New purpose-built analytics service reduces the
time it takes Financial Services Industry (FSI) organizations to
find, prepare, and analyze data from months to minutes
Legal & General and Deloitte among
customers and partners using Amazon FinSpace
Today, Amazon Web Services, Inc. (AWS), an Amazon.com, Inc.
company (NASDAQ:AMZN), announced Amazon FinSpace, a purpose-built
analytics service that reduces the time it takes FSI organizations
to find, prepare, and analyze financial data from months to
minutes. Amazon FinSpace aggregates, catalogs, and tags data across
an organization’s data silos, making the data easily searchable by
the entire organization. The service includes a purpose-built
managed Apache Spark analytics engine that contains over 100 data
transformations commonly used in the capital markets industry to
prepare data for analytics at petabyte scale. To make it easier for
FSI organizations to meet their compliance requirements, Amazon
FinSpace ensures that data access controls are enforced and usage
is tracked at all times. Amazon FinSpace provides an easy-to-use
web application that gives analysts at hedge funds, asset
management firms, insurance companies, investment banks, and other
FSI organizations access to the information they need and the
ability to run powerful analytics on demand across all of their
data. There are no upfront costs or commitments to use Amazon
FinSpace, and customers only pay for the data stored, the users
enabled, and the compute used to prepare and analyze data. To learn
more about Amazon FinSpace, go to
https://aws.amazon.com/finspace.
Today’s FSI organizations are generating and collecting hundreds
of petabytes of data every day from internal data sources like
portfolio management systems, order management systems, and
execution management systems—as well as third-party data feeds like
high-volume historical equities pricing data, employment figures,
and earnings reports. These organizations want to use the petabytes
of data they possess to gain insights that help identify new
sources of revenue, attract and retain customers, and reduce cost
or risk. However, before data can be analyzed, FSI companies
typically spend months finding the right data and getting it
prepared for analysis. Discovering and preparing data is
time-consuming because FSI organizations have data in silos
distributed across departments that specialize in particular assets
or geographies and generate specialized data (e.g. equities,
options, bonds, European mutual funds, Asian currencies, etc.).
Furthermore, data access is tightly controlled by regulation and
policy, meaning analysts must justify to compliance officers how
their access will conform to data use policies before they can
access the data. Once they are granted access to the data, analysts
must prepare it for analysis by iteratively performing data
transformations to discover new insights within the data. For
example, capital markets traders often use technical indicators
like Bollinger Bands, Exponential Moving Averages, and Average True
Range to identify undiscovered trends and patterns. Many of the
data analytics tools available to analysts today were built to run
on a single computer and were not designed to take advantage of the
cloud’s scale and the ability to compute heavy analysis on-demand.
As a result, analysts either have to use small representative
datasets that limit predictive ability, or the data has to be
manually broken up into many subsets, transformed piecemeal, and
manually recombined. Neither approach is ideal or effective.
Amazon FinSpace solves the challenges FSI organizations face by
vastly simplifying the steps needed to find, prepare, and analyze
data, reducing the time involved from months to minutes. Customers
begin by ingesting data into Amazon FinSpace from internal data
silos or third-party data feeds via the service’s Application
Programming Interface (API) or a drag-and-drop interface in the web
application. To find data, customers simply browse a visual catalog
and search for familiar business terms like options trades for the
last three years or U.S. automotive bonds from within the web
application. Amazon FinSpace includes built-in classification
schemas for common FSI data sources (e.g. trades, corporate
actions, and economic data) that customers can customize to their
needs, so the data can be organized in a way that is easy to find
and share. Amazon FinSpace records the daily updates and
corrections received for datasets and processes them to create
point-in-time views to validate modeling assumptions and to show
what data was used to inform past decisions for historical
analysis. Customers can use built-in Jupyter Notebooks to access
data stored in Amazon FinSpace and can then choose from over 100
built-in functions to prepare their data for analysis (e.g.
