Volume 17 (2024-2025)

This paper explores the importance of fostering closer collaboration between front, middle and back-office functions within the fund management industry to achieve shared objectives. It highlights how misalignment between departments can lead to operational inefficiencies, heightened risk and damage to client relationships. The paper emphasises the significance of aligning cross-functional teams around a company’s core values and corporate objectives to streamline operations, enhance regulatory compliance and deliver superior client outcomes. Key barriers to collaboration, such as cultural silos, outdated technology and misaligned incentives, are examined, along with actionable strategies to overcome them. These include leadership-driven cultural changes, investment in integrated technology systems and the implementation of shared performance metrics to align teams with the organisation’s broader goals. The role of technology as an enabler of collaboration is also discussed, with examples of how data integration, automation and AI-driven analytics can improve efficiency and decision making. The paper concludes by illustrating how measuring collaboration success through key performance indicators (KPIs), continuous improvement frameworks and robust feedback loops can sustain alignment and drive innovation. By uniting all functions under a shared vision, companies can position themselves to thrive in an increasingly competitive and regulated landscape. The principles outlined have broader implications for any industry reliant on cross-functional teamwork to deliver longterm value. This article is also included in The Business & Management Collection which can be accessed at https://hstalks.com/business/.
Keywords: collaboration; alignment; efficiency; innovation; communication; continuous improvement

Organisations that have integrated AI solutioning and established mature information management strategy are nearly twice as likely to succeed with artificial intelligence (AI) than organisations that have not.1 Given that generative AI (GenAI) is reshaping capital markets with immediate gains in automation and analytics, those who can demonstrate responsible AI use and strong data protection measures may gain a competitive edge in industries where trust and reliability are paramount. As such, there is a drastic push for the adoption of AI technologies within the trade life cycle. While there are significant opportunities that can arise from adopting AI-related technologies, emerging data privacy directives and bespoke AI regulatory frameworks make implementation difficult to navigate. This paper serves to provide its readers with the knowledge and suite of tools requisite for navigating challenges concerning AI integration, organisation and effectuation for a responsible AI experience. This article is also included in The Business & Management Collection which can be accessed at https://hstalks.com/business/.
Keywords: GenAI; GenAI adoption opportunities and challenges; GenAI operational and technical implementation; GenAI regulatory frameworks and guidance; GenAI and the trade lifecycle opportunities

The history of central counterparties (CCP) risk management is one of gradual evolution, as a result of experience and experimentation. From early callable capital and basic forms of initial margin over 100 years ago to the sophisticated risk systems nowadays, it is hard to disassociate the evolution of CCP risk management from innovations in technology, developments in mathematical/statistical theories and the necessity of agents to respond to new economic incentives and challenges. The recent resurgence of artificial intelligence (AI) represents an important step on this evolution. However, these developments now also pose the question of whether AI will disrupt the natural course of automation observed in CCP risk management or if, in fact, AI will simply add to it. The objective of the paper is to reflect on this type of question, aiming to understand whether the recent developments could be the preceding phases of another AI winter. Using an assessment framework that searches for AI-type characteristics in existing risk functions performed by the CCP, the main conclusion of the paper is that there are some areas like credit risk, custody risk and investment risk that seem to have the features for efficient AI implementations. The supporting argumentation is that these risk functions rely typically on large amounts of mostly public information, to some extent not theoretically coherent across all its components, with models that combine quantitative and qualitative inputs. The paper’s conclusions fall short of saying other CCP risk functions will not be impacted but, from a systematic point of view, these seem more prone to continue on their gradual automation trajectory. This article is also included in The Business & Management Collection which can be accessed at https://hstalks.com/business/.
Keywords: artificial intelligence; automation; central counterparties; financial regulation; derivatives markets; OTC derivatives; risk management; systemic risk

