2024: That's a Wrap
The Three Top Capital Markets Trends of 2024
As the curtain comes down on 2024, GreySpark Partners takes a look back at the three main capital markets trends from this year:
The Transition to T+1 Trade Settlement
2024 was a watershed year for capital markets, with the US becoming the first western economy to transition to a shortened ‘T+1’ security trade settlement period. While the switch to T+1 aims to reduce counterparty risk and improve market liquidity, the impact of T+1 extends far beyond achieving market objectives.
The switch to T+1 has encouraged a wave of innovation that has arguably been necessary for the maturity of the capital markets industry. With some major financial institutions staying dependent on familiar but often cumbersome legacy infrastructure across the front-to-back offices, the shortened settlement cycle has given them no choice but to upgrade systems in order to meet the demands of a compressed trade settlement period.
For example, any trade settlement bottlenecks already being experienced on ‘T+2’ were likely to be exacerbated on T+1. In the capital markets industry, inaccurate and out of date standing settlement instructions (SSIs) are a key cause of trade settlement failures. SSIs are a set of instructions that dictate how a trade should be settled, including the bank accounts that should be used, the currency that should be used for settlement, and other important details. Cleaning up SSIs can be the difference between a firm achieving trade efficiency under T+1 or not. In order to do this, the DTCC suggested to clients to adopt TradeSuite ID processing, which is being established as an industry best-practice. TradeSuite ID leverages automation and allows firms to affirm and monitor the affirmation status of their trades by providing each trade with a unique ID code that can be tracked and managed, while providing a time stamp of trade orders. In doing so, this provides full visibility and transparency of a firm’s trades, while also helping to assist firms in regulatory compliance reporting.
As well as technical innovation, T+1 has also led to significant operational changes. Some financial firms dealing in US securities across the world have had to mobilise employees across the world in order to adjust to the time zone constraints resulting from same day affirmation and confirmations. Firms have also had to ensure business processes, such as pre-funding of transactions, have been optimised in order to meet their counterparty obligations, and that operational resilience standards are maintained.
Generally, the US T+1 transition has been a success, and has instigated other major economies to move to T+1 in order to maintain alignment. This quarter, the EU and UK announced plans to move away from T+2 and toward T+1 in a coordinated approach, taking effect from Q4 2027. Following the announcement, EU-based financial firms are advised to start giving early consideration to how their future operational and technological processes may look in a T+1 environment. Leaning on experience from financial firms in the US in this regard could prove invaluable.
Adoption of Generative AI
Generative AI is poised to revolutionise the capital markets landscape, and this innovative technology has the potential to make a deep impact across the entire trade lifecycle.
Most people have been introduced to generative AI using the well-known application, ChatGPT, which was released by OpenAI in 2023. To say that ChatGPT is AI’s ‘killer app’ would not be an exaggeration – it is the most popular app in the history of the world, with the closest rival being TikTok. To further put this into context, it took TikTok 10 months to reach 100 million users, while ChatGPT achieved this in just two.
Among financial institutions, generative AI finds itself at the start of a long maturation journey, which is still shrouded in both excitement and uncertainty.
However, 2024 gave an early indication about how generative AI may be included in an institutional trading desk. As GreySpark observes, this includes:
Analysis of Text, Including News and Social Media Sentiment: using advanced transformer models such as GPT-3, AI-powered sentiment analysis has become more accurate and efficient, enabling traders to make better-informed decisions based on real-time data.
FX Trading Signal Predictions: : including AI techniques in the process improves human decision making and risk management and enables traders to optimise their trading strategies. The strong dependency on trustworthy and reliable data has created opportunities for market data providers. For instance, Refinitiv has recently collaborated with Bank of China to enhance Eikon’s FX trading signal prediction application.
Order Flow and Market Impact Predictions: AI-driven execution algorithms can help prevent slippage and minimise the costs of execution. Using Generative AI, a trading team can make more trades in a shorter amount of time and increase their profits.
Identification of Counterparty Risk: Generative AI platforms monitor counterparties in near-real-time to quickly identify and respond to potential risks. For example, Generative AI algorithms can monitor news articles and press releases to determine a counterparty’s creditworthiness, which will be relevant for counterparty risk management. Ultimately, Generative AI predictive analysis capabilities could be transformative for assessing risk levels associated with different counterparties based on historical data and real-time market conditions.
Completing Trade Data for Settlement: By analysing historic patterns, market trends, and transaction data, AI tools can detect potential irregularities that may result in settlement failures. Generative AI leverages sophisticated machine learning methods to identify anomalies in trade records and evaluate the associated risks within a context-search framework.
