Jim Kwiatkowski, CEO of LTX

The reason for this is that new artificial intelligence solutions available today can transform the entire process of assessing liquidity, identifying bonds, selecting counterparties, trading bonds, and post-trade reporting. These new efficiencies have the potential to eliminate hours of work and improve results for individual traders, while creating new efficiencies that could facilitate more market-wide trading volumes, liquidity, and transparency, reducing spreads and lowering costs for investors.  

The corporate bond market today 

To understand the potential impact of these next-generation tools, it’s important to look at how market participants trade corporate bonds today. The corporate bond market is a heterogeneous mix of instruments, each with its own tenure, coupon and other characteristics. Traders and investors must navigate a maze of data streams and analytic tools designed to help research and analyse the expansive universe of bonds and their own portfolios. Many bonds trade infrequently, if at all. According to our analysis, in December 2024, 75% of total US credit trading was concentrated in only 16% of bonds. The sheer size and diversity of this market makes it challenging to access. As a result, less than half of investment grade bonds and only a third of high yield bonds are traded electronically.   

By contrast, in markets like foreign exchange, upwards of two-thirds of total trading volume is now executed on electronic platforms. For US Treasuries, that share approaches 80%. What those and other markets have in common is that they are composed of a relatively small number of similar products that trade regularly. However, corporate bonds have not proven as amenable to electronic trading as most other asset classes. At least not yet. 

Market participants frequently advocate for continued electronification because it improves market efficiency by providing transparency, increasing liquidity, and reducing costs. Electronification evolves market structure by enabling new types of trading and supporting higher trading volumes for the benefit of the entire market, and our belief is that AI can help to accelerate this process more quickly.  

The data science revolution  

One of the biggest frustrations for corporate bond market participants today is the fact that they possess a huge and rapidly expanding volume of data, but it is nearly impossible to gather and process all that data in time to help inform a trading decision. That is a problem almost perfectly designed for artificial intelligence. AI-powered applications can quickly analyse the entire universe of available data to create a robust profile for every bond in a portfolio, and for every bond in the market. Instead of manually scouring market data terminals for pricing and other bond data, a trader, investor or dealer can use natural language to simply ask the application about characteristic-based bond discovery, relative value, price and volume history, counterparties, available liquidity, and reporting on trading history. In a matter of seconds, market participants can receive responses to complex bond-related questions, incorporating data from many different sources, that would have taken hours to obtain manually.   

The market is seeing innovations every day, with new platforms employing data science capabilities like machine learning and large language models to aggregate, process and analyse data. For instance, on the LTX trading platform, our BondGPT tool allows users to ask questions and identify corporate bonds based upon the user’s criteria and much more. These capabilities can help answer critical questions like: “What are the most liquid bonds that meet my investment criteria, at what price should I be transacting to get a particular size executed, and what counterparties are likely to be willing to trade on those terms?” 

Saving time and making money with AI 

The benefits to market participants are obvious. As they execute trades, they will save time, while ensuring that their trading decisions are driven by the best and most timely data available.  

The application of AI to corporate bond trading will also deliver other benefits that might take longer to arrive but could prove even more important in years to come. AI-powered platforms will unlock market liquidity by expanding the universe of bonds that participants can analyse and consider when making trading decisions, and by revealing new potential counterparties in the position to buy or sell bonds. Over time, these enhancements will lead to a boom in secondary trading volume. By making it easier and less time-consuming to identify, analyse and price corporate bonds, AI-driven applications could create positive market structure change, enhancing overall market liquidity and lowering costs for all participants.  

It’s difficult to predict when these benefits will materialise at a market-structure level, but our buy-side clients continue to show eagerness in embracing these changes. In the coming weeks and months of 2025, we look forward to sharing more about the innovations we’re working on at LTX to help. We believe that rate of adoption for these innovative tools will continue to accelerate quickly as portfolio managers and traders using traditional methods to analyse and trade corporate bonds experience the transformative potential of incorporating artificial intelligence into their workflows. 

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Artificial intelligence has transitioned from being a nice-to-have enhancement to an essential business capability across capital markets. With mounting pressure for return on investment, firms are increasingly turning to AI and automation to maintain their competitive edge. This shift is enabling organisations to provide more value-add, high-touch services while fostering innovation around new products and instruments with higher returns.

The transformation of raw data into actionable, ROI-based information is fuelling this adoption. Firms that successfully balance innovation with risk mitigation are positioned to take a significant leap forward in the market. This is particularly evident in the investment management space, where technological capabilities have become a crucial selection criterion for institutional investors.

2. Front-to-back investment workflow reengineering

With fee compression averaging 15-20% across asset management over the past five years, firms are under intense pressure to improve operational efficiency. Investment managers who have implemented straight-through processing systems are seeing impressive results: 50-60% reduction in trade processing times and up to 40% decrease in operational costs, all whilst reducing error rates across the trade lifecycle.

The modern investor demands real-time portfolio transparency, personalised reporting, and seamless digital experiences. In fact, 75% of institutional investors now consider a manager’s technological capabilities as a key selection criterion. This has pushed firms to modernise their systems, enabling them to scale assets under management without proportional cost increases and enter new markets or asset classes in months rather than years.

