A new algorithmic framework called Budget-First Tariff Recommendation (BFTR) aims to help telecom operators offer more personalized and cost-effective plans without overcharging customers. BFTR integrates eight different strategies, including two hybrid approaches that prioritize budget and volume. The authors claim that their approach ensures zero overcharging by aligning prices with a reference catalog price. Experiments on a dataset of 974 Nigerian MTN market customers showed that several strategies achieved optimal results in terms of budget usage, volume, and utility, while maintaining zero overcharging. --- Why it matters: This matters to researchers in AI because it provides a new framework for optimizing telecom plans without sacrificing customer satisfaction or revenue. The authors' use of mathematical formalization and proof-based guarantees demonstrates the potential for applying similar techniques to other resource allocation problems. Source: https://arxiv.org/abs/2608.18723