Webinars and Blogs
In this course at Central Banking on "Unlocking Cutting-Edge Innovations for Central Banks: The Key to Data and Emerging Technologies," I’ll present a case study on the use of quantum algorithms for payment settlement optimization. This study demonstrates how quantum computing, an area gaining global attention, can help enhance the liquidity efficiency of high-value payment systems through the efficient reordering of payments.
In this payment systems broadcast session organized by FNA, my coauthor and I present how a layered machine learning framework can tackle challenges in transaction monitoring for payment systems. With the vast volume of transactions processed daily, identifying anomalies is akin to finding a needle in a haystack. Discover how our innovative machine learning framework enhances transaction monitoring.
I spoke at the session on AI in Payments at The Payments Canada SUMMIT! In this session we explored the vast potential of payment data and machine learning in shaping payment analytics, research, and policy. Joined by Opher Baron from the University of Toronto, Kevin Marshall from Interac Corp., and Kimmo Soramäki from FNA. Together, we will delve into the opportunities and challenges from industry, policy, and research perspectives.
Seminar, May 2024: Guest seminar at he M2SDiscovery Interdisciplinary Research Institute at the Wilfrid Laurier University- Seminar Link
In this seminar at the MS2Discovery Interdisciplinary Research Institute for Mathematical and Statistical Modelling in Scientific Discovery, Innovation, and Sustainability at Wilfrid Laurier University in Waterloo, I had the opportunity to present my research on 'Improving Safety and Efficiency of Payment Systems using AI and Quantum Computing. The discussion centered on leveraging advanced technologies to enhance the security and efficiency of payment systems.
In this online seminar hosted by the The Federal Reserve Board's Technology Lab (TechLab) , I had the opportunity to present my paper titled "Finding a Needle in a Haystack: A Machine Learning Framework for Anomaly Detection in Payment Systems." I demonstrated the application of machine learning techniques to enhance the safety of payment systems.
Seminar, Mar 2024: Guest lecture at the Queen's University on Applied machine learning - Course link
In this online lecture at the Queen's Universities course on ECON, I presented an overview of applied machine learning techniques using examples of my research projects on payments and banking, and discussed the opportunities and challanges of using ML.
Seminar, Jan 2024: Guest lecture at the at the University of Toronto's Data Sciences Institute on Applied machine learning - Course link
In this online lecture at the University of Toronto's Data Sciences Institute course on ML, I presented an overview of applied machine learning techniques using examples of my research projects on payments and banking, and discussed the opportunities and challanges of using ML.
Seminar, Nov 2023: Guest lecture at the Indian Institute of Management Ahmedabad (IIMA) on Payments Data and Machine Learning: Opportunities and Challenges - Webinar link
In n the age of AI and Big Data, witness the profound impact on the payments ecosystem, accelerated by rapid digitization in the wake of COVID-19. This seismic shift generates a surplus of high-frequency payments data, aligning seamlessly with advancements in AI, ML, and Quantum Computing. This seminar provides a comprehensive overview, unveiling practical use cases spanning supervised, unsupervised, and reinforcement learning. Explore the promising synergy between payments data and advanced analytics
In the modern digital economy, transactions encompass the exchange of products, services, or money, which are settled through various electronic systems, including wholesale, retail, and instant payment systems. Quantum computing is emerging as a transformative tool for optimizing the efficiency of such payment systems, offering the potential to significantly enhance liquidity and settle transactions more effectively.
In this article, I talk about nowcasting, the process of predicting the present. It is an exciting practical application of supervised machine learning that has yet to be widely known. First, the article introduces where nowcasting is useful and then talks about how ML can be used, with a focus on macroeconomic applications.
Webinar, Mar 2023: Guest Lecture at University of Toronto's DSI on Payments Data and Machine Learning - Closed session - weblink
In this online guest lecture at the University of Toronto's Data Science Institute, I presented an overview of payments data and machine learning using some examples of my research projects, and discussed the opportunities and challanges of using ML for payments research.
Webinar, Feb 2023: Improving the Efficiency of Payments Systems Using Quantum Computing - Webinar link
In this Quantum FinTech Webinar series organized by Rethinc. Labs at University of North Carolina, Kenan-Flagler Business School, we present our paper in which, we test the potential of quantum computing for payments settlement optimization in high-value payments systems.
In this article, I summarize key lessons from 2023 AEA's continuing education session on ML and Big Data for Economic research and analysis with a focus on the following key questions: 1. when ML is useful in economics? 2. which ML models are recommended? and 3. how to use ML for your economic applications?
In this short article, I share my experience of learning AI/ML and building a career in data science. I also provide links to various resources I use to strengthen my knowledge and deepen my understanding of these topics.
In our conversation on his alternate data podcast show, Mark and I discuss how the Bank of Canada is using payments data in innovative ways to make macroeconomic predictions and the outlook for central banks using various other alternative data for economic policy and research.
Webinar, Oct 2021: Estimating policy functions in payments systems using reinforcement learning - Webinar link
In this webinar at the Economics of Payments X conference (EoP-X), I present our paper (joint with many coauthors) about using reinforcement learning to estimate the optimal liquidity management decisions of the banks participating in high-value payments systems.