Applying AI to secure the payments ecosystem
Who is this presentation for?
- Developers, data scientists, machine learning engineers, AI engineers, architects, and executives
Today’s cybercriminals are well organized and well resourced. Criminals invest in artificial intelligence and computing power the same way we do, helping to grow their market into a $600 billion enterprise-strength industry—or almost one percent of global GDP.
As the network connecting 3.3B cards, 54M merchants, and 15,600 financial institutions, Visa is uniquely positioned to detect data breaches affecting merchants in a timely manner. For merchants in the ecommerce space, where financials can be stolen via malware injected into the merchant websites, at scale, the threat posed by malicious actors continues to mount. Between 2015 and 2017, the percentage of merchant attacks occurring in the ecommerce channel went from 27% to 76%. And as two-thirds of breaches go undetected for a month or more, reducing the window of exposure is vital. Visa uses AI, big data, and its suite of risk products to monitor the ecommerce universe and detect breaches faster.
Chiranjeet Chetia and Carolina Barcenas provide a high-level overview of the problem formulation, specialized data engineering, and several aspects of the model architecture, which includes traditional machine learning and deep learning, graph analytics, and semisupervised learning techniques such as generative adversarial network (GAN).
- A basic understanding of machine learning and deep learning concepts
What you'll learn
- Learn the application of AI techniques and the deployment of AI-based payment product
Chiranjeet Chetia is a lead data scientist at Visa. With the scale of data Visa observes every day, he’s immersed into finding meaning and value from this data. To this end, he often collaborates with stakeholders across business and technology at Visa to conduct proof of concepts with the end goal of creating data- and AI-powered products or services for Visa. He has 10+ years of experience in the payments domain, most of it in the realms of ecommerce. Previously, he had various stints from managing SMB merchant risk to managing global collections strategy at PayPal. He holds an MS degree in statistics from Virginia Tech, where he also was a Provost Bioinformatics Fellow.
Carolina Barcenas is the vice president of data science and AI for data products at Visa. She’s responsible for exploring and developing advanced ways for leveraging data to create business value for Visa through artificial intelligence techniques. Carolina is also Austin’s coleader of Visa Women in Technology as well as the organizing force behind the community college intern program that focuses on nontraditional candidates. She’s worked both in industry and academia and has over 20 years of experience designing predictive analytical solutions in fintech. Previously, she worked at PayPal, where she was responsible for managing the risk of small and medium ecommerce sellers. She holds a PhD in applied statistics from the Georgia Institute of Technology as a Fulbright Scholar.
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