3. The data revolution

The volume of market data has exploded, growing from approximately 100 petabytes daily in global markets in 2020 to over 300 petabytes daily in 2024. Multi-asset strategies have become increasingly complex, requiring firms to synthesise data across multiple public and private asset classes. Each asset class brings its own unique data structures, update frequencies, and regulatory requirements.

Modern financial institutions must now process and analyse an unprecedented variety of nontraditional data sources, including satellite imagery, social media sentiment, mobile device location data, and sensor data. This requires sophisticated data management systems that can handle both structured and unstructured data while maintaining data quality and accessibility.

4. Risk analytics takes centre stage

Institutional managers are significantly increasing their investment in risk management and performance analytics tools, with technology spending in this area growing by over 45% annually. The largest institutional managers are reportedly allocating more than $100 million annually to enhance their quantitative analytics capabilities.

This focus on risk analytics is driven by the increasing complexity of modern portfolios, which now include multi-asset strategies, derivatives, structured products, and private markets all interacting in both linear and nonlinear ways. The integration of alternative data, private markets, factor tilts, direct indexing, and ESG risk factors has created multiple new dimensions of market risk that demand sophisticated quantitative analysis.

5. The rise of financial mega-factories

The industry is witnessing the emergence of dominant service providers known as “mega factories” – fund administrators, custodians, and tech vendors that offer comprehensive front-to-back solutions. These providers now process more than $7 trillion in daily transactions, a 65% increase from five years ago. They’re making substantial investments in technology infrastructure and talent to deliver end-to-end services, effectively transforming themselves into essential infrastructure providers for the financial sector.

6. Regulatory technology convergence

The regulatory technology landscape is shifting from fragmented solutions to integrated compliance platforms. Global regulatory fines reached $12 billion in 2023-2024, pushing institutions toward unified compliance and surveillance architectures. By 2025, approximately 65% of major financial institutions are expected to implement or begin transitioning to holistic compliance platforms.

Early adopters of unified compliance solutions are seeing impressive results: 45% reduction in reporting errors, 60% improvement in change management efficiency, and a 25% decrease in operational costs. These platforms enable real-time impact analysis across regulatory obligations, significantly reducing the risk of cascading compliance failures.

7. Trading automation and high touch services

Electronic trading volume has surged dramatically, with 82% of global equity trading now executed electronically, up from 65% in 2019. Low touch trading accounts for approximately 73% of institutional flow, resulting in a 45% reduction in transaction costs and a 68% improvement in execution speed.

The global spend on trading workflow automation is projected to reach $12.4 billion by 2025, growing at a CAGR of 16.8%. Integration of high touch and low touch workflows has become a key focus, with top-tier banks investing $50-75 million in unified trading platforms.

8. Private markets evolution

The private credit market has witnessed a remarkable expansion, growing from $875 billion in 2020 to more than $1.6 trillion. This surge can be attributed to the accelerated modernisation of infrastructure and the democratisation of market access through digital platforms. These technological advancements have enabled a broader range of investors to participate in the market, fostering a more inclusive and dynamic financial ecosystem.

In response to these changes, large financial institutions are increasingly adopting unified data platforms that manage both public and private securities. This integration streamlines operations, reduces redundancies, and enhances transparency, allowing firms to navigate the complex regulatory landscape more efficiently. The move towards unified platforms signifies a fundamental shift in the way financial institutions approach data management, positioning them for greater success in the evolving market

9. Collateral management transformation

Collateral management is undergoing a profound transformation, driven by advancements in real-time processing capabilities, integrated risk frameworks, and digital asset infrastructure. Firms are achieving remarkable efficiency with 93% of margin calls resolved automatically through AI-powered pre-validation checks. The incorporation of ESG considerations, along with the advent of tokenised assets, is redefining traditional collateral systems. This multi-year evolution is optimising processes and enhancing the resilience of collateral management frameworks.

Additionally, the proliferation of advanced analytics platforms is making inventory management optimisation a critical focus. With 93% of margin calls now managed via system-to-system integrations, firms are developing hybrid systems that can seamlessly handle both traditional and digital assets. This convergence is reshaping infrastructure investing, enabling more sophisticated and agile approaches to collateral management. As a result, firms are better equipped to navigate the complexities of the modern financial landscape.

10. No, or low, code revolution

Despite 70-80% of major financial institutions still depending on core legacy systems, low code platforms provide a pragmatic bridge to modernisation. These platforms enable firms to reduce IT development costs while accelerating application delivery from month to days. Business users can now directly build and modify workflows without deep technical expertise, reducing process optimisation time by 65% and increasing staff engagement by 40%.

As we progress through 2025, these trends are not just reshaping the capital markets landscape – they’re fundamentally transforming how financial institutions operate, compete, and deliver value to their clients. Success in this new environment will depend on firms’ ability to embrace these changes while maintaining robust risk management and regulatory compliance frameworks. Those that can effectively navigate this transformation will be well-positioned to capture the opportunities that lie ahead in an increasingly digital and automated financial world.

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Regulators are already pointing to a need for automation as a solution for mitigating the human and technological risks of navigating the complex and fragmented European market. The reason for this is in the numbers – there are 14 authorised central counterparties (CCPs), an additional 24 third country central counterparties, and 29 authorised central securities depositories (CSDs).

