The banking, financial services and insurance (BFSI) sector faces growing concerns as companies struggle to balance data security against data quality in the face of unprecedented growth generated from artificial intelligence, new research shows.
Hitachi Vantara’s 2024 Global State of Data Infrastructure Survey distilled responses from more than 230 BFSI C-level executives and IT decision-makers, and specialists across 15 countries. The survey found that 48% of BFSI companies prioritize data security over data quality, even as 36% identify data accuracy as one of the top three factors of a successful AI implementation.
Data Security Eclipses Data Quality—For Now
Data security is critical, particularly in the BFSI sector, where reputations are built on trust. The overwhelming majority (84%) of these companies acknowledge that losing data through a mistake or attack would have catastrophic consequences on their business. More than a third (36%) of those surveyed are concerned about the risk of an internal AI security incident, such as a data breach resulting from an AI error.
Even more concerning are nefarious threats. Nearly three-quarters (78%) of the BFSI leaders surveyed strongly believe that AI will benefit hackers more than those who protect against cybersecurity attacks. A malicious AI-enabled attack has the potential to bring the business to its knees: 38% of BFSI leaders admit their organization might not recover from a ransomware attack.
The need for accurate, quality data is critical to an effective AI implementation and to the long-term return on investment. However, the leaders surveyed indicated that data is available when and where it is needed only 25% of the time, and BFSI AI models are accurate only 21% of the time.
Still, BFSI companies are pushing forward with AI implementations; 41% of those surveyed say AI is already a critical part of their function. Most companies (71%) are testing and iterating their AI implementations live, and only 4% are using controlled, isolated environments.
Plan for a Strategic AI Implementation
Organizations that build a resilient, AI-ready infrastructure can benefit from AI to drive sustainable growth and gain a competitive edge, while maintaining security and their client’s trust. A successful AI implementation starts with quality data, careful planning, and thorough testing in a safe and secure environment to mitigate risks.
Reduce network complexity by automating security tasks and leveraging unified data management platforms to gain critical insights and improve AI training. Build in redundancy and recovery systems to reduce the damage from failures or attacks, and tap into AI to identify potential risks and secure data on encrypted storage solutions. This type of planning also can improve sustainability and boost ROI, key factors as data storage demands skyrocket.
Identifying the goals and key performance indicators will ensure the AI implementation aligns with business goals and stays on track. Of the IT leaders surveyed, 69% say they define use cases for AI to determine where to employ AI, and nearly a third work with a trusted partners to develop AI guidelines and solutions.
Read Hitachi Vantara’s research report: The State of BFSI Data Infrastructure in 2024: AI’s Hidden Cost of Poor Data Quality
Download the full Hitachi Vantara State of Data Infrastructure Report.