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From Data Exposure to Trusted AI: Building Resilient Data Security in Financial Services

In this whitepaper, you’ll find:

  • Why and how AI is amplifying exposure risks.
  • How AI agents and copilots are creating new paths of data leakage.
  • The top exposure drivers that are common across diverse industries.
  • How to safely operationalize AI in the BFSI sector.

DOWNLOAD WHITE PAPER

PII, PAN, PCI, KYC, AML, and trading records are the top examples of financial data that are considered the most sensitive and highly-regulated data across diverse industries. However, when this data is moved across systems or environments, fed to AI models, shared across borders, or replicated in test environments, it creates data exposure pathways in its wake.

The average cost of a data breach in the financial sector is $6.08 million. However, the greatest loss is trust, from partners, customers, and regulators.

The solution is automated discovery and visibility of sensitive data across all environments, controlling who can access it, and regulating its use by AI agents and copilots.

We’ve put together this whitepaper to help CISOs, CDOs, and BFSI security leaders understand how they can reduce risk, simplify audits, and enable accelerated AI innovation in finance by considering some of the industry’s best-practices.

Access Whitepaper Now
From Data Exposure to Trusted AI: Building Resilient Data Security in Financial Services

Award-winning technology, built by a proven team, backed by confidence. Learn more.

Frequently Asked Questions

Banks, insurers and trading firms hold highly regulated data across cloud, SaaS and legacy systems. Without unified visibility and controls, sensitive data is easily overexposed through misconfigurations, shadow copies and excessive access.

AI is only as safe as the data behind it. Trusted AI requires governed, high-quality datasets, clear lineage, least-privilege access and safeguards against leakage or misuse in training and inference workflows.

It helps prevent PII/NPPI, PCI, KYC and MNPI exposure, toxic combinations of risks, AI-driven data leakage and compliance failures under frameworks like PCI DSS, GLBA, SOX, GDPR and DORA.

No. It complements tools like CSPM, DLP, SIEM and IAM by adding data-layer context so you can prioritize what matters and automate the right fixes.

CISOs, CDOs, CIOs, risk/compliance leaders, data owners and AI governance teams across banking, payments, capital markets and insurance.

All-in-One Solution For Your Business Needs

The Multi-disciplinary practice to grow trust-equity of your brand and comply with privacy regulations

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