Even with automation, demand for headcount may increase

Headcount and talent is a looming issue which European businesses preparing for T+1 are fast becoming aware of. Expectations of the transition to T+1 broadly include a level of operational strain and staffing challenges.

In the US, Bloomberg Asset and Investment Manager (AIM) data suggests two conclusions can be drawn. The first, that automation has great potential to ease this burden. Research, which covered more than 3.7 million trades over an 18-month period relating to clients using AIM’s post-trade capabilities, found that 92% of blocked trades were matched in 2 hours – speeds which would comply with T0 requirements – while 96.2% matched within T+1 timeframes. Just 0.25% matched in T+2 or longer. 

The second conclusion is that, even as automated solutions were implemented, headcount rose across the board as firms bedded in T+1 processing in the run up to and following the deadline. Industry research shows that in the US 52% of businesses that underwent T+1 regulatory compliance added headcount. 

In Europe, concerns about headcount are even more acute. The problem is exacerbated by the multiple timezones and operating hours of European businesses that sit in the middle of the trading day. There is already talk in the industry of the potential for implementing round-the-clock teams to enable businesses to deal with the new time pressure of post-trade settlement. In this scenario, individuals and teams could have responsibility for 24/7 monitoring with the aim of catching and resolving settlement issues immediately.

As a first step, businesses must look at their own operations and consider where automation can play a role in minimising disruption. The critical next step, which should be taken concurrently, is paying great attention to future talent requirements to manage the T+1 transition process. 

Asia presents a unique counterparty problem for Europe

Where operations in Europe will have to be compliant with trades coming in from the US, which already have their own regulatory framework, Asia presents another challenge entirely, and one which will hit European operators harder than, for example, in the US. 

European operations do considerably more trading business with Asia, because of shared market hours. This perk offers a potential downside. In Asia, in particular, there is a broad preference for solving capacity issues by upweighting headcount. As trading volumes increase and timeframes grow shorter, due diligence into the processing capacity of counterparties may well become a requirement. There is potential for this to become an additional capacity and headcount requirement in the interim. 

This is a serious operational risk and there are early indications that businesses in Asia understand that solving it in advance is a competitive advantage – HKEX announced last month its intention to invest in better technology to aid T+1 counterparty processing. 

In conclusion, while the US’ role as a front-runner in implementing T+1 has undoubtedly provided valuable lessons for European businesses undertaking the transition to T+1, any assumptions that the process can be replicated are misplaced. Europe’s fragmented market and its position at the centre of the trading day places greater emphasis on automation, talent, and counterparty risk than for the US.

Data shows that automation will be key to managing processing capacity, but it is not a silver bullet and business leaders must thread the needle very carefully in order to balance the many risks at play between now and 2027.

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Last year was nothing short of dramatic. Political shocks, the August sell-off and the constant ‘will they, won’t they’ over central banks’ approach to interest rate cuts. Yet for the buy-side, banks and exchanges, a quiet technological revolution has unfolded. Innovations bubbling away over many decades are converging and reshaping how firms approach trading technology.

Historically, the disparity between large firms with hefty tech budgets and smaller firms striving to maximise limited resources was stark. Until recently, the idea of building trading systems from scratch was daunting – the operational complexity, time to market and perceived costs were a deterrent.

Now, the convergence of performant and resilient cloud technology, powerful tech accelerators and open-source technology are democratising access to bespoke trading systems. Buying off-the-shelf technology is no longer the path of least resistance. This is a change that will transform not only how institutions view their trading capabilities but also shape their approach to markets.

Breaking barriers

The convergence of recent technological leaps is changing mindsets and levelling the playing field when it comes to deploying state-of-the-art trading technology. The proprietary systems that once gave large banks and hedge funds a competitive edge are no longer exclusive to those with deep pockets. 

Over the past decade, vendors have innovated alongside consultancies as client demands have evolved. Yet, the core question for buyers often remained: do you want a system tailored to your business that you own and control? Or, do you want a vendor system that performs well but pegs you to the pace of the vendors’ innovation?

Advances in cloud and open-source trading technology have skewed what was once a more clear-cut choice. Proprietary technology is no longer the preserve of those with deep pockets. Modular, cloud-based technologies enable continuous development and customisation, bringing built solutions into the mainstream.

Evolving technology strategies

Financial institutions are rethinking their technology strategies. Instead of relying on vendor solutions as temporary fixes, there is a growing realisation that investing in modernising technology stacks can yield better long-term results and innovation potential. The question is no longer simply whether to buy or build, but how to best allocate resources to achieve strategic goals.

This shift has far-reaching implications. As more firms – from exchanges to buy-side entities and investment banks – adopt purpose-built systems, the overall market structure will improve. High-throughput, resilient technologies will enhance operational efficiency and reduce friction, leading to greater market and operational efficiencies.

The road ahead 

The convergence of enhancements to advanced trading systems marks a tipping point for financial services firms. As more and more develop their own technology stacks, the potential for meaningful enhancements to global capital markets grows exponentially.

Computing capabilities that were previously beyond the reach of mid-sized firms are now widely accessible to all through the cloud. These capabilities combined with bespoke systems will pave the way for AI adoption, 24/7 trading, seamless workflows and sophisticated new tools. Without these capabilities, much-hyped technologies or market structure changes will remain on the drawing board.  