Securities finance data has traditionally been used by participants in the financing markets to accurately price and manage lending programmes. Users of data included beneficial owners (long holders of securities), agent lenders, broker deals and, to a lesser extent, hedge funds. Today, the scope and use case for securities finance data far exceeds where we were even five years ago. The changes have been fast and furious. Use cases have proliferated and consumers of the data have expanded way beyond financing markets to the broader institutional and retail markets. The time to market has also increased dramatically. No longer is data available only on a T+1 basis; it is now published intraday in real-time, and the data is being incorporated into factor-driven trading models. This paper explores how securities financing data — anchored in transparency, real-time availability and measurable financial impact — serves as a strategic tool across multiple use cases and financial functions. By integrating specific use cases and showcasing how securities financing data can serve as a strategic asset, this piece illustrates how securities financing data can inform tactical decisions and facilitate long-term optimisation for companies. This article is also included in The Business & Management Collection which can be accessed at https:// hstalks.com/business/.
Keywords: corporate bond short interest; equities short interest; short squeeze; financing rate; liquidity; securities finance data

Risk appetite statements (RAS) were historically treated as standalone theoretical documents rather than integrated risk management tools used to monitor the aggregated major business risk exposures. Over the past several years, the RAS has continued to mature and further embedded itself into the overall risk framework by strengthening its connections with the day-to-day risk management (risk and control self-assessment [RCSA]), risk culture, Internal Capital Adequacy and Risk Assessment (ICARA) and wind down (WD) activities. To support this continued evolution in risk management overall, the Financial Conduct Authority (FCA) established the Investment Firms Prudential Regime (IFPR) for Markets in Financial Instruments Directive (MiFID) Investment Firms on 1st January, 2022.1 The new IFPR rules are documented in the FCA Handbook under ‘MIFIDPRU Prudential sourcebook for MiFID Investment Firms’.2 These rules and supporting guidance provide a rich source of principles of where expected integrations and maturing of the various risk tools should exist, such as the RAS that should integrate with a company’s business model, capital, liquidity and associated other risk assessments. However, more work is needed within companies to fully integrate the RAS to maximise its full benefits within the business. Particularly in driving better aggregated risk assessments, proactive risk management decisions, remediation, escalating major concerns, meeting regulatory requirements and initiating top-down management actions as well as better business decision-making. The FCA published their IFPR Implementation observations3 stating: ‘Some firms did not adequately assess the risks they face or use these assessments to inform elements of their ICARA process including their risk appetite, risk indicator triggers, early warning indicators, stress testing scenarios, and the estimates of own funds and liquid assets required’ and ‘appetite thresholds and trigger points help firms anticipate problems, take effective steps to prevent them and rectify problems when they occur. It is therefore essential that they are aligned to the firm’s own understanding of its risks’. This paper provides a practical solution to robustly integrate the RAS with bottom-up and top-down risk management processes and tools. This paper builds on the historic papers published in the Journal of Securities Operations and Custody (JSOC) as noted below. The risks discussed in this paper are those carried by the investment company and not those carried by its clients.This article is also included in The Business & Management Collection which can be accessed at https://hstalks.com/business/.
Keywords: risk appetite statement; RAS; ICARA; wind down; integration

The paper explores the impact of artificial intelligence (AI) on data licensing practices, particularly in the financial services. The authors discuss the rapid emergence of the technology and the resulting pressures on the data providers and looks to answer the question of whether existing data licensing frameworks need a fundamental re-think or can be adapted or maintained. The scope of the paper includes examining the use of market data in the financial markets, highlighting the complexities. The reader can expect to take away a good understanding three distinct types of data licensing (individual, application and redistribution) and the principles underpinning them giving ‘real’ examples to help with that understanding. The paper then goes on to discuss the relationship between AI technologies and the long-established data licensing practices and how at the heart of everything is the use case or how the authors refer to it as the ‘what not the how’. This article is also included in The Business & Management Collection which can be accessed at https://hstalks.com/business/.
Keywords: artificial intelligence (AI); data licensing; data monetisation; derived data; algorithmic trading; large language models (LLMs); data aggregators

