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How CSPs can combat fraud with AI and machine learning

As smartphone technology has advanced over time, the variety of telecoms fraud schemes targeting networks and customers has also expanded. In the early days, telecoms fraud involved threat actors exploiting payphones for free long-distance calls or trading stolen phone numbers. Today, fraudsters have refined their tactics, using methods like infiltrating phone systems or utilising counterfeit caller IDs to trick people into disclosing personal data, writes Kelvin Chaffer, the chief executive of Lifecycle Software. How CSPs can combat fraud with AI and machine learning

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Online Payment fraud losses to exceed $200 billion over next 5 years

A new study from Juniper Research has found that businesses in eCommerce, airline ticketing, money transfer and banking services, will cumulatively lose over $200 billion (€181 billion) to online payment fraud between 2020 and 2024; driven by the increased sophistication of fraud attempts and the rising number of attack vectors.

“Online Payment fraud losses to exceed $200 billion over next 5 years”

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AI is already delivering savings in the fight against fraud

Every business today is facing a host of new threats in the communications world. Telecoms service providers are no different, and the growing challenge that is VoIP and toll fraud is now estimated to cost £25.5bn globally; more than double that of credit card fraud, writes Carl Boraman, the director of strategic alliances and Tollring.

“AI is already delivering savings in the fight against fraud”

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How AI can help in the fight against fraud

Telecoms fraud is an expensive business, writes Katia Gonzalez, the head of fraud operations at BICS. According to the most recent Global Fraud Loss Survey by the Communications Fraud Control Association, fraud cost the industry a huge US$29.2 billion last year alone. This figure was down by more than 23% on 2015’s total, which is certainly encouraging, but the potential remains for the various types and methods of telecoms fraud to do some substantial financial and reputational damage.

“How AI can help in the fight against fraud”

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ML and AI – the future of revenue assurance and fraud management

Machine learning (ML) and artificial intelligence (AI) – algorithms that learn from data and make predictions – are unlocking opportunities for businesses in almost every field. If you’ve shopped online and suddenly seen advertisements for items suspiciously tailored to your taste, then you’ve seen the wonders of ML and AI at work. “ML and AI – the future of revenue assurance and fraud management”

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