Financial Market Infrastructures Research Articles

The Regulation of Corporate Governance in European Financial Market Infrastructures: A Critique

1This article is the first to consider the variations in governance requirements applicable to European financial market infrastructures. It charts the tangled combination of laws, codes and regulations that apply to the governance of the largest European central counterparties, central securities depositories, and international central securities depositories. Despite the similarity of these institutions in terms of their sector, criticality, complexity and purpose, there are substantive variations in what is required of their governance. Here we question whether this variance is an appropriate reflection of differing institutional needs or a by-product of piecemeal regulatory reform.Our research found no apparent need to regulate for consistency of board size or structure, nor in relation to specificities of committee requirements. However, there are convincing arguments that change is needed around the meaning and application of independence. The current approach to FMI directorial independence is a poor fit given the sectors highly technical nature, its interconnectedness, and the limited pool of available expertise. On top of this, expertise, diversity, and commitment can become trade-offs for adherence to the requirements of independence. We argue that regulation needs to be sensitively calibrated to ensure these important factors do not get squeezed out under the weight of formalized independence. It is our view that independence requirements can be structured to create better balanced boards where the needs of independence, expertise, diversity, and commitment can be weighed against each other in context.

Remarks on Blockchain and Distributed Ledger Technology in Financial Market Infrastructures

Remarks on Blockchain and Distributed Ledger Technology in Financial Market Infrastructures

A computational model of bilateral credit limits in payment systems and other financial market infrastructures

This paper provides the first steps towards a theoretical and structural modelling framework through which optimal decision making in financial market infrastructures such as payments clearing and settlement systems can be assessed from a market microstructure perspective. In particular, the paper focuses on the application of agent-based computational economics and stochastic games in modelling the bilateral credit limit establishing behaviour of Participants in loss sharing arrangements within financial market infrastructures such as the Canadian Large Value Payments System (LVTS). With specific focus on the LVTS, the paper presents a structural model where the payments system represents a market in which bilateral credit limits are the pricing mechanisms for intraday liquidity provisioning and the credit risk arising from the loss sharing arrangement. The data-driven stochastic game framework further illustrates how payments data, in conjunction with other financial market and credit data, can be used to assess emergent macroscopic outcomes in clearing and settlement systems from the underpinning interactions of autonomous decision making agents. The paper speaks to potential policy issues such as the effectiveness of policy levers such as the System-Wide Percentage, regulatory concerns around procyclicality and free-riding arising from the market microstructure behaviours, and design of the System.

Measuring the impact of a failing participant in payment systems

Large banks and critical financial market infrastructures (FMIs) that are not able to fulfill their payment obligations, for example following a bankruptcy or cyber-attack, can be a source of financial instability and contagion in the financial system. This paper develops a composite risk indicator to evaluate the criticality of participants in a large value payment system network, combining liquidity risk (i.e. size of incoming and outgoing payments) and systemic impact or interconnections between network participants in one approach. It is applied, as a proof of concept, to the TARGET2 payment system that links banks and FMIs in a tight network of interdependencies. We find that the most critical participants in TARGET2 are other payment systems (large value and retail) because of the underlying gross size of their payment flows. Some banks may be critical, but this is mainly due to their interconnectedness with other TARGET2 participants. Central counterparties and central securities depositories are less critical to the payment system. Our findings can be used by (1) financial stability experts to evaluate the impact of a failing critical participant in the financial system, and (2) central banks in their role as payment system operator and overseer. Besides, it feeds into policy discussions on payment system access, oversight, and crisis management.

Redundancy of Centrality Measures in Financial Market Infrastructures

The concept of centrality is widely used to monitor systems with a network structure because it allows identifying their most influential participants. This monitoring task can be difficult if the number of system participants is considerably large or if the wide variety of centrality measures currently available produce non-coincident (or mixed) signals. This document uses robust principal component analysis to evaluate a set of centrality measures calculated for the financial institutions that participate in Colombia's four financial market infrastructures. The results obtained are used to construct general indices of centrality, using the most robust measures of centrality as inputs and leaving aside those considered redundant.

Sweden

The Swedish financial market infrastructure (FMI) is modern, stable, well-developed, and subject to regulation and to the CPMI-IOSCO Principles for Financial Market Infrastructures (PFMI).