This paper critically examines the persistent challenges within the asset servicing landscape and articulates a forward-looking strategy for meaningful industry transformation. Drawing upon insights from landmark initiatives, such as the Giovannini Barriers, the Draghi Report and recent regulatory developments — including Shareholder Rights Directive II (SRDII) and the European Capital Markets Union — the paper traces the evolution of asset servicing, highlighting both achievements and enduring pain points, notably in automation, data standardisation and regulatory harmonisation. A comprehensive analysis of a 2024 industry survey, led by Broadridge in collaboration with Depository Trust & Clearing Corporation (DTCC) and International Security Services Association (ISSA), forms the empirical cornerstone of this discussion. The survey reveals the acute operational inefficiencies, high error rates and escalating costs resulting from lack of standardisation from the data source, fragmented processes and legacy systems, particularly in the management of voluntary corporate actions. The paper synthesises these findings to underscore the imperative for standardised, digital-first data at source, and advocates for the creation of ‘golden operational records’ to enable true end-to-end automation. Intended for asset servicing professionals, technology leaders, regulatory bodies and capital markets strategists, this paper equips readers with strategic insights into current pain points, regulatory catalysts and emerging technologies — including AI and blockchain — that are poised to reshape the sector. Readers will gain a nuanced understanding of the root causes of industry inertia, the business case for cross-industry utilities and practical pathways to achieving harmonisation. This piece delivers unique value through its integration of quantitative data, regulatory analysi, and real-world case studies, culminating in actionable recommendations that blend market advocacy with innovation. It is essential reading for those seeking to future-proof their asset servicing operations and drive sustainable transformation across the global capital markets ecosystem. This article is also included in The Business & Management Collection which can be accessed at https://hstalks.com/business/.
Keywords: asset servicing transformation; automation; standardisation; regulatory compliance; artificial intelligence (AI); blockchain technology

Custody is integral to preparing for, and engaging in, the token economy. Without it, financial institutions, investors and consumers cannot use tokenised assets or move, manage and tokenise value in a safe, secure, scalable and compliant way. Given the growing breadth and importance of digital assets — from stablecoins and cryptocurrencies to tokenised real-world assets (RWAs) like stocks, bonds, commodities, real estate and more — market participants require custody in order to unlock access to these new asset classes and the broader token economy. If digital assets are the vehicles, then custody is the road that paves the way and enables the industry to get from point A to point B. Blockchain and digital assets have spread across myriad industries as the number of real-world use cases grows and progressive regulatory regimes take effect. And it is imperative that institutions understand both the considerations and challenges of crypto custody to better prepare for this next evolution in global finance. In this paper the author seeks to directly address this by considering the challenges and evolving regulatory landscape for institutional digital asset custody, specifically by offering examples of the increased tokenisation of real-world assets, comparing traditional with digital asset custody, and setting out the different custody models. The article continues by examining regulatory considerations for digital asset innovation before concluding with possible future developments. This article is also included in The Business & Management Collection which can be accessed at https://hstalks.com/business/.
Keywords: digital asset custody; crypto custody; digital asset regulation; self-custody; managed custody

Settlement efficiency has always been a concern for regulators and supervisors. This issue has recently gained the attention of all stakeholders in financial markets, however, due to: (1) the introduction of the Settlement Discipline Regime (SDR) in the European Union (EU) in February 2022; and (2) the migration to T+1 in the US, Mexico, Argentina and Canada, along with the consequent discussions in Europe about transitioning from T+2 to T+1. There is a perception in the market that the EU settlement efficiency rate is lower than that of other regions; however, there is no available failure rate for the US, and the methodologies used to assess these rates are neither uniform nor comparable. In fact, the EU methodology established by the Central Depositories Deposition Regulation (CSDR) is the most stringent. Furthermore, there are significant differences depending on asset classes, type of transactions and size of markets, etc. Equities markets usually have worse settlement ratios than bond markets, while exchange traded funds (ETFs) have the worst ratio, indicating possible structural problems. Larger markets generally tend to have worse ratios, likely due to higher levels of cross-border investment and more complex products, such as exchange traded products (ETPs) and ETFs. Settlement failures occur for a variety of reasons, encompassing numerous operational and technical issues along the custody value chain. Additionally, factors such as short selling activities and ‘strategic failures’ may contribute, although these are less frequently discussed by market participants. Determining the precise impact of each cause is challenging, as most are typically present during periods of increased settlement failures. These periods often align with high market volatility, elevated trading volumes, high borrowing costs and/or low interest rates. To improve settlement efficiency rates, a comprehensive set of actions should be undertaken by market participants, central securities depositories (CSDs) and regulators. A realistic and achievable target for settlement failures might be around 2 per cent in terms of value, which, while still ambitious, is more attainable than a 0 per cent target. This paper synthesises various analyses and personal experiences, rather than relying on a singular analytic study. This article is also included in The Business & Management Collection which can be accessed at https://hstalks.com/business/.
Keywords: settlement efficiency; fails; short selling; penalties; SDR; CSDR