Reduction in Rekeying: Generative AI streamlines trade confirmation documentation by automatically populating templates with trade details, ensuring accuracy and efficiency. This technology optimises the documentation process, making it ideal for legal and compliance purposes.
Post-trade Automation: Generative AI leverages machine learning and advanced algorithms to mitigate settlement failures. It automates and optimises processes, reducing manual errors, detecting anomalies, ensuring precise trade matching and improving operational efficiency. Its predictive analytical capabilities can provide insights into potential failures, enabling proactive measures to mitigate the risks.
Inherently, generative AI poses a unique set of ethical and cybersecurity concerns, with model bias being the main one. This year, the enforcement of the first comprehensive set of regulations pertaining only to AI, the EU AI Act, reflects the urgency of acting to counter the evolving risks as well as the speed of adoption of this technology. The legislation should go a long way in allowing banks to establish controls and implement governance measures to ensure both safety and effectiveness of the application of the technology in the financial services. Regardless, emerging generative AI applications should be approached with a large degree of caution, with deep consideration over the implications of its use as we head into 2025.
Deepening institutional integration of crypto and digital assets
The integration of cryptoassets into the global financial system deepened this year, with the arrival of 11 spot Bitcoin exchange-traded funds (ETFs) in the US in January. This has opened the floodgates to wider institutional adoption of cryptoassets, putting access to them only one click away. In many ways, the inception of spot Bitcoin ETFs marked the formal recognition and acceptance of crypto as an asset class at the institutional level. Institutional interest has helped drive the price of Bitcoin to a new all-time high of $108,000.
In addition, a Trump Presidency in the US promises a more progressive crypto regulatory environment, with a probable lifting of the SAB 121 custody rule for US custodian banks set to allow more financial institutions to hold crypto on their balance sheets. The resignation of current SEC chairman Gary Gensler and the likely appointment of crypto advocate Paul Atkins in his place may also provide fertile ground for cryptoassets to flourish, putting an end to the turf war between different regulatory bodies such as the SEC and CFTC who have sought to define cryptoassets under their own frameworks. This has led to confusion and hindered greater involvement in cryptoassets at an institutional level.
The EU’s Market in Crypto Assets Act (MiCA), which enters into force on 30 December 2024, also marks a significant regulatory milestone in the world of cryptoassets. MiCA is the first comprehensive set of regulations, globally, tailored specifically to cryptoassets. The framework seeks to enhance crypto investor protections by improving transparency and enforcing anti-money laundering practices among cryptoasset service providers. MiCA is likely to set the precedent for the development of other crypto regulatory frameworks across the world, with the UK proposing a similar crypto regulatory framework to MiCA.
Like with generative AI, cryptoassets currently find themselves on a long maturation journey. With its origins firmly rooted in the retail market, crypto infrastructure across the entire trade lifecycle is arguably not yet fit for institutional purpose. For example, the vertically integrated nature of cryptoassets mean that trading, settlement and custody are often conducted under one roof, leading to heightened counterparty risk. In order to address this hurdle, institutions are increasingly relying on novel third-party crypto custody providers with limited track records and regulatory-binding investor safeguards. One answer to this may be leaning on practices used in the traditional finance world, with the development of crypto prime brokerage models that provide holistic management of the crypto trading process (i.e. portfolio monitoring, execution management) and managing counterparty risk. In this regard, Coinbase Prime has been one of the main frontrunners with its ‘Coinbase Prime’ model.
In addition, tokenisation among financial institutions has proliferated this year. It is increasingly looking a case of ‘when’ and not ‘if’ the majority of securities markets become tokenised, with the benefits of blockchain including instant cross border settlement starting to be realised. HSBC, JP Morgan and Blackrock have all announced their own tokenisation projects. For example, in March 2024, BlackRock launched its first tokenised asset fund, The Blackrock USD Institutional Digital Liquidity Fund, on the Ethereum network. The fund is represented by the blockchain-based BUIDL token, and is fully backed by cash, US treasury bills and repurchase agreements.
2024 has been another progressive year for capital markets, with the rapid technological advancements being spurred by shortening trade settlement periods, generative AI and digital assets. We look forward to seeing what 2025 has in store for capital markets.
That’s all for this year. Thank you for your continued support and readership on Substack, and we look forward to bringing you more capital markets content next year.
Merry Christmas and a happy new year. We’ll be back very soon!
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