The Impact of Financial Development on Inflation: Empirical Evidence from Kenya using the ARDL Approach

This study delves into a comprehensive examination of the intricate relationship between financial development and inflation in Kenya, utilizing time series data spanning from 1973 to 2021. Within the empirical and theoretical realms, especially within country-specific contexts, the multifaceted dynamics of short-run and long-run impacts stemming from financial development on inflation have remained a significantly underexplored area. To address this research gap, we employ ARDL analysis, recognized for its sophistication and analytical rigor. The empirical findings from this study unveil a robust and enduring influence of financial development on inflation in Kenya over the long haul. Nonetheless, it's noteworthy that immediate evidence of financial development's impact on inflation appears relatively modest. Furthermore, the study unveils a complex interplay between interest rates and inflation, both in the short and long run, showcasing an negative relationship. These outcomes emphasize a substantial Granger and ARDL-driven causal link between inflation and financial development. Importantly, the policy implications arising from these empirical insights underscore the critical need for prudent financial sector oversight, focusing on fostering a climate conducive to stable and moderate inflation rates. This necessitates concerted efforts from both financial institutions and the government to fortify financial market infrastructures and bolster the uptake of financial services.

(In)efficiencies of current financial market infrastructures: an empirical assessment

We use unique individual bank-to-bank repo transaction data to empirically assess the efficiency of the existing Swiss financial market infrastructure (FMI) for executing delivery versus payment transactions. This approach enables us to identify its current benefits and drawbacks as well as where new technologies, such as distributed ledger technology, could provide a remedy. We find that the fastest settlement time for repo transactions is 12 s, but that settlements are often delayed by more than 10 min due to the lack of collateral availability. We conclude that the cross-border availability of securities needs to be addressed by either improving interoperability of existing infrastructures or using new technologies.

Distributed ledger technology and financial market infrastructures: an EU pilot regulatory regime

Distributed ledger technology and financial market infrastructures: an EU pilot regulatory regime

Financial Market Infrastructures: The International Approach and the Current Challenges

Financial Market Infrastructures: The International Approach and the Current Challenges

Decentralized Financial Market Infrastructures: Evolution from Intermediated Structures to Decentralized Structures for Financial Agreements

Financial market infrastructures (FMIs) have evolved as core elements of highly intermediated financial markets partly due to the technological limitations of the time when they were first designed. Organizations and firms were unable to share records without having to entrust a single party to manage them; hence this phenomenon of intermediation has led to significant information silos. Simultaneously, it has driven the structure of business models, as well as regulatory supervision and oversight, in ways that furthered intermediation and also created a misalignment of incentives and risk taking between entities now categorized as systemically important financial institutions (SIFIs) and systemically important financial market infrastructures. Over time, this consolidation has led to highly concentrated FMIs and with it, concentrated risks. Some of these risks go beyond the credit risks of just one or two institutions, becoming instead systemic risks that are continuously monitored by regulatory bodies. Over the past decade, advances in public key cryptography, hash functions, virtualization, distributed consensus, multiparty computation, and peer-to-peer networking have led to experimentation around record sharing between erstwhile competitive firms. Over the past five years, a series of independent efforts has chaperoned regulatory requirements into a digital, automated state that enables secure information sharing in full compliance with the law, while simultaneously enabling market participants to mutualize infrastructure that would otherwise be run by a single trusted party. With these developments, many of the services that centralized intermediaries currently provide could potentially be replaced by decentralized infrastructures or decentralized financial market infrastructure (dFMI). dFMI also enables a change in business structure, where a re-alignment of incentives can take place such that those firms taking risks can fully bear the consequences of these risks.

Governance in Systems Based on Distributed Ledger Technology (DLT): A Comparative Study

The (experimental) use of DLT is growing, also in the financial sector. DLT systems themselves advocate the fact that they use (consensus) algorithms and cryptography to create a leaderless system (horizontal). How is it possible to ensure that decisions in these DLT systems are in the interest of all stakeholders and the public interest, including supervisory authorities? Given the popularity of the Bitcoin and Ethereum blockchains, for example, it is not inconceivable that a part of the FMI will be based on a public DLT system in the future. It is therefore important to gain a better understanding of the governance of such DLT systems, and what the risks are for FIs when using DLT. This paper compares the governance of financial institutions (FIs) and financial market infrastructures (FMIs) on the one hand with the governance of systems based on distributed ledger technology (DLT systems), on the other, to discover how they differ, and where potential risks and benefits lie for their future use, also in the financial markets. We answer two questions: i) What are the differences in governance between traditional FIs, FMIs and DLT systems? and ii) What are the consequences of decentralized governance of DLT systems for supervisory authorities?