This year, we can expect accessible proprietary technology to have impacts beyond enhancing narrow functionality. With a growing number of organisations exploring the benefits of custom trading technology and the proliferation of open-source technologies that form the building blocks of sophisticated multi-asset systems, innovation in financial services will be unshackled.

The next twelve months is about building strong foundations for the subsequent five years. Firms that proactively develop and control their own technology will gain a significant competitive edge, leaving those who follow conventional paths behind.

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Using conditional orders, as most algorithms provide liquidity in multiple ATS’, the liquidity is no longer unique in most ATS’ – what you can get in ATS A is typically also available in ATS B. It also leads to race conditions, if you send conditional orders to multiple ATS’, the same contra may be present in multiple ATS’ and you may receive several simultaneous “invitations” to access that liquidity. We recently published a research paper that provides empirical insights into competitive dynamics on ATS’ while using conditional orders.

One key insight is the uniqueness of block liquidity. When we place conditional orders for more than 5,000 shares (*block trades) across multiple ATS’, we observe that 71% of the time, we do not receive simultaneous invites. This indicates that the ATS sending the invitation in those cases is providing unique liquidity. This finding offers a valuable opportunity to analyse which ATS’ truly deliver unique liquidity for block trades. Importantly, our analysis includes only samples where conditional orders are sent to these ATS’ simultaneously, ensuring a level playing field.

Figure 1. Overall ATS market share based on total shares traded (all NMS stocks) in Q3 2024. Source: FINRA

One would think that bank ATS’ would leverage their franchise liquidity, whether it is from their algorithms or trading desks, and create a good supply of unique block liquidity. But surprisingly, that is not what we find. When it comes to unique block liquidity – executions greater than 5000 shares – we still find that good old agency crossing networks remain the most unique source of block liquidity even when used in conjunction with the conditional orders rather than a blotter.

Figure 2. Percent of unique liquidity from each venue based on transaction size > 5000 shares (*block trades). Source: BestEx Research

Among the agency pools, BIDS stood out as the leader in unique liquidity, followed by Liquidnet (LIUH), Instinet’s BlockCross (BLKX), Virtu’s POSIT (ITGI), and Purestream (STRM).

Request access to the full research paper for more observations.

*In the research paper we define block trades as all transactions above 5000 shares.

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Industry challenges and data evolution

Today’s asset management firms face a triple threat: intensifying regulatory oversight, mounting cost pressures, and accelerating technological disruption. Recent industry research reveals that 41% of senior asset managers identify regulatory changes as their primary concern, while 39% point to margin pressure as a critical challenge. These traditional hurdles are compounded by the rapid emergence of technological innovations, particularly artificial intelligence, which 37% of managers view as a potential disruptor. 

While data has always been central to asset management, its role has evolved significantly. No longer just a tool for market analysis and performance tracking, data has become the cornerstone of operational transformation. Forward-thinking firms are moving beyond basic data collection to implement comprehensive data ecosystems that enable real-time decision-making and predictive analytics. Nearly 80% of asset managers now recognise data intelligence as crucial for effective decision-making, triggering a wave of technological investment in automated validation systems, real-time analytics platforms, and cross-departmental data-sharing solutions.

Implementation challenges and cultural transformation

Despite widespread recognition of data’s importance, many firms struggle with implementation. The challenge often lies not in collecting data, but in transforming it into actionable intelligence. Organisations must foster a data-driven culture where decisions at all levels are informed by analytical insights. This involves significant investment in training and development to build data literacy across teams.

Legacy systems and manual processes must give way to automated, integrated platforms that can handle the volume and complexity of modern data requirements. Robust data governance frameworks ensure data quality, security, and compliance with regulatory requirements while enabling efficient access and utilisation. The industry’s approach to artificial intelligence reveals varying levels of technological maturity. While 44% of firms remain in the exploratory phase, a growing number are moving toward implementation. Early adopters gain competitive advantages through enhanced operational efficiency, while cautious firms benefit from learned experiences but risk falling behind. 

Shaping tomorrow’s asset management landscape

The transformation of asset management through data and technology is not just about survival – it’s about creating sustainable competitive advantages. As firms continue to evolve, they must build adaptable data infrastructures that can accommodate future technological advances. This means creating scalable architectures, implementing flexible integration frameworks, and developing clear data strategy roadmaps while building strong technology partnerships. 

The gap between technologically advanced firms and those maintaining traditional approaches will continue to widen. Success in this new environment requires decisive action today to build the data infrastructure and capabilities needed for tomorrow’s challenges. The most successful firms will be those that effectively balance technological innovation with the human expertise and judgment that have always been at the heart of investment management.

As we move forward, the firms that thrive will be those that view data not as a burden to be managed, but as a strategic asset to be leveraged. They will create ecosystems where technology enhances rather than replaces human decision-making, where data flows seamlessly across departments, and where innovation is driven by a deep understanding of both technological capabilities and investment fundamentals. This balanced approach will define the future of asset management, creating a more efficient, responsive, and successful industry.

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The 28th regime offers a potential overhaul of Europe’s capital markets, aimed at addressing key challenges such as financing the green and digital transitions and unlocking private capital. By establishing a streamlined supervisory framework under ESMA, the regime could enhance market integration, reduce fragmentation, and foster cross-border investment. However, it also poses risks, including the possibility of deepening market disparities and hindering the broader goals of the Capital Markets Union. For the regime to succeed, it must balance national interests with the need for a cohesive and competitive European financial market, positioning Europe as a global leader in sustainable finance.

