[Demo] Design Event-Driven Microservices for Cloud → Register Now
Businesses that are best able to leverage data have a significant competitive advantage. This is especially true in financial services, an industry in which leading organizations are in constant competition to develop the most responsive, personalized customer experiences.
Often, however, legacy infrastructure, data silos, and batch systems introduce significant technical hurdles. Innovators like Capital One have made it a priority to overcome these complex challenges and implement centralized data governance so their teams can unlock powerful data streaming use cases.
We sat down with Nisha Paliwal, Managing Vice President of Enterprise Data Technology at Capital One, to learn how this top ten U.S. bank has solved complex data challenges and advanced business needs with data streaming.
Register for the upcoming live session to get the full story.
As one of the leading digital banks in the U.S., Capital One has made technology central to its business strategy. And without the more than 10-year data transformation initiative that the company has undergone with the help of teams like Nisha’s, the company wouldn’t be able to rapidly innovate with data-intensive technologies like artificial intelligence and machine learning (AI/ML) in the way it does today.
When Nisha joined the organization, she already had extensive experience in leading data transformation initiatives. This expertise helped her team focus on big-impact projects, particularly a cloud migration effort that would make it easier for the organization to manage, move, govern, and leverage data at scale.
Nisha said, “We have 100 million customers to serve—that means massive volumes of data are flowing through our organization every day. Despite the challenges this brings, Capital One was able to become the first U.S. bank to fully migrate to the cloud in 2020. A big driver of our cloud migration was our desire to take advantage of the unlimited, instant scalability of cloud-native technologies.”
From card swipes to transfers and deposits, there is a vast number of daily transactions. Adopting cloud-native data solutions like Confluent Cloud was an early step in a multi-year journey toward not only being able to handle this volume of data movement in the cloud but also being able to implement real-time personalization for customers.
“What’s driving all the innovation at Capital One is real-time data at scale, unlocked by first building a cloud-native foundation. Since 2012, the company has been continuously pursuing a cloud-first approach and standardizing on open source technology. Four years into that journey, we partnered with Confluent to adopt Apache Kafka® use cases—from this point forward our progress with real-time use cases accelerated significantly, and we’re still reaping the benefits of that decision today.”
Nearly two decades ago, leaders at Capital One recognized that the industry was going to be won by companies capable of developing innovative technology that would deliver transformative experiences. The end goal was always clear: make customers’ lives easier.
Actually implementing this vision has taken the organization a decade of building the right AI/ML models, streaming data pipelines, and internal processes. Today, Capital One’s technology workforce is comprised of 14,000 people well-trained on how to operate at speed while maintaining the rigorous standards that the financial services industry demands.
Solving data integration challenges in financial services requires a comprehensive data management strategy. Using Confluent Cloud has allowed the company to integrate legacy technology with cloud-native systems.
Nisha said, “Data is everywhere. For Capital One, being able to manage and use all that data—wherever it lives—has been critical in being prepared to adopt and integrate emerging tech.”
She continued, “We had to put a lot of the rigor into data management and continuous data governance so data is ready to use as soon as it’s ingested. Having confidence in where our data is coming from and how it will be used is what unlocks value across the whole data ecosystem.”
At Capital One, constantly improving the customer experience is a key priority. Data streaming has enabled this mission by increasing the speed and scale at which the company can operate. The data governance capabilities in Confluent’s enterprise-ready data streaming platform have also helped Nisha’s team also break down costly data silos.
Nisha said, “The ability to move and scale fast in the cloud is essential for succeeding in the digital age. With tools like Confluent, our ability to stream data, productize it, and manage it at exactly the level we want has made it easier to leverage AI more and more for customer personalization.”
In addition to personalization, Capital One has also needed to be able to use its data to power real-time fraud detection, which involves billions of transactions.
These billions of daily transactions must reach the right destination to ensure that continuous financial monitoring ensures their assets are protected, giving them confidence when banking with Capital One. Nisha explained, “Catching fraud and alerting customers as quickly as possible is essential. The faster and fresher that data can reach the AI models powering fraud detection capabilities, the better the experience on the customer’s end.”
As Nisha noted, enterprises who treat data as a product allow their data owners across the company to govern their data effectively and share it across the organization as reusable data streams.
Regardless of industry sector or desired use cases, data streaming practitioners and business leaders can glean valuable insights from Nisha and her team.
Sign up to attend the live talk with Capital One to learn more about how being able to stream, govern, and process data streams unlocks value for the bank and its customers.
The Markets in Financial Instruments Directive II (MiFID II) came into effect in January 2018, aiming to improve the competitiveness and transparency of European financial markets. As part of this, financial institutions are obligated to report details of trades and transactions (both equity and...
While cloud computing adoption continues to accelerate due to its tremendous value, it has also become clear that edge computing is better suited for a variety of use cases. Organizations are realizing the benefits of processing data closer to its source, leading to reduced latency, security and...