BigTech and Platform Finance: Governing FinTech 4.0 for Sustainable Development

Over the past 150 years, finance has evolved into one of the world’s most globalized, digitized and regulated industries. Digitalization has transformed finance but also enabled new entrants over the past decade in the form of technology companies, especially FinTechs and BigTechs. As a highly digitized industry, incumbents and new entrants are increasingly pursuing similar approaches and models, focusing on the economies of scope and scale typical of finance and the network effects typical of data, with the predictable result of the emergence of increasingly large digital finance platforms. We argue that the combination of digitization, new entrants (especially BigTechs) and platformization of finance – which we describe as FinTech 4.0 and mark as beginning in 2019-2020 – brings massive benefits and an increasing range of risks to broader sustainable development. The platformization of finance poses challenges for societies and regulators around the world, apparent most clearly to date in the US and China. Existing regulatory frameworks for finance, competition, data, and technology are not designed to comprehensively address the challenges to these trends to broader sustainable development. We need to build new approaches domestically and internationally to maximize the benefits of network effects and economies of scope and scale in digital finance while monitoring and controlling the attendant risks of platformization of finance across the existing regulatory silos. We argue for a principles-based approach that brings together regulators responsible for different sectors and functions, regulating both on a functional activities based approach but also – as scale and interconnectedness increase – addressing specific entities as they emerge: a graduated proportional hybrid approach, appropriate both domestically in the US, China and elsewhere, as well as for cross-border groups, building on experiences of supervisory colleges and lead supervision developed for Globally Systemically Important Financial Institutions (G-SIFIs) and Financial Market Infrastructures (FMIs). This will need to be combined with an appropriate strategic approach to data in finance, to enable the maximization of data benefits while constraining related risks.

Central Counterparties’ Insolvency and Resolution – The New EU Regulation on CCP Recovery and Resolution

With its new Regulation on the Recovery and Resolution of Central Counterparties, European Capital Markets Law has filled an important void in the regulatory framework for the operation of central counterparties, which has been established with the EU Markets Infrastructures Regulation (EMIR) as early as 2012. With a comprehensive set of preventive and reactive provisions for the restructuring of central counterparties, the new instrument clearly takes a bold step. The provisions build on existing international standards, but are far more granular than these. The present paper assesses the underlying policy and the technical content of the Regulation in the light of the post-financial crisis literature on the systemic relevance of financial market infrastructures.

Brexit and CCP Supervision: From Extraterritoriality to a Model of Shared Control

Brexit has triggered a battle over the clearing of derivatives between the United Kingdom and the European Union. While the former seeks to maintain its preeminent market position, the latter seeks to curtail it in the name of stability. This contribution submits the economic and legal arguments made in this cross-Channel debate to close scrutiny. It also discusses in depth the most recent changes to the EU's legal framework (EMIR 2.2), which has the double aim to take control of clearing operations in Britain and repatriate the most important of them to the EU. The contribution concludes that we are witnessing the emergence of a new type of supervision for globally significant financial market infrastructures, which is called here shared control.

Decentralized Financial Market Infrastructures

Financial market infrastructures (FMIs) have evolved as core elements of highly intermediated financial markets partly due to the technological limitations of the time when they were first architected. Organizations and firms were unable to share records without having to entrust a single party to manage them; hence this phenomenon of intermediation has led to significant information silos. Simultaneously, it has driven the structure of business models, as well as regulatory supervision and oversight, in ways that furthered intermediation and also created a misalignment of incentives and risk taking between entities now categorized as systemically important financial institutions (SIFIs) and systemically important financial market infrastructures. Over time, this consolidation has led to highly concentrated FMIs and with it, concentrated risks. Some of these risks go beyond the credit risks of just one or two institutions, becoming instead systemic risks that are continuously monitored by regulatory bodies based on coordinated sets of principles and guidelines including the 2012 Principles for Financial Market Infrastructures from CPMI and IOSCO. Over the past decade, advances in public key cryptography, hash functions, virtualisation, distributed consensus, multiparty computation, and peer-to-peer networking have led to experimentation around record sharing between erstwhile competitive firms. Over the past five years, a series of independent efforts has chaperoned regulatory requirements into a digital, automated state that enables secure information sharing in full compliance with the law, while simultaneously enabling market participants to mutualise infrastructure that would otherwise be run by a single trusted party. With these developments, many of the services that centralised intermediaries currently provide could potentially be replaced by decentralised infrastructures or decentralised financial market infrastructure (dFMI). dFMI also enables a change in business structure, where a re-alignment of incentives can take place such that those firms taking risks can fully bear the consequences of these risks.

