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 cyber criminals are well organized and well-resourced. Criminals are investing in artificial intelligence and computing power the same way we are, 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 with two-thirds of breaches going undetected for a month or more, reducing the window of exposure is vital. At Visa, we’re using AI, big data and our suite of risk products to monitor the ecommerce universe and detect breaches faster.
In this talk, we will provide a high-level view 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 semi-supervised learning techniques such as GAN.
Prerequisite knowledgeBasic Machine Learning/Deep Learning concepts Curiosity about AI at scale
What you'll learnApplication of AI techniques 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 is immersed into finding meaning and value from this data. To this end, he often collaborates with stake-holders across business and technology at Visa to conduct proof-of-concepts with the end goal of creating data & 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. Prior to joining Visa, he had various stints from managing SMB merchant risk to managing Global Collections strategy at PayPal.
He holds an M.S. degree in Statistics from Virginia Tech where he also was a Provost Bioinformatics Fellow.
Carolina Barcenas is Vice President of Data Science and AI for Data Products at Visa. She is 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 co-leader of Visa Women in Technology as well as the organizing force behind the community college intern program that focuses on non-traditional candidates.
She has worked both in industry as well as academia and has over 20 years of experience designing predictive analytical solutions in fintech. Prior to joining Visa, she spent 7 years at PayPal where she was responsible for managing the risk of small and medium e-commerce sellers.
She holds a Ph.D. in Applied Statistics from the Georgia Institute of Technology as a Fulbright Scholar.
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