Cloud and AI Paves the Future of Finance: Excerpts from FIA Boca 2022
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Financial markets were among the first to adopt new technologies, and that has certainly been true of the derivatives markets, which were early adopters of electronic trading. Going forward, new capabilities will transform the way industry participants communicate, analyze, and trade.
I sat down with Google Cloud’s Phil Moyer and former SEC Commissioner, Troy Paredes, for a fireside chat at FIA Boca 2022 to discuss the future of markets and policy, the new technologies that are already paving the way for greater speed and transparency, and how cloud can help promote greater resiliency, performance, and security to enable the long-term vision for the market. The following is a summary of our discussion.
The current state of cloud technology
When it comes to technology adoption, we’re seeing the market and participants adopt cloud technologies, and increasingly, machine learning (ML) on a wider scale. Cloud technology allows for easier, faster, and much more secure experimentation with large datasets and ML.
A recent Google sponsored study by Coalition Greenwich (September, 2021) showed that more than 93% of trading systems, exchanges, and data providers are in some way providing services on the cloud. The same study, revealed that about 72% of the financial industry across the buy side and sell side, intend to consume public cloud-data based market data within the next 12 months.
Data-driven decision-making and risk management have always been, and continue to remain, the cornerstones of the financial markets. Over time, technology innovation has facilitated access to better insights from data, and therefore, better decision-making and the ability to manage risk. That expectation is now mainstream, and will continue to grow in sophistication.
The multi-phased technology trajectory
The movement of exchanges to the cloud will occur in a “crawl-walk-run” fashion, with low-hanging fruits the first to be picked in the near term while bigger, paradigmatic changes will occur over the medium and long term. Some organizations are starting all three stages simultaneously, understanding that each will move at an independent cadence.
The “crawl” phase is one in which foundations are built, starting with organizations moving data to the cloud and experimenting with some degree of analytics. It’s one of the most important phases because it’s where the opportunity to increase transparency and risk management takes shape.
In moving to the cloud, the infrastructure – which in the past relied on a combination of people, processes, and some technology – becomes the code that runs applications. This early phase is key to empowering organizations to shift to a cloud-based, agile-first operating model that makes it easier and more seamless to launch new products in the future, including by freeing up people and resources from IT management to more mission-focused work.
Establishing the cloud operating model simplifies the “walk” and “run” phases where compliance is more automated, latency-sensitive applications are more readily available, and the next generation of exchanges, market participants, and regulators is better prepared to meet future challenges.
The “walk” phase is where much of the innovation happens. Exchanges are making significant progress in leveraging foundational data decisions in the “crawl” phase and innovations in the cloud to improve settlement, clearing, risk management, collateral management, and compliance, and launch new products.
And finally, the “run” phase is where organizations will start to move the latency-sensitive markets to the cloud, as the markets increasingly will demand low-latency and high performance along with transparency and analytics to solve historical obstacles to market access.
Opportunities for both regulators and market participants
Any time significant technological change takes place, regulators explore its implications, particularly with respect to their ability to meet their regulatory objectives.
Increasingly, we are seeing technological change driving more opportunities for regulators and market participants alike. Such changes may also allow better protection of the marketplace, with greater integrity and transparency.
Over time, regulatory regimes – rules, regulations, statutes, interpretations, and guidance – will also adjust to new technologies, both benefiting the marketplace and advancing regulatory goals.
As one example, the cloud is increasing the ability to meet compliance obligations by allowing compliance to be built into transactions. Moreover, predicated on the vision of real-time regulatory reporting, and given the pace of technological change in the marketplace over the last several years, various regulators have been using more advanced analytics. This trend will continue to help them more effectively and efficiently meet their objectives, and monitor and meet the expectations they have for the entire market.
Machine learning’s role in the financial markets
Google Cloud’s head of AI and Industry Solutions, Andrew Moore, said that ML will be doing three key things for us in the next 10 years: giving us meaning, providing concierge services, and serving as a guardian. Extracting information that is critical to investor decision-making can be extremely important. With more data than ever, ML can increase the ability to process it while also becoming more accessible in the cloud and better supporting regulatory objectives.
