Jorge Cruz Lopez
University of Western Ontario and Financial Network Analytics
De Nederlandsche Bank
Serafin Martinez Jaramillo
CEMLA and Banco de México
The financial system is rapidly evolving. New payment systems, specialized exchanges and vast amounts of data that were inconceivable a few years ago are now commonplace in financial markets. These innovations are occurring rapidly and in the context of unprecedented market, environmental and geopolitical developments. To ensure efficient and stable markets, financial institutions and regulators require innovative approaches to assess and manage risks and opportunities in the current environment.
Financial market infrastructures (FMIs) are at the core of these developments. Due to their importance to financial stability, FMIs have become the object of international regulatory reforms, and research in this area has increased significantly in recent years. This special issue of The Journal of Financial Market Infrastructures includes five well-crafted and innovative research papers on payment systems, clearing houses and exchanges. The selected papers take advantage of advances in big data and data science to conduct analyses that increase our understanding of FMIs and their role in the wider economy. In what follows, we overview the main ideas and contributions discussed in each paper and conclude with a sincere note of gratitude to those who made this special issue possible.
Our first paper, “Using payments data to nowcast macroeconomic variables during the onset of Covid-19” by James T. E. Chapman and Ajit Desai, proposes an innovative machine learning approach to nowcast macroeconomic variables using retail payments data. The authors’ methodology represents a significant improvement on traditional nowcasting techniques, which are usually based on linear models and, because of their functional form restrictions, are less accurate during financial crises. Importantly, the authors show how their technique could be used to assess the state of the economy during the current Covid-19 pandemic.
Continuing in the area of payment systems, in “An empirical analysis of bill payment choices”, the second paper in the issue, Anneke Kosse uses Canadian data to determine which payment instruments are employed by consumers to pay their bills and the factors driving bill payment behavior. She finds that bill payment behavior varies by bill type and that there is no dominant payment method for all consumer groups. Instead, the payment methods adopted by consumers vary by demographics, financial conditions, technology adoption and point-of-sale payment habits. This research is useful for understanding the incentives that may play a role when introducing new alternatives such as digital payments, or when designing retail payment systems.
Our third paper, “Predicting payment migration in Canada” by Anneke Kosse, Zhentong Lu and Gabriel Xerri, proposes a methodology to predict payment migration when new payment infrastructures are introduced to replace old ones. The authors use a discrete choice demand estimation approach to uncover the preferences of consumers and financial institutions, and they apply their methodology to Canada, which is in the process of modernizing its payments infrastructure. Their methodology offers relevant counterfactuals and estimates that can be used by regulators to fine-tune the parameters of new payment infrastructures to enhance financial stability.
In the area of clearing, Argyris Kahros, Alessandro Pioli, Thomas Carraro, Marios Gravanis and Francesco Vacirca provide us with “A descriptive analysis of the client clearing network in the European derivatives landscape”, the issue’s fourth paper. Their study includes trade-level information on all over-the-counter and exchange-traded asset classes and contract types. They find that client clearing services are highly concentrated, which could have significant implications for financial stability. Their study allows market participants and regulators to better understand how risks are distributed across financial entities and jurisdictions, and how these risks could be managed more efficiently.
Our final paper, “From use cases to a big data benchmarking framework in clearing houses and exchanges” by Olga Lewandowska and Edgar Mai, highlights the importance of benchmarking different approaches to big data technology (BDT). The authors propose a parsimonious benchmarking framework in the context of clearing houses and exchanges that links technical and business benchmarks. In short, their framework aligns technological innovations with economic objectives. Their already important research is likely to increase in relevance as clearing houses and other FMIs continue their adoption of BDT. Consistent benchmarking should allow market participants and regulators to identify risks and opportunities in the implementation of new technologies, which are expected to have a lasting impact on the financial system.
The papers in this special issue were selected from a wide range of submissions spanning different topics. The authors of the selected papers have done an excellent job of presenting their findings clearly and concisely. Moreover, we believe that their work provides important contributions to the literature and to policy debates concerned with crafting adequate responses to the various challenges in the financial system.
The authors employ historical LVTS and ACSS data and use the discrete choice demand estimation approach to uncover end users’ and financial institutions’ preferences when deciding which payment instruments and payment systems, respectively, to use.
The authors present the findings of a detailed descriptive analysis of client clearing activity for derivatives in the euro area, as well as that of clearing members more broadly.
The aim of this paper is to examine which payment instruments Canadians use for paying bills and to assess the factors driving their bill payment behavior.
Economic prediction during a crisis is challenging because of the unprecedented economic impact of such an event, which increases the unreliability of traditionally used linear models that employ lagged data. The authors help to address this challenge by…
In this paper, we propose a conceptual framework that links the technical and business benchmarks in the domain of clearing houses and securities exchanges.