JPMorgan Chase is on track to invest more than $15 billion in technology in 2023, with the goal of driving $3 billion in cost savings and efficiencies across infrastructure and data initiatives, as the bank continues to execute on the firm-wide strategy it laid out last year.
Lori Beer, global chief information officer, said at the
JPMorgan Chase expects that its investments in data analytics and AI to increase customer personalization and client insights will deliver $1.5 billion in business impact by the end of 2023. The bank's infrastructure modernization, which includes optimizing its data centers and migrating applications to public and private cloud, is slated to bring in an additional $1.5 billion in cost savings and efficiencies over the next three years.
The industry giant's interests in AI and cloud computing aren't unique across the sector. Keri Smith, who leads Accenture's applied intelligence banking practice in North America, said as AI innovations become table stakes, banks will have to search for ways to differentiate their services.
Last year, the bank outlined its four technology investment priorities: developing strong products and customer experiences, strengthening infrastructure, increasing investments in and use of data analytics and AI, and maintaining cybersecurity. In 2022, the bank spent about $14.3 billion on technology.
Neil Hartman, a senior partner at consulting firm West Monroe, said major banks have been updating their foundations for several years, and now can work on emerging technology projects.
"We're seeing a shift from the biggest banks into modernizing the bank, and leveraging new technologies to set the bank up for the next business cycle," Hartman said. "There's benefits for the banks today around efficiency and cost savings."
One of the pillars to JP Morgan's strategy is investing in data, AI and machine learning.
Last year, Beer said the company hoped to create $1 billion in value through AI by the end of 2023, but increased its goal due to recent results. In the last year, AI has driven $220 million in retail at the bank through personalized offerings, like credit card upgrades. The technology has also yielded $100 million in commercial business in 2022 by offering bankers suggested products and growth plans for clients. The bank has more than 300 AI use cases in production for risk, marketing, customer experience and fraud. JP Morgan measures value through cost savings and efficiencies, tracking the costs and return associated with investments.
Hartman said the biggest difference between a major institution like JP Morgan and a smaller regional bank is the size and complexity of its lines of business and client portfolio, which raise its imperative to innovate.
"The biggest thing for the largest banks, especially right now, that we're seeing is automation and trying to drive better efficiency throughout their entire ecosystem," Hartman said. "Automating as much as possible, leveraging AI tools, leveraging robotics of workflows, and APIs, all those types of technologies to really drive more efficiency within their four walls."
Hartman said it's especially important for banks to find and automate inefficiencies in their operating models during uncertain economic environments, when reducing costs is a bigger focus.
JPMorgan Chase is currently
Samir Datt, who leads Protiviti's technology strategy and operations practice, said implementing proper governance for trusting AI and monitoring use cases is as important as adopting the technology.
Beer said the bank had a team of data scientists, ethicists, risk professionals and others to evaluate generative AI use cases. She added in her presentation that the bank's policy is, "successful AI is responsible AI."
JPMorgan Chase has hired more than 900 data scientists, 600 machine learning engineers and 200 AI researchers to execute its technology initiatives. Datt said that as banks increase their AI and automation capabilities, it's important to upskill employees to appropriately use and assess that technology. The company has a total technology team of more than 57,000 people.
Hartman said big banks are focused on bringing in those technical skill sets to compete with fintechs and Big Tech companies.
"We couldn't discuss AI without mentioning GPT and large language models," Beer said. "We recognize the power and opportunity of these tools and are committed to exploring all the ways they can deliver value for the firm. We are actively configuring our environment and capabilities to enable them. In fact, we have a number of use cases leveraging GPT-4 and other open source models currently under testing and evaluation."
Other major financial institutions are
Smith said that as the pace of development in generative AI and large language models rapidly picks up, financial institutions have prioritized hitting AI milestones faster. She said companies are adjusting their innovation investment appetites and timelines, looking for ways to automate processes that can lead to faster bottom-line impact.
"When you think about some of the tech investments that are needed to be made, some of these may be giant investments," Smith said. "But what we're finding is people are starting to look at, 'How do I think about this in bite sized chunks, and do this in sprints so that I'm able to get results faster, but also not necessarily have a sizable price tag?'"
JPMorgan Chase's infrastructure modernization, which includes increasing cloud migration and optimizing data centers, is foundational to developing other innovative technologies like AI, Beer said. The company has delivered $500 million in productivity and cost efficiencies from infrastructure investments, and is aiming to hit $1.5 billion in the next three years.
"These gains are tied to investments and actions we've taken in the way we deliver software and our modernization efforts," Beer said. "Specifically, we have driven $300 million in efficiency through modern engineering practices and labor productivity, and we have developed a framework that enables us to identify further opportunities in the future. Our infrastructure modernization efforts have yielded an additional $200 million in productivity, driven by improved utilization and vendor rationalization."
Beer said the modernization investments enable the company to migrate large amounts of data to the public cloud, and increase the data platforms' capabilities. Cloud investments will make up 38% of JPMorgan Chase's total technology infrastructure spend in 2023.
"Our cloud journey will ultimately create a faster, more efficient environment for our business," Beer said. "By working toward our target state of multi-vendor public cloud and modern strategic data centers, we have been able to keep our infrastructure expenses relatively flat while our compute and storage volumes have increased 50% since 2019, and tripled since 2015."
JPMorgan Chase has moved more than half of its in-scope applications to more efficient data centers and decommissioned 300 legacy applications in the last year. In the fourth quarter, the bank completed its migration of Chase.com to the public cloud through AWS.
Datt said updating or migrating off of outdated infrastructure can be tedious and risky, but necessary to keep up with pushing out products and services to meet customer demand.
"[Banks] have got to have the underlying infrastructure, the process discipline, things like true agile enablement and strong devops practices, to move through the development lifecycle, and push that kind of functionality out to production in rapid, controlled fashion while managing risk," Datt said.
The bank is also increasing its use of APIs that allow consumers to share information from their bank accounts with apps and companies, which Hartman said is an expanding trend among large financial institutions.