Europe’s capital markets constrained by fragmentation and regulation

Europe’s capital markets are at a critical juncture. The twin challenges of financing the green and digital transitions – requiring an estimated EUR 700–800 billion annually over the next decade – are far beyond the capacity of public budgets and traditional bank lending. Unlocking private capital is no longer optional; it is imperative. However, Europe’s financial landscape remains constrained by structural and regulatory inefficiencies that hinder the development of deep, integrated, and efficient capital markets capable of addressing these challenges.

One of the key issues is the limited scope for retail investors to participate in capital markets. European savers are often confined to low-yield financial products due to consumer protection rules that, while well-intentioned, restrict access to higher-return investment opportunities. This dynamic discourages capital flows into innovative and growth-oriented sectors, stifling the potential for wealth creation and broader economic growth. Revamping savings products and enabling more direct engagement with capital markets could be transformational in mobilising private investment.

The near-elimination of the securitisation market is another glaring bottleneck. In contrast to countries like the US, Canada and Australia, Europe has yet to harness the full potential of securitisation as a tool to recycle capital and fund businesses. Reviving this market could unlock EUR 300–400 billion annually, but doing so requires a coordinated effort to ensure that securitisation products are both attractive to investors and aligned with robust regulatory standards.

Fragmentation of Europe’s capital markets further exacerbates these issues. National supervisory frameworks create inefficiencies, as firms operating across borders must navigate a patchwork of regulations, duplicating efforts and increasing costs. This lack of harmonisation stymies the development of pan-European financial products, which are essential for creating a truly integrated capital market. The current structure inhibits the free flow of capital and restricts market participants from reaping the benefits of scale and competition.

Towards a 28th regime: A new framework for capital markets integration

To address these challenges, a more systematic approach to determining the most efficient supervisory structure is needed. For instance, a “supervisory efficiency test” could be implemented when reviewing legislation such as MiFID or UCITS, evaluating whether supervision should remain national, adopt mutual recognition, or shift to a supranational level based on the complexity and integration of the market. Balancing the “right to move” with the “right to stay” could also help preserve market presence and influence for smaller or less-integrated regions.

Taxation, governance and shareholder rights present additional complexities. These areas are deeply embedded in national legal frameworks and any attempt at harmonisation must tread carefully to avoid disrupting established practices. A gradual approach to transferring responsibilities, informed by the experiences of the banking union, could help mitigate resistance and build trust among stakeholders.

Beyond structural reform, there is a need for a cultural shift in how Europe approaches capital markets. Policymakers must balance the drive for harmonisation with the need to foster innovation and growth. This includes rethinking the role of regulation to ensure it supports, rather than stifles, market development. For example, simplifying processes for asset managers to operate across borders and aligning rules to reduce compliance costs could enhance competitiveness without compromising investor protection.

Harmonisation efforts should focus on eliminating unnecessary national variations, particularly in areas like prospectus standards, to reduce duplication and complexity. Using KPIs to track market integration, leveraging AI and digital tools to overcome language barriers, and enhancing trust among retail investors are practical steps to increase efficiency. Mechanisms such as EU-wide arbitration for dispute resolution could simplify redress for retail investors, building confidence in cross-border products.

One proposed solution to overcome these barriers is the establishment of a ‘28th regime’ for Europe’s capital markets. This concept envisions an optional framework under the European Securities and Markets Authority (ESMA) that would allow firms to opt into centralised supervision while maintaining collaboration with national authorities. Such a regime could streamline oversight for cross-border activities, reduce administrative burdens and foster the creation of pan-European products. By offering a single set of rules and a single supervisor for certain aspects of the market, the 28th regime could significantly enhance market efficiency and attractiveness.

Potential risks and challenges of the 28^th regime

The 28th regime, while offering the potential to streamline Europe’s capital markets, poses several risks that could undermine its intended benefits. One of the main concerns is the possibility of increasing fragmentation within Europe’s financial markets. If some countries opt into the regime while others remain outside, it could create two-speed markets, with the more developed markets benefiting from integration while smaller, less-developed regions fall further behind. This division could worsen existing disparities, making it harder to achieve a truly unified capital market.

Another challenge is the potential for divergent speeds in market development. Countries with more advanced financial markets might implement the regime quickly, while those with less sophisticated markets could struggle, leading to uneven progress across the EU. This imbalance could discourage investment in slower-moving markets and delay the realization of a fully integrated European capital market.

The 28th regime also risks complicating the broader goal of the Capital Markets Union (CMU). Instead of fostering a single, seamless financial market, it could result in the emergence of smaller, regional unions with differing regulatory frameworks. This fragmentation could hinder the free flow of capital across the EU, making it difficult for Europe to compete globally as a unified economic entity. National authorities might also resist the shift toward centralised supervision, fearing a loss of sovereignty and control over domestic markets.

Finally, the 28th regime must strike a delicate balance between national diversity and integration. Europe’s financial markets are deeply rooted in national traditions, and any attempt to harmonize regulations too aggressively could generate significant political resistance. Success will depend on the regime’s ability to incorporate national perspectives while promoting a cohesive, integrated capital market that can compete on the global stage.

