI

AI (Artificial Intelligence) is transforming the roaming industry, accelerating efficiency, enabling automation, and driving insights for better decisions, among other benefits. Ultimately, AI is a tool that enhances the important work of roaming managers and financial personnel. MACH has been working on incorporating AI into the services relied by roaming managers and financial users. We see AI playing a valuable role in the immediate future in four key areas:

Reporting Assistance

MACH has integrated AI into its reporting tool, One BI, enabling users to access intelligent insights through simple user interaction via a chatbot. AI makes it much easier to find meaningful information by generating easy-to-understand visualizations, reports, and dashboards. It provides insights and recommendations that support informed decision making. 

Maximizing the value of analytics tool can be challenging for roaming managers and financial users. They often require a high degree of technical ability and knowledge, which can take a long time to develop due to the many different features and capabilities of each analytics platform. AI accelerates the user learning curve, reducing the gap between novice and experienced users. It simplify operations and help users take the necessary actions to improve their roaming business. Roaming managers and financial users sometimes cannot afford to spend valuable time learning the ins and outs of their analytics tools. We see AI playing a crucial role in reducing friction in reporting and analytics, providing users with valuable insights, intelligent recommendations, automated reports, and powerful data visualizations.

Forecast

At MACH, we see a strong AI use case in helping users create efficient and accurate forecasts. Forecasting is key to developing profitable commercial strategies, so it is essential that forecasts are accurate and available in time to make well-informed business decisions. MACH AI simplifies forecasting by allowing users to generate predictions directly from any dataset within the MACH clearing platform, leveraging AI’s ability to perform complex calculations instantly and eliminating the need for coding or data science expertise. Users can request forecasts in natural language, such as “predict volumes for the next quarter,” and MACH AI will automatically choose the appropriate model and settings. This capability adds significant operational efficiencies for roaming managers, improving forecast accuracy while reducing the risk of human errors. For more advanced use cases, users can easily customize forecasts by specifying the prediction horizon, preferred forecasting method, or other settings as needed through simple, conversational commands. This makes MACH AI a powerful tool for democratizing predictive analytics across teams, and speeding up decision-making. 

Clustering

Another strong use case for AI in roaming is automated segmentation of roaming traffic into clusters. MACH leverages AI to detect IoT traffic even when IMSI ranges, APN lists, or IMEI information are unavailable. We have also been using clustering to estimate Travel eSIM traffic based on patterns . AI has made these tasks incredibly efficient, improving our ability to segment Travel eSIM traffic. At MACH, we only anticipate the importance of clustering to rise. As more users choose to use Travel eSIMs and more devices rely on internet connectivity and roaming, the ability to segment this traffic is essential for monetization. 

MACH’s convergent billing platform, One Agreement, supports all agreement types within a single, integrated view. The future of commercial roaming settlement will involve many different charging models and agreement types, as roaming managers look to adapt their business to customer behaviour and shrinking margins. These revenue-boosting strategies will rely on accurate traffic segmentation and clustering. AI will play, and already is playing, a significant role in clustering roaming traffic.

Anomaly Detection

Anomaly detection can be used to enhance quality management, for example, by identifying network congestion, degradation, and outage incidents. These events can be linked to revenue losses. It can also be used to improve fraud prevention and detect anomalous usage behaviours. MACH already uses AI in anomaly detection, offering unrivaled efficiency in flagging incidents of fraud and service disruptions as they occur. This rapid detection is crucial to enable quick responses and prevent significant revenue loss. Prolonged service disruption can significantly impact the customer experience, increase bill shock and lead to customer churn. AI is already essential to anomaly detection operating efficiently and enabling timely responses to disruptions and fraud.

Discover how MACH AI Analytics can help you make smarter, data-driven business decisions.