Key points

• Financial institutions face significant data security challenges due to strict regulatory requirements.
• The use of SaaS applications like Google Drive introduces new data security considerations, necessitating specific data classification strategies. Effective data classification is essential for financial institutions to safeguard sensitive information, maintain trust, and ensure compliance, especially within SaaS environments.
• Metomic's AI-powered solution automates and simplifies data classification and compliance processes, enabling efficient discovery, tagging, and management of sensitive data across various platforms, including SaaS apps, for enhanced security.
• Storing sensitive data in SaaS applications like Google Drive poses security risks, including unauthorised access and data breaches. Metomic's data security report highlights these risks and offers solutions. Read our findings in full.

Heavily regulated financial institutions require effective data classification to safeguard sensitive information and ensure compliance. This is increasingly complex due to reliance on SaaS applications like Google Drive for data storage and collaboration.

Navigating these regulations is crucial, as non-compliance can result in significant fines and reputational damage.

This guide will help IT and security teams tackle data classification, covering data types, regulatory compliance, and best practices for protecting sensitive financial information.

What is data classification and how does it relate to financial organisations?

Data classification is all about sorting information based on how sensitive it is and what could happen if it falls into the wrong hands. For financial organisations, this means pinpointing and tagging sensitive data—like customer bank details or transaction histories—so they know exactly how to protect it. For example, a financial institution might classify customer bank details stored in Google Drive as 'Confidential'.

By using data classification software, financial institutions can effectively safeguard their sensitive financial information. High-risk data might need stricter access controls and encryption, while less sensitive info can be handled with a bit more flexibility. This structured approach not only boosts security but also helps maintain trust with clients, which is crucial in the finance sector.

Data classification also fits neatly into existing security policies and frameworks, such as ISO 27001 and COBIT. These frameworks provide a roadmap for managing and protecting data, which is vital for staying on the right side of regulations and enhancing overall security.

With the global average cost of a data breach hitting $4.88 million in 2024, it’s clear that improperly managed data is an expensive business. Having a solid classification strategy can help mitigate risks and protect organisations from potentially massive financial losses.

What types of financial data require classifying?

In the world of finance, a variety of data types need careful classification to ensure they’re adequately protected.

Let’s break down some of the key categories:

1. Customer Financial Details: This includes sensitive information such as bank account numbers, credit card details, and personal identification data, ‍which might be stored collaborative platforms like Google Drive. Since this data is directly linked to your clients’ financial well-being, it falls into the highest classification level—confidential.‍
2. Company Financials: Internal financial records, earnings reports, and business plans also require stringent protection. If leaked, this data could not only lead to financial losses but also damage the institution's reputation.‍
3. Intellectual Property: Financial organisations often hold valuable proprietary information, such as algorithms for trading or unique methodologies. Protecting this data is essential to maintaining a competitive edge in the market.‍
4. Authentication Data: This includes user credentials, access tokens, and any other information used to verify identity. As breaches can lead to significant security risks, this data also demands a high level of protection.

Each of these data types requires different levels of classification. For example, while customer financial details and authentication data are classified as confidential, information like market research without sensitive data can be labelled as public.

It’s worth noting that the financial sector was the most breached industry in 2023, accounting for a staggering 27% of all breaches. With such high stakes, understanding what types of data need classification is crucial for safeguarding against threats and maintaining compliance.

Why is it important for financial organisations to classify data, particularly in SaaS?

Data classification is necessary for financial institutions because it helps minimise the risk of data breaches, a major concern in an increasingly dangerous cyber landscape, especially as the financial sector is the most targeted and breached industry.

By sorting data into categories like confidential, internal, and public, organisations can apply the right level of protection to sensitive information—especially personal financial details and authentication data. This tailored approach makes it much harder for attackers to access high-value data. The risk is heightened when sensitive data resides in cloud-based SaaS applications like Google Drive, where access controls and visibility need careful management.

Data classification also supports cybersecurity frameworks like Zero Trust, which requires that every access request is verified and authenticated before data is shared. Categorising data allows organisations to control access more effectively, ensuring only authorised personnel handle sensitive information.

The stakes are high in the financial sector, with the average cost of a data breach reaching $6.08 million – over $1 million higher than the global average cost of a data breach.

Mishandling data not only leads to costly breaches but can also damage an organisation’s reputation. Legal repercussions can include hefty fines for non-compliance, alongside the loss of customer trust—a vital asset for any financial institution.

What compliance regulations must financial institutions adhere to?

Financial institutions operate in one of the most heavily regulated sectors, where compliance is non-negotiable. A wide range of regulations govern how sensitive data is handled, and failure to comply can result in significant penalties.