Striking the right balance

A well-designed 28th regime could be a game-changer for Europe’s capital markets, fostering greater integration and dynamism. By offering a streamlined framework for cross-border supervision, it holds the potential to position Europe as a global leader in sustainable finance. This regime could channel much-needed private capital into the green and digital transitions, aligning with Europe’s environmental and economic objectives. However, time is of the essence: delays in reforming Europe’s capital markets will result in missed opportunities and underutilized private capital, further delaying the continent’s growth prospects.

Despite the benefits, the 28th regime carries risks that must be carefully managed. Fragmentation remains a major concern. If some countries opt in while others stay out, it could create a two-tiered market, exacerbating disparities between more and less developed markets. This could hinder the smooth flow of capital and undermine efforts to create a truly unified capital market. Additionally, uneven speeds of implementation across the EU could create imbalances, potentially discouraging investment in slower-moving markets and delaying Europe’s capital market ambitions.

The 28th regime also risks complicating the broader Capital Markets Union (CMU) project. Rather than fostering a single, integrated European market, it might inadvertently lead to smaller, regionally divided unions. This could create obstacles to pan-European financial products and undermine the goal of a competitive, unified market. Furthermore, national resistance to centralised supervision could delay or derail progress, making it essential for the regime to balance national sovereignty with the need for a more integrated market.

In conclusion, the 28th regime represents a bold step toward the integration of Europe’s capital markets, but these risks must be addressed for it to succeed. A careful, collaborative approach that balances ambition with pragmatism will be essential for transforming Europe’s capital markets into a globally competitive and sustainable financial hub. Only through a cohesive, pan-European framework can Europe achieve its financial and sustainability goals.

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A year ago, I’d never have imagined myself stepping away from the world of the front-office.

I’d been working in the front-office as a trader or a vendor for my entire career and after selling Broadway Technologies to Bloomberg back in 2023 a number of other opportunities in the front office world presented themselves.

Among these opportunities was the chance to lead Duco and as I considered my choices, I realised just how crowded the front-office landscape has become.

Traders have so much choice in technology that it’s becoming difficult to do anything that really moves the needle. The more I learned about Duco and the problems the company was solving for middle- and back-office teams across the globe, the more it dawned on me just how ripe and exciting the opportunity for innovation outside of the front office is.

This realisation comes alongside a shift in attitudes across the industry wherein business and market trends are reshaping capital markets, putting greater focus on the middle- and back-offices. It’s no secret that these functions have been overlooked and underfunded when it comes to innovation which has left them with outdated technology stacks and inefficient operating models – but that’s all changing.

Firms are waking up to the idea that value is created across the business, not just by the front-office. As the spotlight spreads across the whole organisation, the pivotal role of the middle- and back-office shines bright. 

Operations are now seen as value creators and, with the right technology, they can surely rise to the challenge.

Thinking about value from start to finish

People used to think about capital markets firms as having a front-office that made all the money, with middle- and back-offices doing the admin and tidying up loose ends. Attitudes are changing now because macroeconomic conditions, market forces and regulatory pressures are creating an environment where firms must look at their business more holistically – front to back.

According to analysis by Oliver Wyman and Morgan Stanley, capital markets firms are increasingly focusing on operational efficiency, regulatory compliance, and cost reduction. The latter in particular has become such an issue because it has risen in line with revenue growth during the good times, but when the revenue outlook softened those costs were still there.

Banks’ top priority now is plugging the gaping cost holes at the center of their operations, alongside improving operational efficiency, reducing risk and ensuring compliance with an ever-stricter set of regulatory requirements.

And even if the front-office remains in the driving seat, the fact of the matter is that most capital markets firms have a lot of operational baggage. At some point that baggage becomes too much and the engine cuts out. Middle- and back-offices are full of inefficient systems, manual processes and thousands of overburdened workers trying to get things done. There’s a point at which that stops being scalable – and there’s a strong argument in favour of the fact that the industry is already long past that point.

Capital markets firms are increasingly waking up to the idea that lean, agile and efficient back- and middle-offices are essential to remaining competitive and meeting the main challenges of the day.

According to GreySpark Partners, “post-trade functionality is clearly the single most important area of differentiation among competing banks”. They list securities operations, derivatives operations, portfolio & risk management and bank-client interactions & communications as the top four areas of differentiation among competing banks. What makes you competitive isn’t about who can trade or invest better, it’s about who runs the most streamlined machine.

It’s time for a change

The middle- and back-office needs better technology to achieve their firm’s strategic goals around cost, efficiency and compliance. While the pace of innovation in the front-office may have slowed, the opposite is true in the post-trade arena. 

That’s not to say no one is innovating, more that there are still so many fundamental challenges that are being addressed, or in need of a new solution. Capital markets firms have long struggled with five core challenges around data: the issues of endless variety, constant change, overwhelming scale, hidden lifecycles and a lack of control.

Capital markets firms rely on a number of core automation systems that specialise in a particular asset class which act like the motorways for your data. However, outside of this exists a complex network of point solutions and end-user computing (EUC), all held together by manual work, in order to handle the portion of data that couldn’t travel down the motorway. 

