Securing Financial Data in the Era of AI

For finance leaders, protecting sensitive data is non-negotiable — data breaches, compliance failures, or inaccuracies can lead to lost credibility, hefty fines, and costly missteps.

Advanced technologies like large language models (LLMs) are transforming how finance teams operate, offering unprecedented opportunities for automation and insight. But with these benefits come risks that demand proactive management.

This begs the question: How do you harness the power of AI while keeping your organization compliant and data secure?

This article is the first in a series supporting our new video series, Planful AI Labs, where Sanjay Vyas, Planful’s CTO, breaks down what it takes to adopt AI responsibly. Let’s look at the specific risks AI introduces to financial security, actionable strategies to mitigate them, and how Planful’s secure platform protects your business.

Learn more: Planful AI Labs

AI adoption can deliver significant efficiency, and the best tools incorporate proper safeguards that close the door to significant vulnerabilities.

When your team adopts an AI tool for forecasting, it will expect actionable insights. Generic AI tools or those repurposed from third parties might create misleading results—or “hallucinations”—that drive costly projection errors. Or worse, sensitive financial data is inadvertently exposed during interactions with the tool, triggering compliance violations and eroding stakeholder trust.

Common risks finance teams face when adopting AI include:

• Data mismanagement: Without secure systems, sensitive financial information can be exposed or misused, leading to breaches and liability issues.
• Regulatory complexities: Adopting AI requires navigating frameworks like SOC 2 and the EU AI Act while ensuring compliance across jurisdictions.
• AI “hallucinations”: LLMs can produce incorrect or misleading outputs, which, when unvalidated, can lead to misguided financial decisions.

These risks highlight the need for a structured and security-driven approach to adopting AI in Finance.

Trust is the key to unlocking AI’s potential. Without it, even the most innovative tools fail to deliver their full potential.

Your organization’s decisions depend on accurate, secure, and actionable insights. For AI tools to support your success, they need to earn your trust. This starts with transparency, security, and alignment with financial workflows.

As Sanjay puts it:

“Our customers’ data is sacrosanct. Safeguarding it isn’t just our responsibility—it’s our commitment. Every decision we make, every feature we build, begins with trust and security.”

 

4 Questions to ask before adopting new AI solutions for finance

Before adopting an AI tool, finance leaders must thoroughly evaluate its capabilities and safeguards. Here are four questions you must answer to ensure responsible AI adoption:

• How is data protected? Confirm the tool uses end-to-end encryption to protect sensitive information and ensure that data is not sent to untrusted systems or external vendors.
• Does it meet compliance standards? Look for adherence to SOC 2, HIPAA, and the EU AI Act and verify readiness for future regulatory requirements.
• Does it support finance-specific workflows? Ensure the tool offers features like dimension security and can enforce role-based access controls.
• Are outputs validated? Select systems that verify AI-generated insights against reliable datasets to prevent inaccuracies from influencing critical decisions.

By asking these questions, finance teams can confidently adopt AI tools while minimizing risks.

Planful’s AI-driven solutions are purpose-built to meet the unique needs of finance teams. Here’s how the platform ensures your data stays secure while unlocking AI’s potential:

Regulatory compliance is built into the foundation

Planful aligns with global standards, including SOC 1, SOC 2, SOC 3, ISO, and HIPAA. The platform also evolves in response to emerging regulations, such as the EU AI Act, to maintain compliance across various jurisdictions.

Dimension security tailored to finance

Planful restricts access to sensitive dimensional and other data based on user roles, ensuring each team member sees only the information they’re authorized to access.

End-to-end encryption

Data is encrypted both at rest and in transit to mitigate the risk of unauthorized access. Sensitive financial data is never exposed to external, third-party, or unverified systems.

Guardrails against inaccuracies

Planful validates AI-generated outputs against verified datasets to mitigate the risks of hallucinations or misleading results. This ensures insights are accurate, actionable, and aligned with your organizational needs.

AI has the power to revolutionize financial processes by automating manual tasks and delivering real-time insights. But, unlocking its full potential requires a commitment to trust and security.

Planful empowers finance leaders to adopt AI confidently by integrating cutting-edge tools with built-in safeguards. With Planful, you don’t have to choose between innovation and security — you can achieve both.

 

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Want to learn more about how to adopt AI securely and effectively?

Watch our new video series, Planful AI Labs, to explore strategies and innovations to drive secure AI adoption in finance.

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What are the biggest security risks of using AI in finance?

AI tools can introduce risks such as exposing sensitive financial data, violating compliance standards (like SOC 2 or the EU AI Act), and generating inaccurate insights known as “hallucinations.” Without proper safeguards, these issues can lead to costly decisions or reputational harm.

How can finance teams evaluate whether an AI tool is secure?

Finance leaders should ask whether the tool uses end-to-end encryption, meets compliance standards (SOC 2, HIPAA, EU AI Act), validates outputs against trusted data, and supports finance-specific controls like role-based access. These are essential for secure, responsible AI use.

How does Planful AI keep financial data secure?

Planful embeds enterprise-grade security at every level, including encryption in transit and at rest, dimension-based access controls, and output validation to prevent hallucinations. The platform aligns with SOC 1, SOC 2, SOC 3, HIPAA, ISO standards, and adapts to emerging regulations.

What makes Planful’s AI approach different from generic AI tools?

Planful’s AI is purpose-built for finance. Unlike generic tools, it understands financial workflows, uses secure, finance-specific data, and always keeps humans in control. Planful also guards against AI hallucinations by validating outputs against trusted datasets so insights are accurate, auditable, and actionable.

Why is a “security-first” approach essential to AI in finance?

Finance teams manage highly sensitive data and operate under strict compliance mandates. A security-first approach ensures AI can be adopted confidently—enabling automation and insight without compromising trust, accuracy, or governance. Planful AI is built with this mindset at its core.