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Wells Fargo Launches Next Generation Card Payments with MongoDB

Learn the secrets of Wells Fargo’s mainframe modernization and how to make it work with MongoDB.

Image of a woman making a payment using a smartphone.

INDUSTRY

Financial Services

PRODUCT

Enterprise Advanced

USE CASE

Mainframe modernization

CUSTOMER SINCE

2015

The financial services market is going through a transformation, and customers expect better experiences, greater personalization, and seamless interactions at every touchpoint. Take card payments for example. Once reserved for large, infrequent purchases, today’s consumers use cards for everything from coffee and subway rides to subscription services and thousand-dollar payments. And they don’t expect the transaction to take more than a couple of seconds.

“The amount of data we handle is getting exponentially bigger. We need to be good custodians of that data and use it well to give consumers a seamless digital experience,” says Nadeem Kayani, EVP/CIO of Consumer Lending at multinational giant, Wells Fargo.

When the company decided to launch its Cards 2.0 initiative to make the payment platform more sustainable and scalable, it needed to modernize its mainframe first. While mainframes hold critical system of record (SOR) data, they often bring technical debt, dependencies, and are increasingly costly to manage — not least because there’s a shortage of people with the right skills to maintain them.

Introducing the operational data store

The vision for Cards 2.0 was a smooth, multichannel experience for consumers. Wells Fargo wanted to reduce dependency on third-party processing as much as possible, streamline integrations, and adopt reusable APIs so it could quickly roll out changes across channels.

“We built an operational data store (ODS) on MongoDB to resolve all of these issues,” explains Ram Vemana, Head of Credit Card & Merchant Data at Wells Fargo, during his breakout session at MongoDB .local NYC in June. “It has a sub-second service that can handle more than seven million transactions. That’s more than enough for today and provides the scalability and resiliency we need for the future.”

Thanks to senior management buy-in, the ODS launched in just seven months and now serves 40% of traffic from external vendors. Vemana comments that developers used to working with APIs find the platform intuitive and easy to use. MongoDB also provided training, which enabled teams to learn how to build architectural changes, best practices around data governance, and how to think about data products.

Swapping monolithic architecture for flexible microservices

Today, when data from an external vendor enters the mainframe, it’s pulled into MongoDB and served to other channels. The team created a façade layer between its database and APIs to enable headless microservices, which support different product lines within the business and provide more flexibility than its previous monolithic architecture.

“MongoDB handles more than 20 terabytes of data per day and supports over 80 microservices. We’re currently using the ODS to run our rewards and loyalty programs, for example, which ran on SQL Server previously,” recalls Vemana.

As part of the transformation, developers also built curated data products to make data available and actionable for authenticated processes, which speeds up rolling out new features across channels while keeping data secure.

With MongoDB, Wells Fargo jumpstarted its legacy mainframe modernization and is well placed to continue innovating to give consumers next-generation financial services.

“What we’re doing is both nerve-wracking and exciting. Data is a goldmine. The personalized products we can offer are built into the data we have on every transaction and the knowledge we have on our customers,” says Kayani. “It’s all about how we can utilize that to best serve our customers.”

Learn how MongoDB Atlas is optimized for the financial services industry.

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