Financial institutions are undergoing digital transformations that are seeing them harness the full potential of the huge volumes of data they generate. Importantly, to do that they are deploying the technologies that are already defining our era – artificial intelligence (AI) and the cloud.
From streamlining back-office processes to informing front-office decision making, and from powering transactions and research to enriching customer services, banks and other institutions are investing heavily in AI- and cloud-enabled data to optimise their operations and services.
As the data ecosystem has expanded and challenges over its sourcing, management, distribution, application and storage have grown, solutions are being found in these two ground-breaking technologies. No longer is it feasible to rely on the in-house technology stacks that have served banks through the past decade or more. Recognising that their need to continue this expansion is unlikely to end soon, institutions are looking to the cloud to scale their data capabilities, take advantage of the latest processing technology and all the while maintain control over this most valuable of resources. And they are seizing the potential of AI to mine value from that data.
Cloud data platform provider Snowflake is at the vanguard of this transformation. It’s demonstrating not only its own capabilities, but also explaining the benefits that cloud data management and AI can bring to a broad range of industries in an ambitious Data Cloud World Tour of showcase events in 26 cities around the globe. The next stop of this mammoth project will be in London, where more than 3,000 market participants, vendors and data professionals are already registered to attend.
At a series of events planned for the October 10 conference, high-level executives and experts from institutions operating within the data ecosystem, including State Street Alpha, JPMorgan Chase, Aviva and Capital One, will elaborate on how they are finding solutions in cloud data services.
The AI Future is Here
News headlines have been focused recently on stories about the potential of public Generative Artificial Intelligence (GenAI) application ChatGPT. The most widely recognised of this latest AI technology has potential way beyond composing digital pop songs or writing emails, the focus of many media reports on the technology.
In data management, the potential uses of GenAI, powered by large language models, has been recognised by many financial institutions, including State Street. For instance, it can help in the cross-mapping of datasets, the classifying of data and more generalist applications such as summarising reports and responding to plain English inquiries.
With Snowflake, State Street Alpha is taking the application of GenAI further by applying it to aggregate content at scale and enabling clients to access proprietary and publicly available market data more easily.
The Alpha platform uses GenAI with Snowflake as a strategic partner providing the data foundation of the platform. Snowflake’s cloud-native architecture streamlines data sharing and governance, enables faster time to market for data-centric applications, and offers a rich environment of AI and machine learning-based capabilities for data scientists, quants and engineers.
“Every few years, the technology landscape re-sets, creating a small window of opportunity that in turn enables a giant leap in innovation; GenAI is the opportunity that will define the new set of industry leaders over the next decade,” State Street Executive Vice President and Chief Architect Aman Thind tells A-Team Group. “At State Street, we’ve made large investments in harnessing GenAI, and look forward to demonstrating how we’re empowering our clients with this transformative technology.”
Managing Enterprise Data
Not only are organisations generating huge volumes of actionable data from within their own operations, but they are also buying additional content from external vendors to help with a growing list of use cases, most notably regulatory reporting and environment, social and governance (ESG) workflows.
Marrying all this data within their proprietary enterprise data management (EDM) systems is an evolving challenge. The cloud, however, is providing them with the compute and storage power, flexibility and scale to accommodate these ever-changing demands.
“One of the major opportunities we see is in reducing the time to insight from data to enable rapid, accurate customer decision making and support,” Capital One UK director of data engineering Gareth Thomas, tells A-Team Group. “Prior on-premises data solutions have typically brought challenges in terms of both performance and capacity, with data scientists and analysts having to work within system constraints and limitations, all which put up roadblocks to pace, and depth of insight generation.
“Snowflake data cloud changes all of that – we have seen immediate benefits for our analysts, with data queries completing far faster,” Thomas adds. “And, this is even when we’re running daily batch data loads and sensitive data management processing at the same time – something that would have been impossible to have achieved with on-premises data capabilities.
“And, with the true separation of storage from compute, Snowflake Data Cloud will enable us to easily grow our data for decision making, all whilst scaling to support the data management required.”
Connected Banking Data Apps and Services
The scale and flexibility that the cloud offers means that it can provide a blank canvas on which financial institutions can build powerful, bespoke apps to help in their data management processes. Providers can connect cloud-native data applications and services that can be utilised by multiple uses cases and scaled according to need. Banks can also benefit from app-building tools hosted by cloud providers.
J.P. Morgan is collaborating with Snowflake as part of their cloud-native data platform, Fusion by J.P. Morgan. Fusion provides institutional investors with end-to-end data management, analytics, and reporting solutions, enabling clients to integrate and combine data from multiple sources into a linked data model, and to retrieve that data via modern distribution channels including Snowflake.
“As institutional investors seek to leverage data to drive operational efficiency and generate new sources of alpha, having easy access to investment data is critical,” Gerard Francis, Head of Fusion Data Solutions at J.P. Morgan explains to A-Team Group. “Fusion now enables clients to retrieve their Securities Services data directly from their Snowflake instances and Python notebooks. We’re meeting clients where they are as they transition to a modern technology stack.”
ESG Data Management
ESG is a sprawling ecosystem of multiple datasets, formats and sources. But as regulatory oversight of the way capital is funnelled towards sustainable and socially responsible economic activities increases, institutions have no choice but to get to grips with the multiple challenges its management poses. They also face demands from customers and clients to ensure they lend and invest sustainably.
The UK’s NatWest Bank group has worked with Snowflake to ensure the ESG it needs is properly managed, governed and distributed across the bank in a way that meets growing demands place on the data.
“All the bank’s business heads are bringing more and more use cases for ESG data, driven by customer and investor demand,” Kaushik Ghosh Dastidar, head of ESG data and solution architect at NatWest explains. “Across the entire entity of a financial institution, there’s a joined-up data requirement that’s come up. So, we have moved completely to cloud.”
In particular, Snowflake’s data cloud platform services have helped NatWest seamlessly automate access to, and onboard, data from multiple vendors.
“Cloud is the only technology that allows us to do that at pace across a wide set of customer data,” says Kaushik.
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