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 prioritise 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% recognise the importance of data quality for AI success, financial leaders’ focus remains on data security, leaving gaps in AI performance and long-term ROI.
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 that 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 the 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 that an AI-enabled attack could cause a data breach.
“As AI rapidly transforms India’s financial sector, the real challenge is ensuring it operates on accurate, secure, and well-governed data. Trust is the foundation of India’s BFSI industry, and even a small AI-related error, whether it is an inaccurate prediction or a security breach, can weaken customer confidence and create regulatory challenges,” said Hemant Tiwari, Managing Director and Vice President of India and SAARC Region, Hitachi Vantara. “While 48% of global financial leaders prioritise security while implementing AI, India’s BFSI sector must take a more proactive approach. We need to build resilient data infrastructures that balance security with accuracy, governance, and sustainability. Institutions that establish reliable AI frameworks today will lead the next wave of financial innovation while maintaining trust and operational integrity.”
“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.
“While the rapid adoption of generative AI in the financial services sector is exciting, financial institutions need to ensure they are taking a strategic approach,” said Alenka Grealish, co-head Generative AI Intelligence, Celent. Organisations must balance speed and innovation with a clear focus on security, accuracy, and ethical responsibility. Those that prioritise thoughtful planning and robust frameworks will not only mitigate risks but also unlock the full potential of GenAI to drive sustainable growth and competitive advantage. In the process, they will build lasting trust with their stakeholders.”
The survey outlines the key considerations to building a more resilient, AI-ready infrastructure to help BFSI organisations 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 optimised 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.