Abstract: The world of tech moves at an unpredictable speed. Yet, the financial industry has struggled to keep pace. Payments is big business, but the existing infrastructure is outdated, slow, and expensive—it hasn’t been updated for 40 years. Blockchain technology has created boundless opportunities to improve the payment system by utilizing digital assets and data insights to make global transactions more efficient. This talk will dissect the elements of a transaction, and highlight the processes and applications used to yield results and improve cross-border payments. By analyzing payments technology using data science, we can challenge the existing system to highlight solutions that enable more efficient, reliable, and rapid transfers. We will also explore the emerging solutions addressing consumer needs for speed and transparency in the world of payments. This session will showcase the impact of digital assets on our global infrastructure as the financial industry continues to embrace these new technologies. Data scientists and researchers interested in learning about applications and use cases in the payments and blockchain field will benefit from this talk, as Jen will break down the anatomy of a payment (the size, prefunding, speed, and cost), and its journey across borders. Jen will share use cases highlighting how data science and machine learning help identify areas of improvement in the cross-border payments process.
By the end of the talk, attendees will have:
- An understanding of the various elements that make up a cross-border payment
- Unique ideas for generating solutions using data mapping
- Insight into the effectiveness of digital assets as a solution to the existing financial infrastructure.
Bio: Jennifer Xia is a data scientist at Ripple, a payment technology company named one of the 50 Smartest Companies by MIT and the recipient of the World Economic Forum’s Technology Pioneer Award. Prior to joining Ripple, she worked at Sharethrough, where she analyzed the downstream effects of improving user match rates through data research, and at NERA Economic Consulting. She holds a BA in Economics from the University of Chicago.
Data Scientist | Ripple
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