AI's Data Demands Expose Governance Weaknesses in BFSI, reports Hitachi Vantara

The fast pace of artificial intelligence (AI) is now putting pressure on the traditional data infrastructures in the Banking, Financial Services, and Insurance (BFSI) sectors; making it a difficult position for organizations, as they seem to be forced to balance security, data quality, and sustainability.

According to a report issued by Hitachi Vantara, a wholly owned subsidiary of Hitachi, Ltd., 84% of BFSI leaders state they are worried their infrastructure will cause a catastrophic loss of data due to the demands placed by AI. 

Meanwhile, just 36% of respondents actually focus on data quality—that is paramount to AI performance and represents a way to measure ROI over the lifecycle of the technology. The 2024 State of Data Infrastructure Report highlights the need for leaders in BFSI to implement solid governance frameworks. While AI is being adopted at a higher rate—41% of respondents stated AI is core to their operations—data security was still the primary concern for 48% of BFSI leaders and reflects more concern over internal and external threats.

The Price of Ignoring Data Quality

Although there is a focus on security, the report did mention various pain points that obstruct AI deployments in BFSI:Limited Access to Data: Data is available when required only 25% of the time in banking, financial services and insurance institutions.Low AI Model Accuracy: AI accuracy in the BFSI sector is only 21%.Internal AI Risks: 36% of BFSI leaders are concerned about data breaches due to internal AI risks.Ransomware and AI Attacks: 38% of BFSI leaders are concerned about restoring from a ransomware event, and 32% are concerned about attacks driven by AI.

"As AI matures and evolves in India's financial sector, it's critical that AI is based on data that is accurate, secure and well governed. Trust is the cornerstone of any financial services sector in India and can be broken even by a small event caused by AI, whether it's an erroneous prediction or an insecure action, leading to reduced trust and regulatory implications," said Hemant Tiwari, Managing Director and Vice President of India & SAARC Region, Hitachi Vantara.

Rapid Growth of AI without Proper PreparationThe report also shows that, in many cases, BFSI firms are implementing AI-driven solutions without adequate risk mitigation measures. 71% of BFSI leaders reported they have tested AI models in a production environment, and only 4% are sandbox testing in a controlled environment. When organizations deploy AI without consideration to the risk of AI-driven data and regulatory breaches, they position themselves under unnecessary risk.

Building Resilient AI-Ready Infrastructure

To future-proof AI adoption in BFSI, the report outlines key strategies:

1. Responsible AI Experimentation: 42% of BFSI leaders believe skill-building through experimentation is essential. However, secure sandbox testing is critical to minimizing risk while exploring AI’s potential.

2. Sustainability-Driven Infrastructure: Organizations must integrate energy-efficient data storage and sustainable AI models into their long-term strategies.

3. Simplification and Unified Systems: Reducing infrastructure complexity by automating security tasks and leveraging unified data platforms can streamline AI training and deployment.

4. Enhancing Data Resilience with AI: BFSI institutions should prioritize redundancy systems, roll-back storage, and AI-powered risk detection to counteract AI-driven cyber threats.

“While the rapid adoption of generative AI in financial services is exciting, institutions must balance speed and innovation with security, accuracy, and ethical responsibility,” said Alenka Grealish, Co-Head of Generative AI Intelligence at Celent. “Organizations that take a strategic approach will not only mitigate risks but also unlock AI’s full potential for competitive advantage and long-term sustainability.”

As AI continues to reshape BFSI operations, firms that prioritize a balanced approach—integrating security, accuracy, and sustainability—will emerge as industry leaders, driving financial innovation while maintaining trust and operational integrity.