Weekly digest
Weekly news up to 26/01/2024, Issue #19
Hello everyone and welcome to the latest edition of GreySpark Insights.
We hope you all had an enjoyable festive period, and we wish you a happy and productive 2024.
Please do not hesitate to contact us with any questions or comments you may have. We are always happy to elaborate on the wider implications of these headlines from our unique capital markets consultative perspective. Happy reading!
💥Top story
EU to copy US in speeding up equity settlement to cut risk (see more below)
📰Newsflash
📈Buyside
Buy Side Puts More Emphasis on Electronic Trading
According to research from Coalition Greenwich, electronic trading platforms captured 44% of buy-side U.S. equities order flow in 2023, up from 42% in 2022. Additionally, roughly 37% of overall 2023 volume was executed through algorithms and/or smart order routers, reflecting an increase from 35%. According to Coalition Greenwich, algorithmic trading will conduct 40% of overall trading volumes within the next three years. Portfolio trading remained relatively stable, coming in at 12-13%. Even though electronic trading continues to gain traction, it still remains secondary to high touch trading.
Asian asset managers agree on Hong Kong spot Bitcoin ETF
Following the recent approval of a Bitcoin spot ETF in the US, it seems Bitcoin ETF fever has spread across to APAC markets. Value Partners Group and Venture Smart Financial Holdings (VSFG), two Hong Kong-based assets managers, this week reached a memorandum of understanding to collaborate on offering traditional investment vehicles (including ETFs) underpinned by digital assets to local retail and institutional investors. According to reports, Hong Kong could debut spot Bitcoin ETFs in the region by mid-2024, with regulators taking a friendlier stance to Bitcoin ETFs than other jurisdictions. Around ten hedge funds in the region have also expressed an interest in launching spot Bitcoin ETFs.
📉Sellside
71% of UK and US Banking Institutions Concerned About Regulatory Processes; AutoRek Reveals
A survey of 500 banks across the US and UK found that 71% agree that their financial control processes are not robust or flexible enough to accommodate more regulatory change. The findings come at a time where significant regulatory changes are due to be implemented over the coming months, including European Market Infrastructure Regulation (EMIR) Refit and revisions to MiFID II. In EMIR Refit, one of the key changes will be the increased number of reportable fields for existing and new derivatives transactions, rising from 129 to 203. Reporting standards must also be made using a common template made on ISO20022 standards. The MiFID II revisions largely concern transaction and reporting requirements, which you can learn more about here. At this time, optimising core back and middle-office functions must be a top priority for banks to streamline operations, get in control of their data and achieve regulatory compliance.
ION launches FI EMS to simplify fixed income trading
Trading and analytics platform ION has launched a new product for sell-side (and buy-side) fixed income traders. The solution, called FI EMS, aims to ease challenges around selecting counterparties and sourcing liquidity by digitising the entire dealer-to-customer (D2C) trading process. According to ION, trading desks are under pressure to deliver best execution across different bond asset classes and, therefore, they are increasingly considering digitising the D2C trading process. Digitising this process helps to automate liquidity sourcing and price discovery, helping traders to navigate fragmented markets.
✴️Digital transformation
BNP Paribas launches UK fintech incubator
BNP Paribas announced this week that it is to launch a UK innovation lab that addresses data-led challenges in the financial services sector. The lab is inviting applications from SMEs - rather than traditional fintechs - for an incubator programme focused on harnessing external data and insights to boost engagement with financial services customers. The programme could lead to the establishment of future business partnerships for BNP, and lead to new data solutions hitting the market.
JPMorgan anchors $300 million funding round in Quantinuum
JPMorgan Chase has coordinated a $300 million investment round in quantum computing startup Quantinuum, valuing the business at $5 billion. JPMorgan has has been working with Quantinuum and its predecessor companies since 2020, exploring possibilities for a quantum processor. Quantum technology represents an exciting next step for the capital markets industry, as the industry seeks to achieve higher levels of processing power and increase trade execution quality and portfolio management. Other major financial institutions are currently exploring the potential of quantum computing. In June HSBC also began work with Quantinuum on a series of exploratory projects looking at the use-case of quantum computing in banking.
📱Technology trends
Finastra and Databricks forge alliance to revolutionize FinTech with advanced AI and data solutions
Finastra, a global leader in financial software applications and marketplaces, and Databricks, a renowned data and AI company, have announced a strategic partnership. The partnership is driven by the objective to provide more advanced data and AI-driven solutions and services to financial institutions globally. The collaboration will allow Finastra to unlock the full potential of its data, integrating AI, including generative AI (Gen AI) capabilities, to enhance product quality, performance, and security, while reducing time-to-market.
