FSI Data Systems Strained by AI Boom

Over eight in 10 (84%) leaders of FSI organizations say they fear catastrophic data loss as AI strains their data infrastructure. This comes at a time when businesses are rushing to adopt AI, cognizant of its impact on daily operations and its role in gaining a competitive edge.

This was one finding of the State of BFSI Data Infrastructure in 2024 by Hitachi Vantara, which sought insights from 231 BFSI specialists, C-level executives, and IT decision-makers across 15 countries.

The data delimma

According to the report, the real barrier to AI success isn't the technology itself, but the ability to manage data securely, accurately, and at scale. In a nutshell, many are coming to the realization that their data infrastructure isn’t ready to support AI adoption.

AI’s rapid rise is pressuring traditional data systems, forcing financial institutions to prioritize between security, quality, and sustainability. Indeed, nearly half (48%) of respondents cite data security as their top concern for AI implementation, reflecting the critical need to guard against internal and external threats.

More sobering is the finding that in BFSI companies, data is available when and where it is needed only a quarter of the time (25%), and BFSI AI models are accurate only 21% of the time. In addition to the threat of ransomware, 36% cite AI errors causing data breaches as a top-three risk, and 32% fear AI-enabled attacks could do the same.

A matter of trust

Mark Katz, CTO of Financial Services at Hitachi Vantara, noted that the business model is fundamentally built on trust in the financial services industry. This means reputational harm represents a significant risk, which makes the relationship between security and accuracy both critical and complex.

Katz observed that the consequences could be severe should a chatbot inadvertently disclose sensitive information embedded in its training data. The risk of a chatbot providing incorrect information could also pose a serious threat. And if someone were to act on inaccurate data, it would raise complex questions about accountability and liability, he notes.

“This global research reflects what we're also hearing in Southeast Asia – that the real barrier to AI success isn't the technology itself, but the ability to manage data securely, accurately, and at scale. Financial organizations must focus on strengthening their data foundations to ensure AI delivers real, sustainable impact,” said Joe Ong, Vice President and General Manager for ASEAN at Hitachi Vantara.

The full report can be accessed here.

Image credit: iStock/Anthony Boulton