17 Mar

Real-Time Fraud Detection on Google Cloud

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17th March, 2-3pm GMT

Companies are losing an average of 7% of their annual expenditure to fraud, costing the UK £110 billion a year, and £3 trillion globally (1). In particular, applications fraud and contactless payments fraud are rapidly increasing, with Covid-19 creating a fertile ground for fraudsters adapting their tactics online. 

Thankfully, the field of real-time fraud detection has become even more sophisticated, scalable and cost-efficient. In our latest webinar, Datatonic and Google Cloud are teaming up to catch payment fraudsters in real-time with machine learning. 

  • (1) Financial Cost of Fraud 2018 report – Analysis of 40 types of expenditure with a total value of £15.59 trillion in 49 organisations from 10 countries.
  • Fraud Challenges What the top fraud challenges are in Insurance, Capital Markets, Retail Banking, Payments and other Customer-Facing industries are.
  • Datatonic Case Study How we detected over 90% in fraud value (whilst maintaining high-quality user experience) for a leading payments provider on Google Cloud Platform. When to choose "Buy vs Build" when it comes to your detection models, and how to drive speed, scalability and accuracy.
  • Datatonic Live Demo How to alert common fraud behaviours in real-time, such as inconsistent customer details, multiple accounts, multiple charges and unusually large purchases, through a live demo built by Datatonic.
Sufyaan Kazi
Customer Engineer, Google Cloud
Suf has been in the Cloud Technology space for the last 7 years, working with clients within various industries helping them migrate to Cloud Native architectures and frameworks. In the last 3 years at Google, he has helped many finance customers embrace better designs for processing data, building cloud native apps and helping bring agility to their business. Suf recently worked with Datatonic to help build a real-time fraud detection system for a mutual client.
Alvaro Silva-Santisteban
Head of Strategy, Datatonic
Alvaro leads Datatonic’s Strategy team, laying the path in novel business areas and strengthening Datatonic's position as a leader in AI. He has a technical background in engineering followed by an MSc in Applied Maths from the University of Oxford. Alvaro joined Datatonic from McKinsey&Company where he worked as a consultant serving multiple industries.
Nora Petrova
Principal Machine Learning Engineer, Datatonic
Nora is a Principal Machine Learning Engineer with a background in computer science and physics. Nora presents a strong combination of 8+ years of experience in data science and software engineering, and helps clients with their toughest modelling and engineering challenges.
Who Should Attend

This event is for decision-makers and practitioners in Data Science, Analytics & Engineering, Fraud Prevention / Detection, Risk, and Operational roles in Insurance, Capital Markets, Retail Banking, Payments and other Customer-Facing sectors.

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