In June 2027 the clearing of repos on US Treasuries will become compulsory in the US market, and it is possible that regulators in other markets may follow suit. Given the high levels of non-cleared repo in both the US and Europe, increased mandating of clearing could have a major impact on the operation of the repo market and potentially more widely on financial markets. This paper puts those changes into the wider context of the motivations, origin and evolution of the cleared repo market since the 2000s in the US and Europe. It describes the mechanics and main characteristics of the major significant forms of cleared repo, provided by the Fixed Income Clearing Corporation (FICC), London Clearing House (LCH) and Eurex. It also describes recent market trends, concluding with an analysis of the potential impact of compulsory clearing in the United States and probability of other jurisdictions following the US example. This article is also included in The Business & Management Collection which can be accessed at https://hstalks.com/business/.
Keywords: repo; clearing; capital markets; sponsored repo; cleared repo; liquidity; DVP repo; GCF repo; capital; LCR; FICC; Eurex; CCP

The transition to a T+1 settlement cycle marks a significant milestone in the evolution of global securities markets. This paper examines the key operational, technological and strategic challenges encountered during implementing T+1 and the lessons learned by early adopters, particularly in the US and Canada. The accelerated settlement cycle, designed to reduce counterparty risk and enhance market efficiency, demands a fundamental rethinking of post-trade workflows, requiring companies to adopt automation, streamline processes and foster cross-industry collaboration. The paper also highlights the implications of compressed timelines for cross-border transactions and the critical role of regulatory frameworks in ensuring a smooth transition. In addition, the analysis explores the readiness of other jurisdictions, including the UK and Europe, which are planning transitions to T+1 by late 2027. Drawing on real-world examples and industry insights, this paper provides actionable guidance for companies navigating T+1 while considering the broader implications for future settlement cycles such as T+0. Additionally, the paper assesses how the takeaways from T+1 can shape the transition to T+0, particularly in automation, liquidity management and risk mitigation. This article is also included in The Business & Management Collection which can be accessed at https://hstalks.com/business/.
Keywords: T+1 settlement; post-trade workflows; risk mitigation; global securities markets; operational efficiency; regulatory frameworks; T+0

This paper seeks to reflect on the contributing factors to the successful market implementation of US T+1, with specific focus on the foreign exchange (FX) market. It aims to explore and equip readers with the FX and liquidity management considerations as we look ahead to the UK, European Union (EU) and Swiss adoption of the same. How might this differ from the US rollout, and might it be complacent to assume that a copy/paste approach will work this time around? The paper also looks at industry and tech innovation, and whether any seismic changes can be anticipated in time for October 2027. This article is also included in The Business & Management Collection which can be accessed at https://hstalks.com/business/.
Keywords: foreign exchange; FX; currency; T+1; DLT; hedging

Organisations are facing challenges with data management as traditional solutions struggle to handle the complexity and volume of data. Three key stakeholders are involved: data producers who create data, data consumers who rely on its quality and data teams tasked with maintaining it. Generally, there are more producers and consumers than data teams, leading to strain on the data teams when issues arise. Often, data producers feel responsible for the data, making it harder to address quality problems that affect consumers. A new approach known as data mesh aims to improve this situation by emphasising decentralisation and domain-driven design. In a data mesh, responsibility for data is distributed among domain teams, not centralised in a single team. These teams are accountable for delivering high-quality data to others, treating it like a product. Additionally, a self-serve data infrastructure platform is proposed to support these teams by offering necessary tools and systems. The scalability, improved collaboration and agility offered by the data mesh paradigm, may contribute largely to the success of projects and programmes within an organisation. This article is also included in The Business & Management Collection which can be accessed at https://hstalks.com/business/.
Keywords: data mesh; data sharing; data ownership; data governance; data domain

