COVID-19 accelerated societal and technological changes at a pace we never imagined.
At the onset of the pandemic, market volatility surged and volumes soared. Nasdaq topped several records across its markets, including the U.S. equities market experiencing its highest volume day since 2009, reaching about 5 billion messages, which was about two times its previous all-time high. The Options market recorded ten of its most active days ever, peaking at about 62 billion messages on a single day.
The events of 2020 demonstrate the importance of maintaining resiliency, capacity, performance, immediacy and security across our businesses. It is against this backdrop of unprecedented change and opportunity that we identify the four technology trends that we believe will have the biggest impact on our industry and outlook for the year ahead.
Systems on chips (SoCs) and field-programmable gate arrays (FPGAs) are not new, but we are excited by recent innovations in this space. Notably, we are seeing the rise of Advanced RISC Machine (ARM) architecture for central processing units (CPUs) and advancements in graphics processing units (GPUs) and machine learning optimized chips. These innovations allow us to build more efficient trading systems, deliver better performance, reduce complexity, lower the cost of end products, increase profitability and add new features that differentiate our products. They are having a profound impact on our business – and the financial services industry as a whole – especially as the industry migrates to the cloud.
Edge cloud is reducing reliance on centralized processing (processing performed in one computer or in a cluster of coupled computers in a single location), bringing greater scale and performance to consumers in an increasingly connected world. We see myriad practical use cases outside of financial services such as in internet of things (IoT), vehicular and drone applications. In the financial services industry, edge cloud can support workflows designed to evolve customer engagement models and provide deeper insights from data, as well as enable hybrid cloud strategies.
The powerful combination of cloud, federated learning and homomorphic encryption could potentially overcome regulatory and other barriers to sharing and analyzing data for purposes such as fighting financial crime and improving market integrity. The cloud is a neutral, secure infrastructure for internal and external stakeholders to share, analyze and act upon data, and the hyperscale cloud providers have tools to help organizations do it. With federated learning, organizations can share insights without actually sharing data. Moreover, homomorphic encryption is emerging as a technology that can allow organization to share data, retain complete control over who can access or perform analysis on it, and have auditability of that process.
SaaS in the Cloud
The adoption of the software-as-a-service model (SaaS) in the cloud is rapidly accelerating. Financial institutions and marketplaces are finding that it is much faster and cost effective to onboard clients as well as upgrade products and deliver new ones. SaaS in the cloud contributes to our resiliency and security because it alleviates some of the potential risk of downtime in our own data centers. Deploying infrastructure as code allows us to manage and define the desired state of our technology infrastructure using configuration files, and determine the security configuration before it is deployed in a public cloud.
Tech Trends 2021
Discover the tech trends in 2021 that are reshaping markets everywhere and driving the global economy.
Going forward, we see an opportunity to leverage innovations in SoCs, edge cloud, machine learning and encryption techniques, as well as SaaS to make us even stronger and more agile.
Custom chips are key to next generation compute
Systems on Chips (SoCs) are not new, but recent innovations in this space are affecting Nasdaq’s business – and the financial services industry as a whole – especially as we and the industry migrate to the cloud. Essentially, these advancements are giving us the tools and flexibility to design faster, more efficient and resilient trading systems.
Hardware Advancements Powering Innovation
Google was a pioneer in this space with its custom machine learning hardware known as the Tensor Processing Unit (TPU).
Amazon Web Services
AWS unveiled Inferentia, a custom piece of silicon that is meant for machine learning workloads.
Nvidia’s GPUs were invented to produce realistic video game graphics, but they are also highly suitable for training neural networks in machine learning and artificial intelligence.
Edge cloud is bringing greater scale and performance to consumers
Edge cloud is a dynamic and distributed cloud model where compute and storage resources move close to the edge of the network, where content is created and consumed. It reduces reliance on centralized processing, bringing greater scale and performance to consumers in an increasingly connected world.
At Nasdaq, we see myriad practical use cases for edge cloud. Data can be collected from sensors in roadways and traffic lights to gauge traffic flow and price tolls dynamically. It can be collected from machines in a factory, and then sent to a nearby location for analysis to determine when the device is likely to fail or need maintenance. An aircraft engine manufacturer can retrieve specific metrics in-flight, and then do the bulk downloads of telemetry data at the airport gate. Pharmaceutical companies can instrument their vaccine shipments, so they receive an alert if the temperature deviates from the correct parameters – a critical use case in the age of COVID-19.
Edge Cloud Applications within Financial Services
Marketplaces and financial firms can create a special purpose or customized cloud that is aimed at addressing the needs of certain workflows.
Retail banks can use edge cloud to enhance their client experience on apps, tablets and kiosks.
Investment managers can use low-latency edge computing to make predictions with machine learning models trained in the public cloud using alternative datasets.
Nasdaq's Accelerated Path to the Cloud
Transforming the Capital Markets of Tomorrow
Saas in the Cloud
SaaS empowers technology providers to utilize their underlying infrastructure to onboard clients, respond to changes in client engagement, upgrade products and deliver new ones much faster as well as achieve scale. SaaS in the cloud is an even more compelling proposition.
Through SaaS transformation, we can scale our business quicker, and deliver better and more flexible products and services to our clients.
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