A symbiotic relationship: the criticality of data and technology
10 June 2024
Data remains critical to the enablement of technological change, says Matthew Chessum, director of securities finance at S&P Global Market Intelligence, who explores ways to remain at the forefront of innovation
Image: stock.adobe.com/Alexander
Data and technology are intricately linked. This has been the case since the industrial revolution, where the collection of data was used to enhance manufacturing processes to develop higher quality and cost-effective products. Strong, reliable data was instrumental in driving technological advancements by providing the insights, inputs and feedback necessary to improve performance, enhance user experiences and drive innovation across various industries.
Data has always been important within financial markets as it enables informed decision making, better risk management, a more effective evaluation of performance through the recognition of trends, it facilitates price discovery and, most importantly, it fosters competition among market participants. By disseminating information efficiently, data helps to ensure that financial markets operate smoothly and effectively. The collection and analysis of data identifies areas requiring improvement and helps to prioritise future development. In short, market innovation would not be possible without data as it remains critical to the enablement of technological change.
Recently, we have seen how the importance of processing data 鈥� through new mediums such as artificial intelligence (AI) 鈥� has led to strong investor sentiment in the financial markets. The increased understanding of the power and technological change that can be harnessed using AI has been reflected in the stock prices of the much-celebrated group of stocks known as the 鈥渕agnificent seven鈥�. AI and large language models require data to perform and represent the next step in the data-led technological revolution that we are currently experiencing.
Within the securities finance markets, high quality and clean data is critical to providing the next generation of products and solutions that are required by market participants to continually improve multiple aspects of their day-to-day processes. With a focus upon collateral management, enhancement of the provision and timeliness of new and more complex reporting, as well as reducing transaction times and costs, S&P Global Market Intelligence continues to use its proprietary data available to build stronger, deeper and more competitive securities finance markets through a number of different initiatives.
Research papers
The securities finance data analytics team is constantly researching and testing new proprietary data sets to discover unique ways of generating market signals. Most recently, they discovered the benefits of using active utilisation and bond value divergence together for portfolio construction. Due to the uniqueness in their factor signal, they were found to be uncorrelated across the two universes. This report is just one of many that indicates the power that multiple datasets can have when combined.
The growing use of AI and machine learning
The realisation of the benefits that are directly linked to the increased adoption of AI continues to be felt across numerous industries. Across the securities finance landscape, AI continues to improve the quality and quantity of data that is being consumed within our data sets daily. It is also leading to enhancements in a number of data points, such as our daily short forecast predictions which are based on public data sets that are not published daily.
The development of enhanced narration on market share and performance criteria for individual client data sets is also adding a new and exciting dynamic to our product offering. Not only can we now supply insights through the data points themselves, but we can also provide a growing level of commentary regarding what the data is showing and, more importantly, what it may be reflecting.
As with all machine learning, those clients who truly embrace this technology in its early stages will see the true benefits of the machine learning process as the more data the system consumes, the more advanced the output will become.
The repo market
Our Repo Data Analytics tool provides transparency into the repo market that has, until now, never truly existed. Technology has led to the collection, dissemination and calculation of multiple data points across the repo landscape in a fully automated and timely manner.
Gone are the days of historical market reports and inefficient, backward looking market surveys being the only window into the repo market. By offering and packaging numerous data points, the tool allows for better risk and liquidity management, better decision making 鈥� especially when used in conjunction with the securities lending data set to evaluate route to market 鈥� and better regulatory planning. Innovation and technology continue to play a role in developing this product further, one example being the new ability to provide repo GC levels across maturity curves through the amalgamation of multiple data sets.
Collateral management
Finding new and innovative ways to finance long holdings and collateralise trading activity can be possible through the deployment of both data and technology. Using advanced exchange-traded fund (ETF) data analytics, it is now possible to match eligible collateral profiles to existing ETFs.
By matching collateral requirements to the exact specifications on a new asset type, collateral eligibility is increased, risk profiles remain unchanged, liquidity and efficiency grows and return on investment can be improved. Without the increasingly important symbiotic relationship that exists between data and technology, this process would be lengthy, inefficient and prone to human error.
Onboard accelerator
The efficient and timely onboarding of new funds into a securities lending programme is a critical task for both borrowers and lenders. Despite its importance, both revenues and competitive advantage continue to be lost through its numerous inefficiencies and the onboarding of new accounts remains both challenging and time-consuming.
The protracted timeframes needed to complete the process are reflective of its manual and clerical nature. Counterparts frequently spend time navigating various emails, spreadsheets and documents that are shared and requested multiple times. The onboarding process has suffered from a lack of innovation and consideration over the years, which has resulted in an ongoing administrative challenge for onboarding teams and a delay in the introduction and monetisation of new sources of liquidity.
Onboarding assets quickly into a securities lending programme is more than just an administrative task. Competitive advantage can be gained by simplifying the process, automating the processing of documentation and by reducing the administrative costs involved. The future of client onboarding is ready for a disruptive change.