This paper examines the current state of withholding tax recovery, reviews historical efforts to streamline inefficiencies, and evaluates the opportunities and challenges presented by the upcoming implementation of European Union Faster and Safer Tax Relief of Excess Withholding Taxes (EU FASTER) in 2030. The paper explores how thoughtfully crafted technology architecture will enable custodians and asset servicers to thrive within the digitised, relief-focused and reporting-intensive framework that EU FASTER envisions. By embracing collaborative digital ecosystems and strategic partnerships, providers may better meet emerging demands for transparency, automation and regulatory alignment as these policy changes unfold. This article is also included in The Business & Management Collection which can be accessed at https://hstalks.com/business/.
Keywords: withholding tax recovery; EU FASTER; FATCA; CRS; regulatory reporting; digitisation; operational efficiency; risk management

This paper examines Macau’s bond market development as a strategy for economic diversification, highlighting the need for a comprehensive securities law (Lei dos Valores mobiliários [LVM]). Recent progress includes the establishment of the China (Macau) Financial Assets Exchange Co. Ltd (MOX) and the Macao Central Securities Depository and Clearing (MCSD), which have improved market infrastructure and transparency. The current fragmented regulatory framework, however, requires the LVM to streamline oversight and enhance investor confidence. The LVM is crucial for fostering a liquid secondary market and positioning Macau as a competitive financial hub. This article is also included in The Business & Management Collection which can be accessed at https://hstalks.com/business/.
Keywords: Macau; bond market; securities law; economic diversification and financial infrastructure

Throughout 2024, European Union (EU)-based financial entities have been analysing their thirdparty and intra-group technology contracts against compliance with the EU Digital Operational Resilience Act (DORA), and renegotiating with vendors where necessary, in order to comply from 17th January, 2025. McKinsey estimates that EU institutions typically earmarked €5−15m for DORA programme strategy, planning and design, although full implementation costs may be five to ten times that range.1 The DORA analysis is also highlighting that certain companies are not compliant with existing regulatory expectations. Financial regulators and global standard-setting bodies have published high-level principles and also detailed expectations to ensure that companies have in place prudent third-party risk management controls, both at an enterprise level and for managing individual third-party arrangements. As securities markets participants become increasingly reliant on third-party service providers for tasks that they had not previously undertaken, leveraging technology and artificial intelligence (AI), supervisory focus is extending to operational resilience across third-party services relationships, not just outsourcing. In this paper, we explore key themes of existing outsourcing and third-party risk management regimes that apply to financial entities and their service providers. We note key differences between regulatory expectations on resiliency and outsourcing, highlight key best practices and challenges to implementing these expectations and, finally, consider the impact of AI solutions on such regulatory expectations.
Keywords: operational resilience; artificial intelligence; outsourcing; digitisation; financial regulation

There is a growing industry consensus that blockchain presents an exciting insight into the future of next-generation operational technology. As blockchain brings a new way of organising the underlying ledgers and communication, often we see industry leaders launching an on-chain version of their core business and operating both in parallel, such as J. P. Morgan’s Onyx and Euroclear’s D-FMI. Therefore, the question on the minds of many is what mass adoption would look like, as participants balance the needs of modernising existing systems versus migrating to new ones. This paper seeks to unwrap the key challenges and delve deeper into this multifaceted technology, to show that a trusted bridging solution that has footing in both traditional and new ecosystems is instrumental to enable the industry to move towards adoption and convergence. The author argues that post-trade financial market infrastructures (FMIs) have a key role to play in helping industry participants amplify the benefits of adoption, while crossing the various associated chasms of costs, scalability, risks and uncertainty.
Keywords: digital assets; blockchain; DLT; adoption; scaling; FMI; post-trade

