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Home » Cyber Security News » Vulnerabilities & Exploits » BFSI firms face rising AI risks as data security and quality concerns intensify – ET CISO

BFSI firms face rising AI risks as data security and quality concerns intensify – ET CISO

BFSI firms face rising AI risks as data security and quality concerns intensify – ET CISO

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The rapid integration of artificial intelligence (AI) in the banking, financial services, and insurance (BFSI) sector is straining traditional data infrastructures, creating a difficult balance between security, data quality, and sustainability.

A recent survey by Hitachi Vantara reveals that 84% of BFSI leaders fear their infrastructure may lead to catastrophic data loss due to AI demands, while 48% of respondents cite data security as their top concern.

Despite the growing importance of data quality for AI success, with only 36% of respondents acknowledging its critical role, security concerns remain paramount.

The survey, conducted among 231 global IT and business leaders, highlights the need for BFSI firms to strengthen governance frameworks to mitigate both internal and external threats. With 73% of leaders expressing concerns that AI may empower hackers more than cybersecurity defences, the potential for AI-driven attacks continues to rise.

Many BFSI institutions are accelerating AI adoption without sufficient preparation. Around 71% of respondents reported testing AI models in production environments, while only 4% use controlled sandbox environments to mitigate risks. This lack of adequate risk management exposes organisations to potential regulatory breaches, data loss, and operational disruptions.

Hurdles in AI deployment

The survey underscores key pain points in AI deployment within BFSI. Data is accessible only 25% of the time when required, while AI model accuracy remains low 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 prioritising redundancy systems to safeguard against AI-driven threats.

As AI continues to reshape 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.>

  • Published On Apr 1, 2025 at 09:12 AM IST

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