The technology will likely manifest in trading and anti-money laundering activities as they relate market functions, as well as managing a wide variety of risks – supporting the interests of both investors and regulators in terms of decision-making, surveillance, and protections.
Rather than taking individuals out of the equation, the digitization of markets, assets, and guard rails combined with ML will allow people to focus their expertise in different ways to achieve key objectives.
Building the market foundation for the future
The goals of operational resiliency, security, and privacy will continue to be critical for building the market foundation for both participants and regulators. While technology promises to create advantages in concrete, tangible ways, it will be important to scrutinize potential risks and concerns.
Priority one for technology providers is to build an environment of trustless security, including encryption at motion and encryption at rest, ensuring that markets are operationally resilient while instilling confidence for any exchange that runs on top of that infrastructure. Multicloud architectures and approaches are likely also to be part of the solution for operational resilience.
Throughout time, liquidity has been the outcome of improved access, transparency, and security. Technology providers are responding by sharing both the responsibility for, and fate of, the markets of the future to build an efficient, faster, and more transparent and secure financial industry.
You can learn more about our approach in our newest white paper, Building the financial markets foundation for the future.
Expert Takeaways on API Strategies from The State of API Economy 2021 Report
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Did you know API traffic for Apigee customers increased 46% year-over-year, to 2.21 trillion calls, between 2019 and 2020? If you have more questions on APIs trends and their role in disrupting enterprises digitally, you can catch up on key take aways from the Google Cloud’s State of API Economy 2021 report and insights from Google’s experts on API-best practices.
Business Evolution with API Ecosystems
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During uncertain times, ecosystem partnerships that leverage APIs have proven to help companies scale and address gaps in their businesses. Apigee customers, like CHAMP Cargosystems, have pursued API-first ecosystem models to enter adjacent markets, create new customer interaction models, and rapidly grow their brand reach and partner ecosystems. As a result of building their API ecosystem, they are transacting 300 million electronic exchanges and 20 million shipments per year.
CHAMP selected Apigee to provide an API platform and developer self-service portal option to all of its SaaS customers. Google Cloud’s Apigee API management platform and portal allows CHAMP and its customers to quickly connect to a variety of backend systems, including in-house, third party apps, marketplace portals and more– thereby accelerating their digitization strategies and opening up new markets through an API ecosystem.
Join this webcast and hear from this leading Enterprise company on how to:
- Identify new revenue sources and markets using an API management platform
- Improve time to market while still complying with all industry requirements
- How to create a proof of concept to grow API adoption throughout your organization
- Align internal business leaders and partners to see the importance of an API-first platform vision
Google Cloud Helps Northwell Health to Boost Caregiver Productivity and Access to Right Care Using AI
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Lung cancer is the leading cause of cancer death in the United States and like any cancer, early detection is crucial to survival. Screening at-risk populations is an important part of reducing mortality, and if concerning nodules are found on imaging, further testing may be required. Today, we’ll share how Northwell Health uses Google Cloud products such as Cloud Healthcare APIs and BigQuery to increase caregiver productivity and deliver better care for patients with findings that indicate potential development of lung cancer.
Northwell is New York’s largest healthcare provider
Northwell Health is New York’s largest healthcare provider with 23 hospitals and nearly 800 outpatient facilities. Northwell’s nearly 4,000 doctors care for millions of patients each year, and at this scale, there is an immense amount of healthcare data to manage. To better manage and leverage this data, Northwell Health partnered with Google Cloud starting in 2018.
Enabling caregivers to spend more time with patients
Nic Lorenzen, the lead developer of Northwell Emerging Technology and Innovation team, has a mission to put together data for caregivers in a way that makes sense. It is no secret that inefficient electronic health records systems have a negative impact on a physician’s ability to deliver quality care. Traditional EHRs have information distributed across many tabs, which forces caregivers to spend considerable time at the computer trying to find information. Moreover, speed of care matters. If care is delayed, patients may have to spend more time in the hospital and may suffer worse health outcomes.