In a total portfolio approach (TPA) asset owners use their entire capital to maximise the net impact of their investments by diversifying over risk factors. The focus is on allocation to risk exposures rather than asset classes, as in the traditional strategic asset allocation (SAA). Compared to the SAA, the TPA leads to better quality of decision making by using a factor lens that embraces the continuum between equity and debt as well as across public and private markets. The increasing adoption of the TPA coincides with what has even been termed ‘hypergrowth’ of investing in private markets. Many asset owners may be overestimating their liquidity needs and thus be foregoing valuable opportunities for investing in private assets and harvesting an illiquidity premium. As the costs of illiquidity do not depend on the asset but the specific state of a portfolio, TPA requires frequently generated cash flow forecasts for investments in these illiquid assets. By following the TPA and by treating private assets on an equal footing to liquid asset classes, asset owners can construct their portfolios in a new and innovative way that has the potential to sustainably generate higher returns. Newer risk factor models in combination with highly automated cash flow forecasting tools create a unifying framework whereby risks are measured more realistically, and a private asset’s illiquidity is not penalised if no liquidity is needed within the portfolio’s context.
Keywords: total portfolio approach; strategic asset allocation; private assets; risks factors; liquidity risk; cash flow forecasting

Capital markets companies are in the midst of a series of challenges that they cannot solve with revenue growth. This has increased the impetus for companies to look inwards and think about efficiencies and cost savings. The operating model that serves capital markets — and the legacy technology that powers it — is struggling to keep up, but change has historically been fraught with risk and the chance of failure looms large. This paper explores the need for a ‘next-generation’ operating model, the transformation pitfalls companies need to avoid when delivering one, the technology that enables it, and why people and data must be at the heart of any change.
Keywords: data; automation; operating model; transformation

There has been significant excitement surrounding the potential of distributed ledger technology (DLT) in revolutionising the world’s financial services markets in recent years. The aspiration of achieving a flawless method for trading, matching and settling security transactions is a far-reaching objective that all industry participants strive for. Financial services professionals do not begin their day aiming to create transaction failures. Such failures result in financial losses, including fines, staff expenses and overdraft charges across the industry. Despite decades of efforts to achieve a 100 per cent settlement rate, success has remained elusive. This paper delves into the evolution of our existing settlement framework, examines the risks it has brought about and speculates on potential improvements by enhancing our current systems and processes with necessary technological advancements.
Keywords: post-trade; T+1; settlement efficiency; SSIs; DLT

This paper explores the current state of cloud computing in the financial industry. While the potential benefits of cloud adoption — agility, scalability and innovation — are acknowledged, the paper highlights the challenges that remain. These challenges include a lack of clear and consistent regulations across jurisdictions, concerns about data security and residency and the complexity of navigating a hybrid cloud environment. The paper argues that to unlock the full potential of cloud computing in finance, a collaborative effort is needed. Regulators are expected to establish clear global standards for security, data residency, reporting and service level agreements (SLAs). Financial institutions should prioritise security and sustainability when choosing cloud providers and advocate for clearer regulations. Finally, cloud service providers (CSPs) themselves need to collaborate with regulators and financial institutions to develop standardised security frameworks and reporting formats. By working together, the paper concludes, all stakeholders can build a more secure, sustainable and prosperous cloud future for the financial industry. Readers will gain an understanding of the current challenges and opportunities surrounding cloud computing in finance, along with the key actions needed to move forward. They will also be introduced to key concepts such as data residency and hybrid cloud strategies.
Keywords: cloud computing, banking; security; regulations; standards; cloud service providers; CSPs

The asset management industry is dealing with a variety of challenges, ranging from difficult market conditions, higher operating costs, declining fees, intensifying competition from passive funds, right through to the introduction of new and complex regulations. At the same time, asset managers are also looking for innovative ways to diversify their businesses, either by launching private fund strategies aimed at the retail market or integrating environmental, social and governance (ESG) standards into their decision-making processes, to name just a few. All these dynamics are forcing asset managers to rethink their historic operating models. If companies are to adapt, however, then they will need access to excellent data. The problem is that many asset managers do not possess this data themselves, or if they do, it is often unstructured and unusable. This is where their global custodians are well positioned to help them. With many global custodians sitting on mountains of data, leading providers are now sanitising this information and turning it into useful insights and analytics for their institutional clients. From this, asset managers will be able to enhance their asset allocation processes, streamline operations, better comply with regulations and ESG requirements and bolster their retail distribution capabilities. In today’s highly crowded market, the ability to successfully make use of data could be the difference between winning and losing lucrative mandates.
Keywords: resilience; data; operations; custody and efficiency