But, the amount of data traveling these roads is growing. You don’t even have to look that far back to see just how fast this is happening. Futures and options trading volumes, for example, have hit a new record for six consecutive years, with volumes rising 64% year-on-year to 137.3 billion contracts in 2023.

This means an increasing amount of resources are needed to manually transform, enrich, reconcile and validate the trade data that isn’t fully automated. This data is still mission-critical – it fuels internal reporting, informs P&L calculations and risk management. It’s under increasing scrutiny from regulators and must follow ever-more prescriptive rules around format and quality. 

The ‘last mile’ has therefore grown over the years into a spaghetti junction, filled with opaque and risky processes, outdated technology and legions of ‘Human APIs’ manually holding it all together.

But it’s a problem that can be solved by innovations in cloud computing, Software-as-a-Service, no-code applications, machine learning and AI. Data automation is a transformational approach to managing data that leverages these amazing technologies and enables firms to overcome historic challenges around data.

Duco clients, for example, isdemising on-premise legacy systems automating end-user computing like spreadsheets in their hundreds eradicating manual processes from their operations. 

The need for an innovation mindset

So, the technology is there to help middle- and back-offices to innovate towards smarter, more efficient, transparent and low-risk operating models. But the existence of technology isn’t enough on its own.

Operations have long been change-averse. It’s entirely understandable; they’re dealing with mission-critical processes and everyone knows that transformation projects are difficult. They’ve also spent decades working with technology in a certain way: on-premise, hard-coded, maintained and operated by IT. It’s difficult to think differently when you’re used to doing things a certain way. 

Therefore, to truly benefit from the latest advances and thinking around technology, processes and people, firms need to adopt an innovation mindset. In my first six months at Duco I spoke to dozens of customers, and the top question was: “How can we do more with the platform?”

That’s the innovation mindset right there, thinking not about how to do the same things a bit more efficiently, but to ask whether it’s possible to do things in an entirely different way. To move, for example, from a reactive operating model built around the need to clean up after bad data to a data-centric operating model, where controls are put in place proactively to ensure STP. One where exceptions really are exceptional.

Santander’s José Muñoz described this mindset onstage at Sibos, asserting that “transformation should be a third of your time. We try to focus people on change all the time, as part of their business-as-usual.”

Santander aren’t the only firm who are starting to view change as a necessary part of run-the-bank. The leading capital markets firms recognise that they can’t afford to stand still. Operations leaders like José are looking to push the boundaries of what’s possible, and that’s what’s so exciting about being a technology vendor in this space. We have the capability, and the market is demanding something different to what they’re used to. It’s the perfect environment for innovation to flourish.

Operations is in the spotlight

It’s never been a more exciting time to be in the middle- and back-offices. The spotlight is shifting to look across the business as firms realise that value creation happens everywhere. The technology is there for you to make big changes and solve your long-standing challenges. Plus, the market trends, regulatory changes and demands of the business need you to innovate.

The challenges are big, but the solutions are there. With the right mindset, you can be a driver of serious change in your organisation. Are you ready?

The post The most exciting place for innovation in capital markets? Operations. appeared first on The TRADE.

While the UK general election result was priced in, and data from TraX showing a slight uptick in UK Government bond prices, markets were rattled by gains made by the political far right – initially in the European Parliament elections, and then in France following Emmanuel Macron’s decision to call a snap election.

The expected initial gains by the far right in the French election led to a winning left-wing coalition in the second round amongst taxing political manoeuvres. The result is a divided Assemblée Nationale with no absolute majority, leaving Europe’s second largest economy without clear direction.

This has caused havoc for French capital markets, and it will certainly take time to reassure investors as the political picture slowly settles. We are already seeing a busier than expected summer in markets – which we largely expect to continue – with heightened volatility, a challenging liquidity environment and a likely continued ‘higher-for-longer’ interest rate scenario.

The events in Europe and their knock-on effects into markets have now been further heightened by the US presidential election in November. With President Biden dropping out and Kamala Harris now Donald Trump’s opponent, investors are weighing up the potential impacts of the respective candidate’s presidency. During the build-up to the election, markets will be in flux as they as prepare for a Trump or Harris presidency.

Despite all these uncertainties, the broad outlook for investors in bond markets remains promising – known for their relative security and stability, they have maintained high yields compared to recent history.

Investors need to focus on selecting the right markets and sectors, effectively managing risks, and allowing for best execution within that market.  

And while the challenge of market entry and accessing liquidity is always there, continued technological advancements are forming the foundation upon which innovative tools applied across the trade lifecycle are developed and refined. There are today a myriad of technologies and solutions that can help.

This approach forms the basis of how MarketAxess is innovating, with high-quality market data being at the core of any technological advancement. The proliferation of high-quality datasets in bond markets has also driven its broader evolution: the automation of the market.

As seen with many industries, the bond markets have also recognised the potential of artificial intelligence (AI) and machine learning (ML). At MarketAxess we have used this to address a range of activities, with one key example being price discovery – one of the main headaches for investors – wherein CP+ provides an accurate tool for predictive real-time pricing for global credit and rates markets.

Bond markets are democratising through the expansion of new liquidity pools and increased accessibility to global markets.