To solve this problem, Nic’s team focused on giving caregivers the most relevant pieces of data at the right time by developing an intelligent clinician rounding app. The data needed to derive these insights can depend on the caregiver’s role–a nurse cares about different things than a cardiologist. This system aggregates multiple data sources, and provides patient-specific insights to caregivers.
This system would not have been possible before with traditional EHRs and data warehouses that have proprietary data models and rarely sync data in real time. Now with data easily accessible through Google Cloud’s Healthcare solutions, Nic’s team can deliver the right clinical information to the right people instantly. These days, Nic says, “instead of spending 75% of our time dealing with architecting the underlying platforms, we spend 75% of our time focused on higher value use cases for clinicians and patients. Google Cloud’s Healthcare solutions have greatly improved our developer productivity and time to value.”
Caregivers have found this new system to be a game changer.Before the implementation of this system, caregivers would spend, on average, seven to nine minutes finding the data needed to make medical decisions for one patient. Now, that aggregated information is delivered to a caregiver’s mobile device in less than a second.
Ensuring patients get the right care with the power of AI
There are a number of reasons why patients might not get the care that they need. For example, patients today can go to multiple hospitals and clinics settings, and coordinating care across multiple facilities is complex. Regional hospitals and clinics have their own siloed view of their data, so pertinent information gathered by one clinic might not be seen by another. These gaps in clinical data lead to gaps in patient care.
When a patient gets radiologic imaging, they may have findings unrelated to the reason they initially got the imaging. For example, a chest CT for a car accident might reveal an incidental lung nodule that could be cancerous. Unfortunately, research shows that a large portion of patients do not get follow up for these incidental findings because it isn’t the primary reason why the patient is seeing a doctor. Moreover, social determinants of health are a factor that affects which patients receive follow-up care. Identifying these patients and providing the necessary follow up care prevents adverse events related to delayed detection of cancer.
With Cloud Healthcare solutions, Northwell built an AI model to identify these patients so that oncologists can appropriately follow up with patients who have findings suspicious for lung cancer. The AI model detects incidental pulmonary nodules in radiology reports so that doctors can then contact the patients that need follow-up care. Nic says his team was able to build this system in a week: “Google Cloud did a lot of heavy-lifting for us and allowed us to get to the AI applications much faster. It allowed us to build a platform that just works.”
Healthcare systems can now rapidly generate healthcare insights with one end-to-end solution, Google Cloud Healthcare Data Engine. It builds on and extends the core capabilities of the Google Cloud Healthcare API to make healthcare data more immediately useful by enabling an interoperable, longitudinal record of patient data. Northwell Health uses Google Cloud as the core of their platform, enabling their developers to create solutions to the most pressing healthcare problems.
Special thanks to Kalyan Pamarthy, Product Management Lead on Cloud Healthcare and Natural Language APIs for contributing to this blog post.
Rapido: Finding the Quickest Route to Success with Google Maps Platform
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Founded in 2015, Rapido operates a mobile app-based two-wheeler taxi service across more than 40 cities in India. More than 100,000 drivers provide Rapido two-wheeler taxi services, while more than 400,000 current or prospective drivers have downloaded the company’s app. Consumers have downloaded the app more than 5 million times, and the business receives about 5 million orders per month for taxi services.
“If a consumer wants to travel from point A to point B, they simply open up the app on their smartphone, select pickup and dropoff locations, and tap ‘request,'” explains Rishikesh SR, Co-Founder, Rapido. “We can track that request to the nearest available two-wheeler taxi and allocate the job to the right driver.”
Google a compelling opportunity
The business started operations on a cloud service. However, Google presented a compelling opportunity to Rapido to improve its location-based intelligence through a wide range of cloud-based map APIs, infrastructure, and mobile app development services. “Google Maps Platform was particularly interesting to our business and we saw enormous potential to use it to improve our service and gain a competitive edge,” says Rishikesh.
Rapido elected to use Geocoding API to enable its app to convert addresses to geographic coordinates, and the reverse, allowing consumers to identify point A and point B on their journey. The company also uses Directions API to identify the fastest route between pickup and dropoff locations, which enables Rapido to provide users with approximate prices for trips. Distance Matrix API is used to calculate the travel times and distances between locations, and Maps SDKs for Android and iOS to add interactive maps to the app.
