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The rapid adoption of artificial intelligence (AI) in the banking, financial services, and insurance (BFSI) sector is putting a strain on traditional data infrastructures, making it challenging to balance security, data quality, and sustainability.
A recent survey conducted by Hitachi Vantara found that 84% of BFSI leaders are concerned that their infrastructure may not be able to handle the demands of AI, resulting in potential catastrophic data loss, while 48% of respondents identified data security as their top priority.
Although the importance of data quality for AI success is growing, with only 36% of respondents acknowledging its critical role, security concerns remain the primary focus.
The survey, which polled 231 global IT and business leaders, highlights the need for BFSI firms to strengthen their governance frameworks to mitigate internal and external threats. With 73% of leaders expressing concerns that AI may empower hackers more than cybersecurity defenses, the potential for AI-driven attacks continues to rise.
Many BFSI institutions are accelerating AI adoption without adequate preparation, with around 71% of respondents reporting that they are testing AI models in production environments, while only 4% use controlled sandbox environments to mitigate risks. This lack of proper risk management exposes organizations to potential regulatory breaches, data loss, and operational disruptions.
Challenges in AI Deployment
The survey highlights key pain points in AI deployment within BFSI, including limited data accessibility, with data only available 25% of the time when needed, and low AI model accuracy, at just 21%. Internal AI risks, data breaches, ransomware threats, and AI-driven cyberattacks are additional concerns.
To address these challenges, BFSI firms need to adopt resilient AI-ready infrastructures. Key strategies include ensuring secure sandbox testing during AI experimentation, integrating energy-efficient data storage, automating security tasks to reduce infrastructure complexity, and prioritizing redundancy systems to safeguard against AI-driven threats.
As AI continues to transform the BFSI landscape, institutions that balance innovation with robust security and governance practices will lead the next phase of financial transformation.
Firms that build resilient AI frameworks today will not only mitigate risks but also secure long-term competitive advantages while maintaining trust and operational integrity.
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