Fighting Future Fraud:
A Strategy for Using Big Data, Machine Learning, and Data Lakes to Fight Mobile Communications Fraud

fighting-future-fraudWe have had the privilege of working with global leaders and visionaries on their strategies for future fraud, big data, and machine learning. What consistently comes up is that best-in-class carriers know the fraud types and fraud methods that they have been attacked with in the past, and they know the scale of fraud today. However, what keeps them up at night can be captured in a famous phrase by Donald Rumsfeld:

“There are known knowns. These are things we know that we know. There are known unknowns. That is to say, there are things that we know we don’t know. But there are also unknown unknowns. There are things we don’t know we don’t know.”

This translates to:

  • New Fraud – What new types and methods of fraud are criminals using that we don’t know about and that we aren’t detecting?
  • New Platforms and Technology – How are we going to use new big data platforms and machine learning to detect both old and new types of fraud in real time?
  • New Sources of Data – How are we going to protect subscribers from fraud in the new world of connected cars, connected home, mobile payments, IoT in utilities, and IoT in health and fitness?

What is critical to understand is that a) criminals are continually innovating; b) each subscriber will have many devices, many channels, and many potential attack points; and c) we need a better way to detect new fraud and protect customers and carriers in this new world – today in 2016, not in 2020.

In “Fighting Future Fraud”, we present a strategy for using big data, machine learning, and data lakes to fight mobile communications fraud – both current and future fraud.

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