Google Cloud Results
- Enables the business to optimize use of Maps Platform APIs
- Takes 5 million orders per month
- Establishes a robust platform for expansion
“Google Maps Platform is particularly useful for us as it identifies optimum routes for two-wheel services,” says Rishikesh. “This saves us time and money, while helping us deliver a better consumer experience.”
In addition, Rapido uses the Snap to Roads service to deliver best-fit geometry for sets of GPS coordinates within the Roads API, which identifies and provides metadata about the roads on which drivers travel. “Snap to Roads in Roads API allows us to optimize the path drivers take and helps ensure the fare charged is accurate,” says Rishikesh.
Improving user experiences
As Rapido matured, Rishikesh considered how to improve the user experience of the app while reducing the business’ costs. In 2017, Rapido asked Google Cloud Premier Partner and Google Maps Platform Partner Searce to help meet these objectives. Searce provided the technical and business advice that prompted Rapido to take advantage of the unlimited API calls, 24-hours-a-day, 7-days-a-week support, and strict SLAs available through the Google Maps APIs Premium Plan for Asset Tracking.
Searce also helped Rapido optimize its API calls and integrate directions and distance calls with the Roads API to smooth out variations in GPS readings received from the handsets of two-wheeler taxi owners. Finally, Searce helped Rapido deploy the Firebase mobile and web development platform to automate the mode configuration of the API keys, rather than maintain a time-consuming manual process. This move also minimized the likelihood of any issues arising if Rapido decided to start multiple projects or add more licenses, or combine Google Maps APIs Premium Plan for Asset Tracking with an external license.
Technical skill and experience
Searce finalized its initial engagement with Rapido last year and provides ongoing support and advice. “Searce’s technical skill with Google Maps Platform put us on the right path to provide a better, more relevant user experience,” says Rishikesh.
Rapido also now uses a range of Firebase services for app development, testing, and modification. The business employs Google Analytics for Firebase to measure customer use of and engagement with its app, enabling the business to make informed decisions about where to direct its resources. In addition, the business is using the Firebase Test Lab app-testing infrastructure to test its Android and iOS apps across a range of device configurations, view the outcomes, and make changes as needed.
Rapido uses Firebase Remote Config to change the app’s behavior and appearance on the fly in response to the results of A/B testing across sections of its user base. Furthermore, Rapido uses Firebase Crashlytics to provide app crash reports to its Firebase console.
Firebase Dynamic Links allows Rapido to direct users to linked content in the iOS or Android version of the app, while Firebase Cloud Messaging enables Rapido to deliver notifications and other messages to users. Cloud Firestore provides a NoSQL cloud database to store and sync data for the Rapido app.
Rapido has also started using the Firebase Realtime Database to store and sync information about customers that can be used to provide a more informed, personalized service.
At the same time, Rapido uses a BigQuery data warehouse to process about 10TB of data every month for analysis and reporting that supports decision-making across the business. The organization is also using application containerization through Google Kubernetes Engine on Google Cloud Platform.
“We are moving our apps from dedicated virtual machines to a scalable containerized environment that consumes fewer resources,” says Rishikesh. “It makes sense to work with Google – the business that designed the Kubernetes container-orchestration system.”
Rapido has also started using the Cloud Functions event-driven serverless compute platform to process smaller jobs. “This is ideal for small use cases in particular as we do not have to spin up virtual machine instances,” says Rishikesh.
Finally, Rapido is using image classification through the Vision AI service to analyze riders’ documentation, such as driving licenses. This allows the business to verify details such as names, addresses, and expiry dates with more than 90 percent accuracy – a high rate in a country where each state has its own license template.
Expanding rapidly to new cities
The Rapido app enables drivers to pick up customers quickly – in most cases, between 2 and 5 minutes.
Overall, the high-quality experience for consumers and drivers delivered by Google Maps Platform, combined with Firebase, has helped power Rapido to robust growth. The business now takes more than 5 million orders per month.
“With Google, we are delivering the right experience to users through Google Maps Platform, Firebase, and Google Cloud Platform services,” concludes Rishikesh. “We have realized our vision faster and now have a robust platform to grow in the future.”