Through the deployment of new data points and technology, a new digital solution capable of triggering a change of this magnitude is the S&P Global Market Intelligence Onboarding Accelerator for 网爆吃瓜 Finance.聽It is already transforming the client onboarding process and making it fit for the twenty first century, adding valuations into the workflow and vastly improving time to market and revenue opportunity.
Enrichment of intraday trading analytics
Improvements in technology have created the possibility to continuously process multiple transaction files 鈥渟ame day鈥�, delivering enhanced timeliness and more regular data updates throughout the trading day within our existing data portal. The increase in the ability to clean, process and publish this data has led to a more efficient marketplace where the nature of the over-the-counter market previously led to a dislocation of available data.
Higher frequency data provides more granular trading insights into the securities lending market. Monitoring market moves by viewing aggregate trade information for previously settled, pending and intraday trades had led to an improved analysis that can be produced by cumulatively seeing the totals for all loans and loan returns throughout the trading day. This increases transparency into intraday borrow costs 鈥� which, as we saw during the US regional banking crisis in March 2023, can change at an ever increasingly rapid pace.
Our intraday data set now covers 85 per cent of all market transactions. This accomplishment alone has moved the securities finance market from one based on historical data points into a world of almost real-time pricing and risk management.
Intraday transactions are processed continuously to update new trade information directly on the securities finance web portal and API based products. The increased ability for firms to ingest this data directly into their systems has led to more accurate pricing, better positioning, and a more truthful view of market activity.
Technology optimisation to enhance data flows
Embracing new technology continues to increase the speed and reliability of data flows, which in turn increases the ability to innovate. The introduction of our cloud-based modernisation model across the S&P Global Market Intelligence 网爆吃瓜 Finance environment has been living proof of this concept.
The latest web server optimisation tools have improved performance, scalability and speed while providing a better experience for customers. The adoption of Test Caf茅 for UI automation has also led to faster product development and releases. This new technology has permitted more data to be shared in less time, which feeds back into the virtuous circle of continuous technological improvement.
As this demonstrates, data advances technology in a number of different ways. It trains machine learning tools; it optimises performance; it helps in detecting anomalies,聽improving security as a result; and it helps to drive innovation further and quicker. By facilitating automation through the provision of the necessary inputs for automated decision making and controls that enable the execution of tasks without human intervention, data remains the critical component of nearly all technological enhancement seen in recent times.
Data can inspire multiple waves of data-driven innovation, as we learnt during the industrial revolution. The pioneering work demonstrated during the eighteenth century, and the transformative power of data in driving innovation and revolutionising traditional industries, continues to be experienced across multiple industries today.
The securities finance market serves as a testament to the enduring impact of data-driven approaches in the shaping of modern financial markets. At S&P Global Market Intelligence, we continue to embrace data-led technological change and look forward to working with our colleagues, partners and friends in the future to remain at the forefront of innovation and market led technological initiatives.
Data has always been important within financial markets as it enables informed decision making, better risk management, a more effective evaluation of performance through the recognition of trends, it facilitates price discovery and, most importantly, it fosters competition among market participants. By disseminating information efficiently, data helps to ensure that financial markets operate smoothly and effectively. The collection and analysis of data identifies areas requiring improvement and helps to prioritise future development. In short, market innovation would not be possible without data as it remains critical to the enablement of technological change.
Recently, we have seen how the importance of processing data 鈥� through new mediums such as artificial intelligence (AI) 鈥� has led to strong investor sentiment in the financial markets. The increased understanding of the power and technological change that can be harnessed using AI has been reflected in the stock prices of the much-celebrated group of stocks known as the 鈥渕agnificent seven鈥�. AI and large language models require data to perform and represent the next step in the data-led technological revolution that we are currently experiencing.
Within the securities finance markets, high quality and clean data is critical to providing the next generation of products and solutions that are required by market participants to continually improve multiple aspects of their day-to-day processes. With a focus upon collateral management, enhancement of the provision and timeliness of new and more complex reporting, as well as reducing transaction times and costs, S&P Global Market Intelligence continues to use its proprietary data available to build stronger, deeper and more competitive securities finance markets through a number of different initiatives.
Research papers
The securities finance data analytics team is constantly researching and testing new proprietary data sets to discover unique ways of generating market signals. Most recently, they discovered the benefits of using active utilisation and bond value divergence together for portfolio construction. Due to the uniqueness in their factor signal, they were found to be uncorrelated across the two universes. This report is just one of many that indicates the power that multiple datasets can have when combined.
The growing use of AI and machine learning
The realisation of the benefits that are directly linked to the increased adoption of AI continues to be felt across numerous industries. Across the securities finance landscape, AI continues to improve the quality and quantity of data that is being consumed within our data sets daily. It is also leading to enhancements in a number of data points, such as our daily short forecast predictions which are based on public data sets that are not published daily.
The development of enhanced narration on market share and performance criteria for individual client data sets is also adding a new and exciting dynamic to our product offering. Not only can we now supply insights through the data points themselves, but we can also provide a growing level of commentary regarding what the data is showing and, more importantly, what it may be reflecting.
