Dive Brief:
- Financial services companies grapple with data distribution hurdles as they move forward with AI initiatives, according to data center services provider Digital Realty. The company surveyed 2,254 global IT decision-makers across 11 industries, including 362 in the financial services industry.
- Two-thirds of financial services industry respondents said their organization was executing an AI strategy, but more than half found funding data infrastructure upgrades to be a challenge. Bringing data in closer proximity to business and AI operations was a priority for 7 in 10 respondents.
- “If you don’t have the right data where you need it, then your AI strategy is broken before it starts,” said Dan Eline, VP of platform solutions at Digital Realty, in the report. “Data must be in the right place where AI can ingest it and create more data in a forever-perpetuating cycle.”
Dive Insight:
The financial industry sits atop mountains of data that can fuel predictive modeling, improve risk assessments and drive customer experience innovations. But leveraging those assets to feed generative AI tools remains a challenge.
Citi invested billions of dollars in IT systems modernization efforts following a 2020 Federal Reserve Board enforcement action that found deficiencies in the bank’s data and compliance risk management controls. The upgrades reversed historic underinvestment in Citi’s infrastructure, CEO Jane Fraser said, and included migrating workloads to private cloud infrastructure.
JPMorgan Chase Chairman and CEO Jamie Dimon made data and infrastructure modernization at top priority as the bank rolled out a suite of AI-powered tools internally this year. The company led the banking sector in AI adoption, according to the Evident AI Index published in October.
Throughout the sector, organizations are mobilizing to bring data and AI closer together. Nearly two-thirds of financial services companies have IT infrastructure distributed across up to 10 global locations, Digital Realty found. More than three-quarters of respondents said their organization is planning to add up to five locations in the next two years.
Despite adoption of distributed ecosystems, 3 in 5 respondents said they lack IT infrastructure in locations necessary to achieve their AI goals.
The problem can get worse as data accumulates, attracting applications, services and more data, according to Digital Realty. This virtual cycle can nonetheless lead to silos that impede enterprisewide AI adoption.
“As data collects in one location, it becomes more difficult to move that data away from its current location,” the company said in the report.
“The challenge for banks isn’t a lack of customer data — they have plenty of it. The challenge is that banks’ data is typically siloed across lines of business,” according to Publicis Sapient.
The technology consulting firm surveyed 1,000 senior banking executives earlier this year. Nearly one-third of respondents cited budget constraints as a barrier to data modernization.
Digital Realty identified a similar problem. More than half — 56% — of IT leaders in financial services firms surveyed said their organization lacked adequate investments in data systems and analytic tools.
