5 reasons why financial services firms should choose Google Cloud Platform

By Chris Lehman | Head of Engineering | Google Cloud

Historically, financial services organizations were hesitant to migrate to the cloud, primarily due to security and compliance concerns. However, shifting consumer expectations and the COVID-19 pandemic forced financial services companies to fundamentally rethink their business models. Now, many financial institutions that were previously cloud-shy have become cloud champions as they realize the opportunities that cloud computing offers in terms of scalability, cost savings, security and compliance, and innovation through access to cutting-edge technologies like big data analytics and machine learning.

Financial services organizations around the world are choosing Google Cloud Platform to transform their business operations, ensure operational resilience, and thrive in a digital, post-pandemic economy. Here are just a few reasons why.

1. Data warehouse modernization and smart analytics at scale

Financial services organizations handle and store a tremendous amount of data, including structured customer data and other information gathered firsthand, as well as unstructured data mined from the internet and other sources. More data means better insights, but a lot of this data goes unused due to the complexity of managing traditional data warehouses. Organizations spend about 85% of their time on systems engineering tasks and only 15% on analyzing and deriving insights from their data.1 Additionally, these solutions don’t scale well.

BigQuery, Google’s serverless, scalable data warehousing solution, automates systems engineering tasks and offers a simplified user interface, freeing organizations from time-consuming systems engineering tasks and giving them more time to work with their data. Since BigQuery is completely software-based, it requires no upfront hardware provisioning or management, and it automatically scales to maximize query performance. IT administrators don’t need to provision compute resources, and data analysts can run queries without concern for underlying infrastructure.

BigQuery leverages a distributed computing model, so complex queries are processed using multiple servers in parallel. With multiple data centers, each with hundreds of thousands of cores, dozens of petabytes in storage capacity, and terabytes in networking bandwidth at its disposal, BigQuery can analyze petabyte-sized datasets at lightning-fast speeds.

Organizations that migrate to BigQuery can reduce their total cost of ownership (TCO) up to 41% to 52%.2

2. Support for hybrid and multi-cloud environments

According to Flexera’s 2021 State of the Cloud Report, 92% of enterprises have a multi-cloud strategy, while 80% have a hybrid cloud strategy.3 Financial services firms often prefer hybrid environments because compliance mandates require certain workloads to be hosted on-prem.

Anthos, a 100% software-based approach for hybrid and multi-cloud environments, enables companies to migrate and modernize in place, at their own pace, while enjoying a consistent development and operations experience across both cloud and on-premises environments. In addition to supporting on-prem workloads, Anthos also integrates with AWS, with Azure coming soon.

The perfect solution for financial services enterprises with complex compliance requirements and highly distributed IT environments, Anthos puts the enterprise in control, enabling them to run the right workloads in the right cloud at the right time and manage their entire data environment through one centralized dashboard.

Additionally, Google Cloud customers can opt for a range of hybrid connectivity options between their on-prem datacenter and cloud, suitable for any location, budget, or bandwidth requirements, with Dedicated Interconnect and Partner Interconnect.

3. Unmatched cybersecurity

Google’s global-scale technical infrastructure is designed to provideo, from Google’s data centers to its operational processes. For example, although Google is one of the world’s largest hardware manufacturers,4 it does not sell its servers; they are built solely for internal use, ensuring that Google retains complete control over the build process.

In addition to encrypting all data in transit between its platforms, customers, and data centers, GCP encrypts all data at rest in GCP services by default. Additionally, GCP enables developers to encrypt cloud applications at the application layer, for the highest levels of data security.

Google Cloud never accesses customer data unless doing so is absolutely necessary to fulfill its contractual obligations, such as when resolving a technical or security issue. GCP’s internal technical controls require any employees who access customer content to provide a valid business justification, and Google performs regular audits to ensure that these access controls are being adhered to.

4. Powerful but user-friendly AI & machine learning tools

Google Cloud offers a wide variety of artificial intelligence and machine learning tools designed for developers, analysts, and other users who don’t have a background in data science. For example, BigQuery ML enables data analysts to build and deploy advanced, custom ML models using only basic SQL. These models can be further refined according to location or whatever other variable the analyst wants by leveraging Google’s extensive library of public datasets, which include weather information, COVID-19 tracking, and more.

Another example is LendingDoc AI, a specialized solution built for the mortgage industry that is part of Google Cloud’s Document AI tools, which parse and extract insights from business documents. LendingDoc AI automates routine mortgage document reviews, reducing processing time and streamlining data capture while ensuring compliance with regulatory mandates. Borrowers get a faster and smoother loan application experience, while lenders get to spend less time on administrative tasks and more on work that drives the business and adds value.

5. Mission critical customer support services

In the financial services industry, one minute of downtime can mean millions of dollars in lost revenue. Even a single incident can have severe repercussions. For these ultra-demanding environments, Google Cloud offers Mission Critical Services (MCS), a unique consultative service available to GCP Premium Support customers.

MCS customers get more than premium support. Google partners with them throughout their cloud journey, leveraging methodologies developed and refined by Google’s Site Reliability Engineering (SRE) teams over the past two decades — and used by Google Cloud to support its own infrastructure.

Google’s highest tier of engineers have comprehensive familiarity with MCS customers’ workloads, enabling them to monitor, prevent, and mitigate system incidents 24/7. In contrast to Google’s Premium Support, which guarantees a response within 15 minutes, MCS customers get a five-minute response time, within which Google will set up a “war room” staffed with engineers who can leverage their knowledge of the customer’s data environment to quickly diagnose and solve the problem.

1 https://cloud.google.com/blog/products/data-analytics/5-reasons-your-legacy-data-warehouse-wont-cut-it
2 https://services.google.com/fh/files/events/esg_economic_validation_migrating_to_google_bigquery.pdf
3 https://info.flexera.com/CM-REPORT-State-of-the-Cloud
4 https://www.wired.com/2012/07/google-server-manufacturing/

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