The Too-Big-To-Fail Problem and the Blockchain Solution

The paper seeks to ascertain whether and to what extent blockchain technology may contribute to solving the politically and socially intractable problems of effectively resolving distressed TBTF financial institutions. It revisits the TBTF problem in the light of the Global Financial Crisis and the COVID-19 crisis and provides an overview of the constantly evolving DLT/blockchain ecosystem. It further seeks to address the main arguments commonly advanced by blockchain sceptics/opponents against the more widespread adoption of crypto-assets. Given blockchain’s capacity for decentralization, transparency and automation, the technology seems particularly well suited for tackling TBTF. On that basis, the paper discusses the potential impact of blockchain technology on (TBTF) bank resolution in three possible scenarios. Gradual adoption over the next five years may significantly improve the resolution process primarily through enhanced transparency of the blockchain-recorded history of assets and transactions. Over the next decade, a ‘smart securities world’ may emerge where bail-in could be automated and systemically important assets and liabilities resolved through distributed financial market infrastructures (dFMIs). The final scenario, with a 20-year horizon, is a fiat cryptocurrency in a reformed financial system where banking panics are eradicated. These scenarios are speculation. However, the basic technological building blocks are already available today and with improved scalability, more reliable smart contract execution and widespread adoption over time they could help to significantly improve the resolvability of TBTF institutions.

Measuring the Impact of a Failing Participant in Payment Systems

Banks and financial market infrastructures (FMIs) that are not able to fulfill their payment obligations can be a source of financial instability. This paper develops a composite risk indicator to evaluate the criticality of participants in a large value payment system network, combining liquidity risk and interconnections in one approach, and applying this to the TARGET2 payment system. Findings suggest that the most critical participants in TARGET2 are other payment systems, because of the size of underlying payment flows. Some banks may be critical, but this is mainly due to their interconnectedness with other TARGET2 participants. Central counterparties and central securities depositories are less critical. These findings can be used in financial stability analysis, and feed into central bank policies on payment system access, oversight, and crisis management.

Chile

The BCCh is considering broadening access to its services beyond commercial banks and some Financial Market Infrastructures (FMIs). The services include settlement accounts, intra-day liquidity, standing deposit and lending facilities, and eligibility for ELA. Banks have always had access to these services, while Central Counterparties (CCPs) and the Securities Settlement System (SSS) were granted access to a settlement account in 2009. The BCCh is considering extending its services to various types of Nonbank Financial Institutions (NBFIs) to enable it to more closely manage and mitigate financial stability risks.

Shallow or Deep? Detecting Anomalous Flows in the Canadian Automated Clearing and Settlement System using an Autoencoder

Financial market infrastructures and their participants play a crucial role in the economy. Financial or operational challenges faced by one participant can have contagion effects and pose risks to the broader financial system. Our paper applies (deep) neural networks (autoencoder) to detect anomalous flows from payments data in the Canadian Automated Clearing and Settlement System (ACSS) similar to Triepels et al. (2018). We evaluate several neural network architecture setups based on the size and number of hidden layers, as well as differing activation functions dependent on how the input data was normalized. As the Canadian financial system has not faced bank runs in recent memory, we train the models on “normal” data and evaluate out-of-sample using test data based on historical anomalies as well as simulated bank runs. Our out-of-sample simulations demonstrate the autoencoder’s performance in different scenarios, and results suggest that the autoencoder detects anomalous payment flows reasonably well. Our work highlights the challenges and trade-offs in employing a workhorse deep-learning model in an operational context and raises policy questions around how such outlier signals can be used by the system operator in complying with the prominent payment systems guidelines and by financial stability experts in assessing the impact on the financial system of a financial institution that shows extreme behaviour.