This is embodied in our all-to-all trading model, Open Trading. It has continued to strengthen markets by identifying new pockets of liquidity, which is critical not only for traditional markets such as Eurobonds, US investment grade and high yield credit, but also for unlocking opportunities in developing markets and enabling investors to access more opportunities, and with speed.

More and more markets are progressively opening up and evolving, as investors demand greater access to local and hard currency debt. A notable recent example is the inclusion of Indian government bonds in JP Morgan’s emerging market debt index, which enhances tradability and attracts foreign investment in India.

Looking ahead, the second half of this year will no doubt be uncertain for investors, with a backdrop of political and economic risks; elections, persistent inflation and central bank policies. This will challenge market participants on many levels.

For investors to successfully navigate bond markets during this time, they need the tools and data behind them to make effective decisions. While many are already using some of these tools today selectively, we expect to see much wider adoption across investor-types and markets going forward as they seek new ways to remain competitive in challenging markets.  

The post How can bond investors access liquidity and trade effectively in a challenging, politically fuelled market? appeared first on The TRADE.

With broker-dealers seeking ways to enhance efficiency and reduce costs, many are turning to automation. Unfortunately, broker-dealers can’t trust artificial intelligence (AI) yet with crucial aspects like compliance and risk management. Recent Large Language Models (LLM) achievements show remarkable results in summarising existing information and recognising patterns in mixed content like recorded sound, images, and video. However, decision-making processes that are a crucial part of compliance and risk management are far from being fully automated by the usage of the LLM-like AI. In particular, so-called AI hallucinations are a noticeable side effect of the LLM application in different spheres of IT and automation. 

Fortunately, there are multiple ways to automate these business areas with good old automation software crafted specifically for its purpose, time-tested, and configurable to suit each brokerage’s needs. 

Limiting risk exposure

Risks emerge when clients sell options, short stocks, and take advantage of a leverage provided by a broker. Different broker-dealers have their own criteria for measuring an acceptable level of risk the client takes intraday and whether to limit it or not. Say, if a client exceeds a safe number of orders daily, their orders should be alerted or sent to a risk desk for review before being further routed to execution. Other limiting parameters can be the total used margin, daily unrealised loss, or the total size of derivative products’ position in the client’s portfolio. Regulators oblige broker-dealers to monitor client risk if they offer derivatives trading. However, broker-dealers themselves may put additional controls in place to avoid situations when their clients can’t cover losses due to a lack of funds. 

In this scenario, risk exposure can be automated to detect such clients and their risky operations. Broker-dealers can fine-tune risk management to assign risk profiles or bespoke risk parameters on the individual account or account group level. At the same time, the software will not distract the risk desk department with clients’ orders that do not increase the risk exposure or are below the accepted risk level. 

Post-trade operations 

When it comes to operations, involving corporate actions can be entirely automated without the need for interruptions from a broker-dealer’s staff. In the case of a stock split and reverse stock split, merger, or acquisition, clients’ portfolios can be automatically updated with the new number of equities they’re eligible for. Dividends can also be automatically represented as cash transactions or as an equity increase. 

As regards reconciliation, we’ve learned through our work with brokers that they spend too much time on manual reconciliation due to legacy systems and missing integrations between them. To keep up with growing trading volumes and the number of end users, as well as the recent implementation of the T+1 settlement rule, brokers should automate reconciliation with the latest technology. 

The perfectly automated process looks the following way: a broker’s trading platform is integrated with their venue of choice for custody, clearing, and settlement. The tool syncs transaction data in the client’s trading platform with the venue’s “Start of Day” (SOD) files. If there’s a mismatch between the broker’s data and SOD files, the broker’s trading officers use a specially developed web UI to approve adjustments in the trading platform database. The process might be further automated by automatically adjusting the trading platform records and intrade syncs. The tool supports individual and bulk corrections. Thus, a broker’s staff doesn’t have to search for mismatches and update them manually in something as outdated as an Excel file. 

In addition, brokers might get a substantial competitive advantage if they implement a tool for clients that notifies them about all prospective commissions and fees they’ll have to pay before sending orders for execution.  

Order routing is another key factor. Smart and thoroughly thought-through order routing poses no risk and only brings gains to broker-dealers. While being aligned with the best execution rule, a broker-dealer has the right to route client orders not only to public exchanges but also to dark pools and alternative trading systems (ATSs). 

What’s different about sending orders to dark pools and ATSs is that broker-dealers can save on execution fees and get paid for order flow. 

Why automation is required here — dark pools and ATSs prefer orders manually issued by traders and not algorithmically generated orders, let alone pay for them. Intelligent order routing allows us to define execution destinations per order/account according to this aspect. 

Besides this basic filtering, there are four automation scripts for intelligent order routing according to: traded volume, percentage of orders sent to a particular venue, user groups, primary and secondary destinations, routing time, depending on trading hours. 

The bottom line

Automation undoubtedly improves brokers’ operations. It makes their processes more efficient, reduces risks, and improves overall performance. By using automation tools in important areas like risk management, post-trade operations, reconciliation, corporate actions, commissions, and order routing, broker-dealers can make their work easier and gain an advantage in the industry. 

As automation changes, broker-dealers should carefully consider each automation solution’s benefits and possible impacts. This careful approach helps broker-dealers make good decisions that meet their goals and the rules. Ultimately, using automation well can help broker-dealers succeed in a changing and competitive market. 

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