Banks and other financial data services companies are fast becoming competitive arenas for modern data management in the cloud.
Wells Fargo is the latest big bank and financial firm to jump into the action, choosing Microsoft as its primary public cloud provider and Google Cloud for additional cloud services.
Meanwhile, JP Morgan Chase is already working with AWS on an ambitious and far-reaching modernization strategy. And Bank of America has teamed with IBM on the IBM Cloud for Financial Services, which has a growing list of customers and partners.
These industry-specific cloud platforms provide a glimpse into the future of data management and application development in financial services. And they may serve as a harbinger of where things are heading in other industries.
Cloud and database providers are responding with tools and services that are tailored to the idiosyncrasies of different industries. Case in point: Snowflake just announced its Financial Services Data Cloud, for banking, fintech, insurance, and investment-management firms.
Microsoft and others offer their own financial industry clouds and services. Let’s take a closer look at some of the latest developments.
The Wells Fargo of Tomorrow
Wells Fargo, which provides financial services to a third of U.S. households, announced on Sept. 15 that they will use Microsoft’s Azure data and analytics services to deliver new and improved customer experiences and support collaboration among employees. In addition, Google Cloud will provide AI and other data solutions in support of customer personalization.
Saul Van Beurden, Wells Fargo’s head of technology, announced the partnerships under the umbrella of a new digital infrastructure strategy. “The Wells Fargo of tomorrow will be digital-first and offer ease-of-use products and services,” said Van Beurden. “And all of that starts with driving speed, scalability, and enhanced user experience through the next-generation digital infrastructure strategy.”
Importantly, Wells Fargo emphasized that its cloud environment will provide safeguards to protect data and financial assets, as well as privacy and data confidentiality.
The firm is taking an interesting hybrid, multi-cloud approach. In addition to Microsoft Azure and Google Cloud, it plans to transition to third-party data centers, which will be used for private cloud and hosting services. But the data centers are an interim step. Wells Fargo said its “longer-term aspirations are to rely predominantly on public cloud.”
Snowflake’s Turnkey Data Cloud
Snowflake’s new Financial Services Data Cloud combines data sharing and collaboration, encryption and other security measures, governance, and compliance with financial industry standards and regulations, all geared to the financial sector.
Snowflake already has a jumpstart in the industry, as more than half of financial services firms in the Fortune 500 are using its services. Its new industry cloud is likely to draw in more such customers.
As it does with its general-purpose data cloud, Snowflake makes it easy for financial customers to tap into third-party offerings. For example, they can access data sets from partners such as Acxiom and S&P Global, as well as end-to-end data services from companies such as Amazon, BlackRock, Cognizant, and Dataiku.
Here’s an example of how those integrations work: Cognizant’s Quick Start data exchange lets insurers combine policy and claims data with third-party datasets from the Snowflake marketplace for risk evaluation and underwriting.
Snowflake said it has successfully completed an assessment, by KPMG, of 14 cloud controls for protecting sensitive data under the Cloud Data Management Capabilities framework. The organization behind the framework is the EDM Council, a non-profit trade association. Also, Snowflake’s Financial Services Data Cloud is compliant with Sarbanes-Oxley requirements.
You can see the potential for these financial industry clouds: industry-specific features and capabilities, ease of use, fast implementation, standards, policy compliance, and security measures that customers want and need.
Modernization at JP Morgan Chase
To understand where all this is heading, look no further than JP Morgan Chase, which is building out its IT infrastructure and applications environment using dozens of cloud services from AWS.
This case study was presented earlier this year by JP Morgan Chase CIO Lori Beer at AWS re:Invent, but AWS recently shared the replay, and in my view, it’s worth every minute.
Two defining characteristics are important for context. First, JP Morgan Chase operates at a tremendous scale—with 35,000 developers, 6,000 applications, and 450 petabytes of data across hybrid clouds. And second, JP Morgan Chase has been in business for more than 200 years and even funded the development of Thomas Edison’s lightbulb.
So, when Beer describes JP Morgan Chase’s strategy as “a true modernization effort,” it’s not hyperbole.
Here are a few of the AWS services that JP Morgan Chase is using:
- Amazon EMR, a big data platform, for trading analytics
- AWS Lambda and Elastic Kubernetes Service for risk calculations
- Amazon’s SageMaker ML services for the bank’s companywide AI platform, dubbed Omni AI
One major undertaking is “refactoring applications,” which is to say migrating existing apps to AWS as part of the modernization effort. Some of the AWS cloud databases being used are Aurora, RDS for Oracle, RDS for PostgreSQL, and DynamoDB.
The bank’s AI projects represent some of the most forward-looking development activities. They include using natural language processing for more personalized customer interactions and ML models for risk assessment.
JP Morgan Chase is also building a cloud data warehouse on Amazon Redshift. That, along with AI and elastic computing, will help the bank “infuse analytics in everything we do,” said Beer.
Conclusion: Other Industries May Be Next
The bottom line is that JP Morgan Chase has become more agile, secure, and efficient as it modernizes, according to CIO Beer.
Those are impressive accomplishments. Many CXOs, regardless of industry, would love to be able to say the same. Which is why I have no doubt we will see more data modernization projects move to the cloud across industries.
