Fraud Analytics Using Machine-learning & Engineering on Big Data (FAME) for Telecom. (arXiv:2311.00724v1 [cs.LG])

Telecom industries lose globally 46.3 Billion USD due to fraud. Data mining
and machine learning techniques (apart from rules oriented approach) have been
used in past, but efficiency has been low as fraud pattern changes very
rapidly. This paper presents an industrialized solution approach with self
adaptive data mining technique and application of big data technologies to
detect fraud and discover novel fraud patterns in accurate, efficient and cost
effective manner. Solution has been successfully demonstrated to detect
International Revenue …

analytics arxiv big big data billion data data mining efficiency engineering fraud industries low machine machine learning machine learning techniques mining paper rules solution telecom usd