As with all machine learning, those clients who truly embrace this technology in its early stages will see the true benefits of the machine learning process as the more data the system consumes, the more advanced the output will become.
The repo market
Our Repo Data Analytics tool provides transparency into the repo market that has, until now, never truly existed. Technology has led to the collection, dissemination and calculation of multiple data points across the repo landscape in a fully automated and timely manner.
Gone are the days of historical market reports and inefficient, backward looking market surveys being the only window into the repo market. By offering and packaging numerous data points, the tool allows for better risk and liquidity management, better decision making 鈥� especially when used in conjunction with the securities lending data set to evaluate route to market 鈥� and better regulatory planning. Innovation and technology continue to play a role in developing this product further, one example being the new ability to provide repo GC levels across maturity curves through the amalgamation of multiple data sets.
Collateral management
Finding new and innovative ways to finance long holdings and collateralise trading activity can be possible through the deployment of both data and technology. Using advanced exchange-traded fund (ETF) data analytics, it is now possible to match eligible collateral profiles to existing ETFs.
By matching collateral requirements to the exact specifications on a new asset type, collateral eligibility is increased, risk profiles remain unchanged, liquidity and efficiency grows and return on investment can be improved. Without the increasingly important symbiotic relationship that exists between data and technology, this process would be lengthy, inefficient and prone to human error.
Onboard accelerator
The efficient and timely onboarding of new funds into a securities lending programme is a critical task for both borrowers and lenders. Despite its importance, both revenues and competitive advantage continue to be lost through its numerous inefficiencies and the onboarding of new accounts remains both challenging and time-consuming.
The protracted timeframes needed to complete the process are reflective of its manual and clerical nature. Counterparts frequently spend time navigating various emails, spreadsheets and documents that are shared and requested multiple times. The onboarding process has suffered from a lack of innovation and consideration over the years, which has resulted in an ongoing administrative challenge for onboarding teams and a delay in the introduction and monetisation of new sources of liquidity.
Onboarding assets quickly into a securities lending programme is more than just an administrative task. Competitive advantage can be gained by simplifying the process, automating the processing of documentation and by reducing the administrative costs involved. The future of client onboarding is ready for a disruptive change.
Through the deployment of new data points and technology, a new digital solution capable of triggering a change of this magnitude is the S&P Global Market Intelligence Onboarding Accelerator for 网爆吃瓜 Finance.聽It is already transforming the client onboarding process and making it fit for the twenty first century, adding valuations into the workflow and vastly improving time to market and revenue opportunity.
Enrichment of intraday trading analytics
Improvements in technology have created the possibility to continuously process multiple transaction files 鈥渟ame day鈥�, delivering enhanced timeliness and more regular data updates throughout the trading day within our existing data portal. The increase in the ability to clean, process and publish this data has led to a more efficient marketplace where the nature of the over-the-counter market previously led to a dislocation of available data.
Higher frequency data provides more granular trading insights into the securities lending market. Monitoring market moves by viewing aggregate trade information for previously settled, pending and intraday trades had led to an improved analysis that can be produced by cumulatively seeing the totals for all loans and loan returns throughout the trading day. This increases transparency into intraday borrow costs 鈥� which, as we saw during the US regional banking crisis in March 2023, can change at an ever increasingly rapid pace.
Our intraday data set now covers 85 per cent of all market transactions. This accomplishment alone has moved the securities finance market from one based on historical data points into a world of almost real-time pricing and risk management.
Intraday transactions are processed continuously to update new trade information directly on the securities finance web portal and API based products. The increased ability for firms to ingest this data directly into their systems has led to more accurate pricing, better positioning, and a more truthful view of market activity.
Technology optimisation to enhance data flows
Embracing new technology continues to increase the speed and reliability of data flows, which in turn increases the ability to innovate. The introduction of our cloud-based modernisation model across the S&P Global Market Intelligence 网爆吃瓜 Finance environment has been living proof of this concept.
The latest web server optimisation tools have improved performance, scalability and speed while providing a better experience for customers. The adoption of Test Caf茅 for UI automation has also led to faster product development and releases. This new technology has permitted more data to be shared in less time, which feeds back into the virtuous circle of continuous technological improvement.
As this demonstrates, data advances technology in a number of different ways. It trains machine learning tools; it optimises performance; it helps in detecting anomalies,聽improving security as a result; and it helps to drive innovation further and quicker. By facilitating automation through the provision of the necessary inputs for automated decision making and controls that enable the execution of tasks without human intervention, data remains the critical component of nearly all technological enhancement seen in recent times.
Data can inspire multiple waves of data-driven innovation, as we learnt during the industrial revolution. The pioneering work demonstrated during the eighteenth century, and the transformative power of data in driving innovation and revolutionising traditional industries, continues to be experienced across multiple industries today.
The securities finance market serves as a testament to the enduring impact of data-driven approaches in the shaping of modern financial markets. At S&P Global Market Intelligence, we continue to embrace data-led technological change and look forward to working with our colleagues, partners and friends in the future to remain at the forefront of innovation and market led technological initiatives.
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