Singapore – With AI increasingly testing system limits, around 84% of business leaders fear devastating data loss, and 41% report that AI is now essential to their daily functions.
This is according to the latest survey from Hitachi Vantara, the data storage, infrastructure, and hybrid cloud management subsidiary of Hitachi.
In the report, the company indicated that 36% recognise the importance of data quality for AI success, yet financial leaders prioritise security, creating gaps in performance and ROI. With this, about 84% say data loss due to an attack or error would be catastrophic.
Interestingly, findings revealed that ignoring data quality comes at a cost for BFSI institutions. In fact for BFSI companies, data is accessible only 25% of the time when and where it’s needed, and AI models in use are accurate just 21% of the time.
Approximately 36% are also worried about the risk of a data breach from internal AI, and 38% are concerned about the inability to recover data from ransomware.
Despite ransomware dominating concerns, 36% of IT leaders further say one of their top fears is AI making a mistake that leads to a breach, and 32% are troubled by the potential for AI-driven attacks to compromise data.
BFSI companies are also rapidly integrating AI, despite facing ongoing accuracy issues. However, 71% of respondents admit to testing AI systems in live settings, with only 4% leveraging safer, sandboxed environments.
In addition, the report found that while data quality is widely seen as essential to effective AI, urgent concerns such as cybersecurity continue to overshadow it, compromising overall ROI.
Joe Ong, vice president and general manager for ASEAN at Hitachi Vantara, said, “Financial institutions worldwide are accelerating AI adoption, but many are realising their data infrastructure isn’t ready to support it. 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 organisations must focus on strengthening their data foundations to ensure AI delivers real, sustainable impact,” added Ong.
Meanwhile, the survey outlined essential steps for building a more resilient, AI-ready infrastructure, offering a roadmap for BFSI organisations to future-proof their operations. These include responsible experimentation, sustainability at every level, simplifying and unifying systems, as well as ensuring data resilience and leveraging AI for defence.
Mark Katz, CTO of Financial Services at Hitachi Vantara, also commented, “The business model in financial services is inherently tied to trust. Reputational harm is a significant risk, and so in our industry, the interaction between security and accuracy is a critical and complex challenge.”
“For instance, if a chatbot inadvertently discloses sensitive information that was included in the training data, that will have serious repercussions. Additionally, the cost of a wrong answer or a hallucination poses a significant risk; if someone were to act on bad data, it raises all sorts of questions about liability,” explained Katz.
