New Hitachi Vantara Survey Finds Financial Services Leaders Struggle with Data Governance and Infrastructure Demands
Hitachi Vantara report reveals 84% of leaders fear catastrophic data loss as AI strains infrastructure and 41% say AI is already a critical part of their function.
The rapid advancement of artificial intelligence (AI) is placing unprecedented demands on traditional data infrastructures forcing businesses in the Banking, Financial Services and Insurance (BFSI) sector to prioritize between security, quality and sustainability, according to a new survey from Hitachi Vantara, the data storage, infrastructure, and hybrid cloud management subsidiary of Hitachi, Ltd. (TSE: 6501). Reflecting input from 231 global IT and business leaders, the State of Data Infrastructure 2024 Report found that while 36% recognize the importance of data quality for AI success, financial leaders’ focus remains on data security – leaving gaps in AI performance and long-term ROI.
“Financial institutions worldwide are accelerating AI adoption, but many are realizing their data infrastructure isn’t ready to support it,” said Joe Ong, Vice President and General Manager for ASEAN at Hitachi Vantara. “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.”
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. This is understandable considering that 84% of respondents admit losing data to an attack or mistake would be catastrophic. However, the study results showed that ignoring data quality comes at a cost for BFSI institutions, including:
- In BFSI companies, data is only available when and where it is needed a quarter of the time (25%), and BFSI AI models are accurate only 21% of the time.
- 36% are concerned about the risk of a data breach from internal AI, and 38% are concerned about inability to recover data from ransomware.
- Although ransomware attacks are top-of-mind for BFSI IT leaders, 36% say a data breach caused by AI making a mistake is a top three concern for them, and 32% are concerned an AI-enabled attack could cause a data breach.
“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,” said Mark Katz, CTO of Financial Services, Hitachi Vantara.
“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.”
Despite accuracy challenges, AI adoption within BFSI is accelerating. However, many are deploying AI without adequate preparation, with 71% of respondents admitting to testing and iterating on live implementations, while only 4% are using controlled sandbox environments. The research confirms that financial services leaders are convinced that data quality is the most important consideration for successfully implementing AI, but concerns like security are too urgent to ignore, and ROI is suffering.
The survey outlines the key considerations to building a more resilient, AI-ready infrastructure to help BFSI organizations prepare for the future, including:
- Responsible Experimentation: Two out of five BFSI leaders (42%) said they were building the necessary skills to implement AI through experimentation. Responsible testing in secure sandboxes can mitigate risks while uncovering AI’s potential.
- Sustainability at Every Level: From energy-efficient data storage to optimized software, business and IT leaders must integrate sustainable thinking into their infrastructure, applications, models, data practices and strategies from the start.
- Simplify and Unify Systems: Reduce complexity by managing hybrid environments uniformly, automating security tasks and leveraging unified data platforms for faster insights and streamlined AI training.
- Ensure Data Resilience and Leverage AI for Defense: Plan for recovery with redundancy systems, roll-back storage and AI model restoration to mitigate risks from failures or attacks. Use AI to identify risks, enhance recovery and secure data with immutable, encrypted and self-healing storage, countering threats from AI-enabled attackers.
Derived from Hitachi Vantara’s 2024 Global State of Data Infrastructure Survey, this report represents 231 BFSI specialists, C-level executives and IT decision-makers spanning 15 countries across the globe.
Download the Banking, Financial Services and Insurance industry report here: https://hitachivantara.com/en-us/gated-forms/state-of-bfsi-data-infrastructure
For more information on how Hitachi Vantara is helping customers provide a data-driven approach to modern data infrastructure, please click here.