Bollinger Bands, Exponential Moving Averages, and Average True
Range)—or they can build and use their own functions to prepare
data for analysis. Amazon FinSpace provides managed Spark clusters
that can be scaled up or down on demand so organizations can
benefit from the elasticity, scale, and cost savings provided by
cloud computing. Customers define their data access policies within
Amazon FinSpace, and the policies are automatically enforced across
data search, visualization, and analysis. Amazon FinSpace records
data access, tracks data usage, and generates compliance and
activity reports indicating who accessed data at what point in
time.
“FSI organizations generate and purchase massive amounts of
data, but using this data is very difficult because of the time and
effort it takes to collect and prepare data for analysis,” said
Saman Michael Far, VP of Financial Services Technology, AWS.
“Amazon FinSpace is a game changer for FSI organizations. Amazon
FinSpace radically reduces the time it takes for FSI customers to
do analytics across petabytes of data, making it significantly
easier for them to identify new sources of revenue, attract
customers, and reduce cost and risk.”
Amazon FinSpace is generally available today in US East (N.
Virginia), US East (Ohio), US West (Oregon), Canada (Central), and
Europe (Ireland), with availability in additional regions coming
soon.
Legal & General Reinsurance (L&G Re) is the global
reinsurance hub of the Legal & General Group with a specialty
in the reinsurance of annuities, particularly pension risk transfer
business. “At Legal & General, our mission is to guarantee the
long-term financial security of our clients’ customers around the
world,” said Thomas Olunloyo, CEO of L&G Re. “Our reinsurance
specialists work with a broad range of data to measure asset
performance, mortality, and longevity risk. Today, this data is
distributed and stored across many teams, systems, and structures.
We are excited about the release of Amazon FinSpace and its ability
to help us unlock the full power of our data to enable our team and
efficiently give new insights to our clients. Amazon FinSpace will
transform how we use data by giving our analysts the ability to
instantly and easily access all the company’s data to carry out
analysis faster and immediately share the results across the
business, while ensuring our data governance and access control
policies are met in full.”
Deloitte is helping transform organizations around the globe.
The organization continuously evolves how it works and how it looks
at marketplace challenges so it can continue to deliver measurable,
sustainable results for its clients and communities. “In working
with financial services industry clients, we have found that
cloud-based analytics and AI/ML allow us to answer questions that
we couldn’t answer several years ago and drive value in new ways.
Data, analytics, and AI/ML will continue to be key and become even
more important to financial institutions’ decision making and
business outcomes over the next decade,” said Jojy Mathew,
Principal, Deloitte Consulting LLP, and Deloitte’s Financial
Services Data and Analytics Leader globally. “When companies are
building algorithmic, stochastic and predictive models, large data
sets are key. Amazon FinSpace will allow users to process petabytes
of data at the scale demanded. In addition, FinSpace enables
‘analytics sandboxes’ to be created quickly and brings advanced
analytics capabilities to citizen data scientists.”
About Amazon Web Services
For over 15 years, Amazon Web Services has been the world’s most
comprehensive and broadly adopted cloud platform. AWS has been
continually expanding its services to support virtually any cloud
workload, and it now has more than 200 fully featured services for
compute, storage, databases, networking, analytics, machine
learning and artificial intelligence (AI), Internet of Things
(IoT), mobile, security, hybrid, virtual and augmented reality (VR
and AR), media, and application development, deployment, and
management from 80 Availability Zones (AZs) within 25 geographic
regions, with announced plans for 15 more Availability Zones and
five more AWS Regions in Australia, India, Indonesia, Spain, and
Switzerland. Millions of customers—including the fastest-growing
startups, largest enterprises, and leading government
agencies—trust AWS to power their infrastructure, become more
agile, and lower costs. To learn more about AWS, visit
aws.amazon.com.
About Amazon
Amazon is guided by four principles: customer obsession rather
than competitor focus, passion for invention, commitment to
operational excellence, and long-term thinking. Amazon strives to
be Earth’s Most Customer-Centric Company, Earth’s Best Employer,
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