Here’s a quick overview of some key regulations:

1. GDPR (General Data Protection Regulation): This EU regulation focuses on protecting customer data privacy. Financial institutions handling European customers' data must ensure stringent data protection measures are in place to avoid hefty fines, which can reach up to 4% of global turnover.
2. CCPA (California Consumer Privacy Act): Similar to GDPR, CCPA grants California residents more control over their personal data. Non-compliance can result in fines of up to $7,500 per violation.
3. SOX (Sarbanes-Oxley Act): This US regulation requires strict auditing and financial transparency, ensuring financial data integrity. Failing to meet SOX standards can lead to criminal charges and severe reputational damage.
4. ISO27001: An international standard for information security, ISO27001 provides a framework for managing sensitive financial data and implementing security controls. Certification helps financial organisations demonstrate their commitment to data security.
5. NYDFS Part 500: This regulation, specific to New York, mandates that financial institutions must establish a comprehensive cybersecurity programme. Compliance requires regular risk assessments, data encryption, and the reporting of cybersecurity incidents.

For financial institutions, the stakes are high. Beyond fines, non-compliance can severely damage a business' reputation, leading to a loss of customer trust. Regulatory breaches can also result in operational disruptions, which can be costly and time-consuming to recover from.

These regulations extend to data stored and processed in SaaS environments like Google Drive, requiring financial institutions to ensure their use of these platforms meets compliance standards.

For more details on compliance regulations and how they apply to financial services, navigate to our checklist of financial services regulations you should know about.

Data Classification in SaaS Applications, like Google Drive

Financial institutions are increasingly leveraging the collaboration and accessibility benefits of SaaS applications like Google Drive. However, storing sensitive financial data in these environments introduces unique security considerations. Data classification plays a vital role in mitigating these risks.

As our internal report highlights, Google Drive, can house various types of financial data, from customer account details to internal reports. By implementing a data classification strategy, organisations can label files in Google Drive according to their sensitivity (e.g., using custom metadata fields or naming conventions). This allows for granular control over who can access, share, and download information.

For instance, files classified as "Confidential" can be restricted to specific teams, while sharing of "Restricted" documents outside the organisation can be automatically blocked.

A key challenge is the distributed nature of data across multiple SaaS applications. Data classification provides a consistent framework for understanding and managing data security regardless of where it resides. Tools like Metomic can automate the classification process within Google Drive, ensuring that as new files are created or uploaded, they are appropriately tagged and protected according to the organisation's policies. This proactive approach is essential for maintaining compliance and preventing data leaks in the cloud.

Implementing Best Practices for Financial Data Classification

To keep financial data safe and compliant in SaaS apps, financial organisations should follow these key best practices for effective data classification:

1. Know your data

Start by identifying the types of information you're handling, from customer financial details to internal business records.

2. Categorise based on risk

Label your data as confidential, internal, or public, depending on how sensitive it is and what could happen if it's exposed.

3. Keep policies fresh

Regularly update your data classification policies to account for new data types and any changes in regulations.

4. Automate access controls

Use automation to limit access to sensitive data, making sure only authorised people can see or edit it.

5. Review often

Regularly check your data classification and access controls to catch any outdated labels or potential security gaps.

6. Work together across teams

Collaborate with different teams to ensure data is classified properly according to both business needs and security guidelines.

How can Metomic help?

Metomic plays a crucial role in assisting financial organisations with their data classification challenges in SaaS applications.

Here’s how our platform can enhance your data security and compliance efforts:

• Automated data discovery and classification: Metomic leverages advanced AI technology to automatically identify and classify sensitive data across various cloud and SaaS platforms. This automation allows organisations to maintain oversight of their critical information, ensuring proper management and protection.
• Ensuring compliance with regulations: Our platform simplifies the complexities of regulatory compliance. By effectively tagging and managing data, Metomic helps financial institutions meet the stringent requirements of financial regulations such as GDPR, CCPA, and ISO27001, thereby reducing the risk of non-compliance.
• Mitigating risks and improving data visibility: In addition to classification, Metomic identifies potential risks by flagging sensitive information that may be improperly shared or stored. This enhanced visibility enables organisations to proactively address vulnerabilities, ensuring robust protection for sensitive financial data.

📝Report: The Risks of Storing Sensitive Data in Google Drive

After scanning approximately 6.5 million Google Drive files, Metomic found 40.2% contained sensitive data that could put an organisation at risk of a data breach or cybersecurity attack.

Other key highlights include:

• 34.2% of all the files scanned were shared with external contacts (email addresses outside of the company’s domain).
• More than 350,000 files (0.5%) had been shared publicly, giving access to anyone who had the document link
• 18,000 files were flagged as “Critical Level” data files, meaning the information contained “Highly Sensitive” data or the file permissions were not applied securely.

Have a read of our findings in full, showing the risky nature of storing sensitive data in Google Drive.