Fighting the fakes: How telcos can help

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As public suspicion about the veracity of online information increases, telcos could use their behavioural data to help Amazon, Google, Airbnb, Uber and others counter fraud, identity theft and fake reviews.


Format: PDF filePages: 43 pagesCharts: 9Author: David PringlePublication Date: June 2020

Table of Contents

  • Executive Summary
  • Introduction
  • Using big data to combat fraud
    • Account activity
    • Movement patterns
    • Contact patterns
    • Spending patterns
    • Caveats and considerations
  • Limited progress so far
    • Patchy adoption of Mobile Connect
    • Mobile identification in the UK
    • Turkcell employs machine learning
  • Big Internet use cases
    • Amazon – grappling with fake product reviews
    • Facebook and eBay – also need to clampdown
    • Google Maps and Tripadvisor – targets for fake reviews
    • Uber – serious safety concerns
    • Airbnb – balancing the interests of hosts and guests
  • Conclusions
  • Index

Table of Figures

  • Figure 1: Growing the market for telco identity services
  • Figure 2: The key telco data sets that can help Internet platforms to combat fraud
  • Figure 3: How Mobile Connect can be used to check an individual’s identity
  • Figure 4: Using multiple data points from a mobile network to check identity
  • Figure 5: The number of merchants on Amazon’s Marketplaces is growing rapidly
  • Figure 6: The gulf between Amazon’s review scores and the results of Which?’s tests
  • Figure 7: Some reviews on Google Maps may not be based on a first-hand experience
  • Figure 8: Google Support receives complaints about allegedly fake reviews
  • Figure 9: Multiple technological advances can be used to detect digital fingerprints

Technologies and industry terms referenced include: Airbnb, Amazon, Authentication, COVID-19, eBay, fake news, fake reviews, fraud, google, GSMA, identification, Machine Learning, Mobile Connect, Privacy, Trust, Uber