Eurex to launch derivatives on Socially Responsible Investing indices
Derivatives exchange Eurex will expand its equity-index linked product line with futures on Socially Responsible Investing (SRI) indices. SRI Indices are designed to represent the performance of companies with high environmental, social and governance ratings. Starting from 22 January 2024, Eurex will begin trading futures on SRI indices calculated by STOXX and MSCI, who are strategic partners in Eurex’s offering of derivatives on ESG indices. The offering should help investors facing stricter ESG mandates and need to invest responsibly, such as asset managers facing regulations under the terms of SFDR.
🧑⚖️Regulatory developments
EU to copy US in speeding up equity settlement to cut risk
According to European Commissioner Mairead McGuinness, it is now a case of ‘when’ and not ‘if’ EU capital markets halve the time it takes to settle equity trades. Currently, the EU operates on a two-day settlement cycle. However, following the move from the US to switch to a one day settlement cycle from May 2024, the EU has come under pressure to switch to a one-day settlement cycle in order to retain global trading alignment. In theory, the switch to a one-day settlement cycle should increase market efficiency and reduce counterparty risk, because it reduces the amount of exposure to a counterparty during uncertain times. Nevertheless, a switch to T+1 settlement in the EU will pose a significant structural challenge, given the high number of exchanges and counterparties in the EU.
ECB report reveals shocking climate risk in 90% of European banks’ portfolios
After an assessment of the credit portfolios of 95 global and regional banks by the ECB, results found 90% of banks’ loan portfolios are not aligned with global climate goals and the EU’s 2050 climate neutrality target. The ECB employed an alignment assessment focused on several carbon-intensive sectors, including oil & gas, and coal. Remarkably, only 8 out of 95 banks had lending practices in line with the EU’s 2050 net zero pathway. Additionally, despite 72 banks committing to net zero, a concerning 93% are yet to align their strategies and internal processes to achieve this objective.
📊Chart of the week
The model above shows how a bank can apply a standardised way of evaluating AI use cases. Specifically, this could be an AI trading workflow, such as an analytics platform or trading system. This model does not only prioritise where existing use-cases can be upscaled and modified, but also weighs up which new prospective AI technologies are the right ones to pursue. Each element of the AI return equation is explained below:
Income Uplift: AI can be used to create and augment new revenue streams. For example, AI use cases can contribute to portfolio returns through strengthening research and analysis.
Efficiency Gains/Cost Reduction: One of the main opportunities with AI is its potential in improving operational efficiencies, requiring the need for fewer resources for a given process. An example is the use of AI in payment processing, which can decipher what payment instructions need to be conducted among thousands of simultaneous client communications.
Risk Reduction/Avoidance: AI technology can provide a toolkit for understanding, controlling and mitigating a number of risk factors by enabling solutions like anomaly detection, anti-money laundering checks and cross-analysis of suspicious activity reports.
Customer Satisfaction: Using AI to help deliver a frictionless customer experience at multiple touchpoints help to build trust and reduce churn. For example, reducing operational downtime and providing round-the-clock service can help banks with customer satisfaction and retention in the face of growing competition.
Talent Satisfaction: Banks are in competition to attract and retain the best talent. AI can enhance and empower the employee experience, equipping them with the necessary skills to enhance their own personal capabilities.
Costs to Implement: Monetary and business costs of implementing AI.
Risks to Implement: Includes the impact of AI on multiple business lines and processes, the effort and expertise needed to operate the AI, and the infrastructure needed to accommodate the AI use case.
🐤Tweet of the week
Source: Jason Mikula via ‘X’
📄GreySpark insight
The successful implementation of a digital twin model requires firms to have already created a well-defined data strategy plan tailored to their firm’s unique specifications.
Given that digital twins consist of highly sophisticated hardware and software, the development, implementation and maintenance of a digital twin is typically highly complex. During the initial phase – digital twin data strategy – the firm may reach out to reputable, compliant third party subject matter experts with experience of implementing digital twin models. Failure to properly execute a digital twin model can lead to an unnecessary strain on resources and higher implementation and running costs, while leaving the firm vulnerable to operational risks. In many ways, poorly implementing a digital twin framework may do more harm than not implementing one at all. Crucially, failure to develop a robust and agile digital twin model could mean that financial firms will fail to achieve operational resiliency compliance – especially as existing regulatory frameworks, such as DORA, continue to evolve and become more nuanced.
The digital twin is increasingly becoming an integral part of financial firms’ operational resilience frameworks. According to MarketsandMarkets, digital twin technology in the financial services sector is set to be worth USD 0.5 billion by 2028.
Discover more here.