The rapid evolution of artificial intelligence (AI) and especially machine learning (ML) has significantly transformed the technological landscape, influencing diverse sectors and making notable inroads into the realm of finance. This paper delves into the challenges posed by ML models, known for their black-box nature, non-deterministic behaviour, reliance on big data and inherent complexity, often lacking clear specifications. These characteristics present novel testing challenges compared to traditional software. In addressing these challenges, the authors introduce a conceptual framework tailored for testing ML-based systems, with a specific focus on financial applications. Theoretical concepts are exemplified through a real-world case study of the implementation of an ML-based bond trading system within a banking context. As the AI technologies become increasingly integrated into critical financial systems, a deeper understanding of their testing strategies will be essential for mitigating risks and harnessing their full potential. The heightened significance of in-depth testing knowledge, propelled by AI-driven progress, holds relevance for both testers and managers in navigating the complexities of the technological changes.
Keywords: artificial intelligence (AI); machine learning (ML); digital banking; innovation; testing; software testing; software quality; test automation

The capital market plays an important part in Brazil’s economic development. It meets a large part of companies’ financing requirements and protects against market fluctuations. BSM is the main self-regulator of the Brazilian capital market. It performs self-regulation, supervision and inspection for organised markets managed by B3 — Brasil, Bolsa, Balcao — one of the world’s largest financial market infrastructure companies, providing trading services in an exchange and over-the-counter (OTC) environment. Pursuant to these goals, BSM monitors operations, orders and trades executed in this trading environments, supervises market participants and, if necessary, applies penalties against those who violate regulations. In this paper, the author shares how, in his current role, he verified the need for strategic mapping of BSM’s self-regulatory agenda. The paper aims to map opportunities for creating and updating legal standards that govern the capital market, to establish incentives for economic agents to reduce cost of compliance and make their regulation more efficient and effective. Several key drivers for BSM developments are: autonomy and empowerment, collaborative culture, agility and adaptability, and technology and digital transformation. BSM is adopting innovations in several areas, including trading technology with advanced analytical tools for monitoring electronic trading platforms, risk management systems and advanced analytical tools, as well as market surveillance monitoring: artificial intelligence (AI), machine learning (ML) and other technologies to detect abusive trading activities. Furthermore, it is promoting education and research: workshops, executive education courses and partnerships with universities and market schools and other initiatives to strengthen market understanding and improve trading analysis practices. All these tools bring to self-regulatory organisations (SROs) significant benefits, including greater transparency and efficiency.
Keywords: innovation; self-regulatory organisation (SRO); capital markets; BSM Market Supervision

Custodian banks have long been the unsung supporters of the investment industry, ensuring the smooth operation of transactions, servicing large institutions and infrastructure to support significant amounts of money management. As modern asset managers and asset owners continue to grow, however, they will demand more from their custodian- partners. The demand for services will come from more sophisticated, technology-reliant functions, and as such, the role of custodians will undergo a profound transformation. What has helped custodians be successful so far — reliance on people and process to deliver services — will not continue to help them in the future. This paper explores considerations for custodians and the adaptations required in their service models to meet contemporary challenges. We conclude that a fundamental shift is required away from traditional mindsets to ensure custodians remain central to supporting the needs of asset managers and asset owners.
Keywords: custodian; investment data; operating model transformation; data-as-a-service

