Cloud-focused partnerships are initiatives that have gathered steam recently, due to the huge volumes of data required for running analytics, achieving best execution and reducing risks. Indeed, in September 2020, both Aquis Exchange and the Singapore Exchange (SGX) signed agreements with Amazon Web Services (AWS) to build a financial environment based on cloud and cost optimisation. This allows new participants much easier, as well as cheaper, access to the markets. With a pliable infrastructure, market players can now supply their clients’ toolkits with developing models, data analytics, algorithms and machine-learning solutions, which may be used to originate go-to-market ideas that deliver new products and services.
Even the Covid-19 Pandemic has pushed financial institutions to invest in performative and secure digital services, with the aim of facilitating capital markets staff working at home for an extended period of time.
In early November 2021, the final stage of a ten-year process was carried out, when Google Cloud invested $1 billion in CME Group, a major global trading platform. Under this agreement, CME is going to commence moving its technological infrastructure with data and clearing services in 2022, and thereafter it will shift its markets on to the cloud. Another ten year, strategic agreement with Google will allow CME to offer its participants a faster system as well as develop new instruments, thanks to Google technology such as risk mitigation tools, a more user-friendly platform and more efficient analysis services.
Nowadays the broader use of remote working leads financial institutions to consider the migration to cloud of many of their activities, with an eye on evolving financial risks (liquidity, market and credit), non-financial risks (cybersecurity and fraud) and regulatory demands. However, for many firms, data protection is a high priority and the perceived lack of security and control in cloud environments has resulted in a slower adoption and use of cloud platforms.
That said, the main short-term challenge is to connect, without hacks or delays, data centres with multiple cloud providers in order to create a high-performance network. This is the reason why financial institutions should look at a long-term plan of 5 or 10 years to build a digital infrastructure with multiple entry points. Despite the potential benefits, migration to the cloud needs significant investment in resources, and a resilient plan for managing the financial impact. The economic effort needed to migrate and operate in the cloud may require huge investment over many years, although most cloud providers offer incentives for long-term agreements. Most of these expenses are focused on the research of analytical and technical talents to develop and maintain the database, with testing, and with improving algorithms and tools, and furthermore in investment in computing power. Today’s datasets are huge, and the volume of data comes from multiple sources in a variety of formats. For processing information, financial institutions need a performing, and adequate, infrastructure that is able to read a continuous flow of real-time data and run faster and easier models to mitigate risk or predict market trends through “what if” scenarios (i.e. Monte Carlo simulations).
In addition, the adoption of cloud infrastructure by data providers and exchanges (e.g. Bloomberg, Nasdaq, CME Group and S&P) has led a large number of financial organisations to approach cloud innovation in order to leverage benefits. The ability to have quick access to technology has brought an increase in the number of market players and so too greater competition in capital markets.
Algorithmic trading engines could provide a solution to manage big datasets, where strategies are created and tested with historical and real-time data in the cloud. This could improve best execution in fragmented markets, switching the behaviour of algorithms according to real-time market trends. For predicting market movements, machine-learning algorithms collect and use data related to the evaluated financial asset and to every correlated instrument, supported by real-time technical and fundamental analysis. Obviously, if the amount of data that needs to be processed is not huge and power computing is enough, the algorithm is more responsive to changes. In order to execute heavy datasets needs high-performance computers which are very expensive. An option to avoid full migration to the cloud is a hybrid trading approach. Initially, financial institutions migrate only their heaviest datasets and selected functionalities to the cloud, keeping their own trading platform separate. With a gradual and planned migration, project teams can move other components and complex functions later, conducting tests to fine-tune performance and risk mitigation.
The latest developments are more of a digital revolution than just a transformation for financial markets, and the Covid emergency has only accelerated this process. On the subject of creative destruction, Joseph Schumpeter says: “an innovator could, through a new product or lower costs of production, establish a dominant position in a market. But eventually, that dominant position would be destroyed, as another new product or process was invented”. We are on the peak of an innovation cycle, and capital markets digitalisation is flying above the cloud!
©Markets Media Europe 2022
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