Right now there is a lot of talk about business models that give people what they want based on the data accumulated about them. For example, take this article about the rise of ‘faster than real-time’ predictive business models. But is there an obvious flaw? Many dislike the idea of huge amounts of personal data being collected, just so a business can forecast our purchasing habits. But might some users wreck the system, by deliberately pumping garbage into the analysis? Cory Doctorow, the author and internet activist, thinks that privacy concerns will provoke some customers to rebel; see here. For example, CyanogenMod is an aftermarket firmware distribution for Android phones that aims to enhance privacy, and it also has an experimental feature where randomly-generated data is supplied whenever an app asks for personal data (such as current location). So here is a very relevant question for any business intending to make money from user data: what is their prediction for the amount of data that will be deliberate garbage?
Predicting Garbage In, Garbage Out
During his career, Eric has been a Director of Risk Management for a national telco, the Chief Executive of the Risk & Assurance Group, a Chief Marketing Officer for a software business, a consultant, a public speaker and the publisher of Commsrisk since its launch in 2006. Look here for more about the history of Commsrisk and the role played by Eric.
The comms providers that Eric has worked for include Qatar Telecom, Cable & Wireless, T‑Mobile, Sky and Worldcom. In addition to his proficiency at speaking about the current scamdemic, Eric is also a qualified chartered accountant and a subject matter expert in consumer protection, enterprise risk management, fraud prevention, data integrity and billing accuracy. Eric was the lead author of Revenue Assurance: Expert Opinions for Communications Providers, published by CRC Press. He can be reached through the contact form on this website.
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The Commsrisk Global Fraud Dashboard

Our Global Fraud Dashboard uses AI-powered search to collate, update and visualize data about scams and other network abuses from around the world. New charts are added each month. See it here.
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