Although the adoption of distributed ledger technology (DLT) is still in a very early phase, its application to the issuance and custody of digital securities is making progress and various platforms and solutions based on a blockchain/DLT infrastructure are emerging. The cash leg of settlement, however, is still not properly solved for this type of infrastructure. For the settlement of digital assets, traditional payment rails are still often used, which hinders the technology from reaching its full potential in areas such as efficiency gains, both in respect of costs and time. To support and prepare for a potentially wider adoption of digital assets, the European Central Bank (ECB) is exploring in 2024 new technologies for wholesale central bank money settlement together with interested market participants. Central bank money systems have centralised architectures designed for single issuers and operators. As central bank money is traditionally used to support the settlement of securities, the question of how to bring it to newly emerging decentralised DLT platforms in an interoperable and efficient manner requires an answer. The ECB, together with three national banks as solution providers, is exploring three different approaches and will likely shed light on several important considerations: is wholesale central bank money necessary on-chain in a tokenised form? What are the advantages and disadvantages of alternative approaches? This paper provides a comparative overview of the explored solutions and describes the assumed interoperability mechanisms between the digital asset and payment systems.
Keywords: DLT; digital assets; settlement in central bank money; interoperability; ECB exploratory work

With the recent adoption of the European Union (EU) FASTER directive, the EU intends to act against the practical hurdles for a proper taxation of cross-border income payments. At the same time, Germany is implementing the Act to Modernize the Relief from Withholding Tax and the Certification of Capital Gains Tax (ABzStEntModG) and with this, the Mitteilungsverfahren Kapitalertragsteuer auf Dividenden und Hinterlegungsscheine (MiKaDiv) reporting regulation, which aims at both the modernisation of withholding tax procedures and at anti-abuse measures, as a result of the experience with cum/cum and cum/ex tax fraud. Both regulations will have a significant impact on the processing of cross-border income payments by financial intermediaries. EU FASTER requires the implementation of new reporting regimes and will potentially change the way income payments are processed, and requires certain intermediaries to offer new services for tax relief or refund.
Keywords: withholding tax; EU FASTER; cross-border taxation

The unique identification of securities is the basic building block of financial markets. It is impossible to trust anything else about a security without first knowing what is being bought and who is selling it. Security identifiers provide that critical function almost invisibly, allowing trades to be executed, cleared, settled and tracked in a standardised, consistent manner across the countless individual portfolios and security master files that make up the global financial system. This concept is so fundamental and critical to the efficient operation of our financial markets that it is often taken for granted. Two recent trends, however, have forced a closer look at the underlying governance structure of security identifiers as a potential source of trade settlement failure and confusion among market participants. The rise in popularity of reverse stock splits and the introduction of alternative securities identifiers that use a different approach to cataloguing these types of corporate actions has created a scenario in which market participants using different securities identification taxonomies will see the same underlying security two different ways. The phenomenon puts a spotlight on the issue of securities identifier permanence and raises serious questions about when an identifier needs to change to address corporate actions. This paper argues that the approach utilised in the governance of the Committee on Uniform Securities Identification Procedures (CUSIP) and International Security Identification Number (ISIN) identifiers, whereby identifiers change in response to corporate actions, is critical to the maintenance of efficient financial markets.
Keywords: CUSIP; ISIN; FIGI; securities identifiers; reverse split; corporate actions; permanence; ABA; FactSet; Bloomberg

This paper attempts to provide a careful and balanced look at some of the benefits and challenges of tokenisation of securities. A fundamental problem is the lack of consistency in how ‘tokenisation’ should be defined. According to a report by McKinsey & Company in 2023, ‘Tokenization adoption was poised for success six years ago, but progress was limited … the path could be different this time’. In the past, tokenisation was: (1) limited to a process of creating a representation of financial, intellectual or physical assets on a blockchain (ie distributed ledger technology [DLT]); and (2) discussed as a narrative of disintermediation and programmability as a basis for efficiency gains. As it became clear that DLT, with its basic game-theoretical approach, comes with high costs and opaque governance, traditional platforms with high efficiency such as the European TARGET2-Security (T2S) with atomic settlement and delivery-versus-payment (DvP) show up as blueprints for efficiency. A proposal of the Bank for International Settlement (BIS) for a unified ledger, Project Guardian of the Monetary Authority of Singapore (MAS), both in 2023, and an announcement of the U.S. Securities Industry and Financial Markets Association (SIFMA) in 2024 about ‘settlement on a common regulated venue … [of] tokenized assets’ can be regarded as paradigms for a new and pragmatic approach, with coordination and synchronisation as key objectives in the context of financial market infrastructures.
Keywords: tokenisation; distributed ledger technology; platforms; operational efficiency; synchronisation