Managed containers: An enterprise standard at Colgate-Palmolive
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Kubernetes is an increasingly key part of the application deployment strategies at large organizations, and one of the most recommended options for the teams we work with. An idea brought to life at Google, organizations throughout the world use containers and Kubernetes on-premises, in Google Cloud, or in a multi-cloud scenario, and it has emerged as a leading application deployment platform. And because it’s open source, anyone can pop the hood, so to speak, to see how each component of it works, creating a trusted, verifiable framework that users can rely on.
Customers begin their Kubernetes and containerization journeys using various offerings in our product portfolio. Some, like Colgate, started their modernization journey with Kubernetes. Colgate is an $18B global consumer products company with ~34,000 diverse and dedicated people serving over 200 countries and territories. Through science-led innovation, they drive growth and reimagine a healthier future for all people, their pets, and our planet.
During ideation, they talked through various considerations: What technology strengths does their organization have? What skills do their teams need? What will this initiative look like a decade from now? They implemented the following Kubernetes-focused architecture:
Supporting a variety of use cases and teams
Google Cloud also helped Colgate break new ground over the years, especially in the areas of cloud-native networking, security, monitoring, pub/sub, managed containerization, and multi-tenant environments.
Over time Colgate began to leverage Google’s managed container portfolio, which includes Cloud Run. Cloud Run lets you run containers on top of a serverless platform, unlocking workload possibilities for public websites, private services, APIs and batch jobs and eliminating a lot of the time spent on infrastructure management. Cloud Run also requires no prior knowledge of Kubernetes or containers.
Simplified enterprise-level management
Many teams have found that they prefer the serverless, hands-off approach that Cloud Run provides, and Colgate now evaluates Google Cloud’s serverless solutions alongside GKE for any applications destined for the cloud. At the same time, Cloud Run lets them continue to leverage their investment in workloads based on the Open Container Initiative.
For example, Cloud Run is designed for Kubernetes compatibility with consistent management capabilities such as the ability to manage resources using kubectl via the config controller, and the ability to browse logs and metrics from both platforms in Cloud Logging and Monitoring. Cloud Run and GKE data planes are also interoperable, allowing Cloud Run and GKE services to be exposed behind a VPC behind private IPs using an internal load balancer. Cloud Run as an option has contributed to faster innovation, allowing Colgate to bring smiles to many more faces globally.
Google’s managed container offerings provide a composable and comprehensive set of solutions for customers’ applications. At Colgate, container-based managed services are used across the stack: on the front-end, where they use Identity-Aware Proxy to manage authentication and External Load Balancers to handle incoming traffic with high availability and low latency; at the application layer, where they can choose from Cloud Functions, Cloud Run, or GKE, depending on the level of control they need over the application; and at the internal load balancing level where NGINX® controllers serve internal applications. Together, these managed services ensure that Colgate has the flexibility to choose the right toolchain and maximize their goals for each use case.
Colgate wanted to build internal applications on Cloud Run in a way that complied with their organization’s policies while maximizing developer productivity. They were able to use new features like the Cloud Run Identity Aware Proxy GA to build a secure, serverless deployment for their applications.
A great partnership with Google Cloud
Colgate and Google Cloud have enjoyed a deep partnership for many years, engaging across many technologies, teams, and design patterns.
They’ve engaged with Product and Engineering across compute, networking, Kubernetes, and serverless as they brought this new way of thinking to their users.
For Colgate and many of our customers looking to address the needs of the modern user, Google’s managed container offerings are a breath of fresh air. Its reliability, scalability, and control offer the flexibility to build applications that meet the demands of both internal and external consumers. In addition, the variety of container offerings available on Google Cloud — GKE and Cloud Run — allow customers to make app deployment decisions based on the amount of Day 2 operations the users are willing to take on. Platform administrators appreciate the reduced management effort, users enjoy reduced downtime, and developers can simply deploy.
Google Cloud contributors: Rex Orioko, Rachel Tsao
Colgate-Palmolive contributors: Matthew Tattoli, Nicholas Farley, and David Wiser
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