Key points

• Financial institutions face stringent data security challenges due to heavy regulation.
• Different types of financial data require varying levels of protection and classification.
• Compliance with regulations like GDPR and NYDFS Part 500 is crucial to avoid fines and reputational damage.
• Metomic automates and simplifies data classification and compliance processes, using AI to efficiently discover, tag, and manage sensitive data for enhanced security.

Financial institutions face a lot of regulatory challenges, making effective data classification essential for safeguarding sensitive information and ensuring compliance.

Data classification is vital for financial institutions, as understanding and protecting sensitive information is crucial for maintaining trust and integrity.

With various types of data—from customer account details to internal reports—each requires careful handling to ensure compliance with regulations like GDPR and NYDFS Part 500.

However, navigating these complex regulations can be tricky, and non-compliance can lead to hefty fines and serious reputational damage that could affect your entire organisation.

This guide aims to help IT and security teams tackle data classification effectively. We’ll dive into the types of financial data that need classification, why regulatory compliance matters, and share best practices for protecting sensitive information in a financial institution.

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.

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. 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.

📝Report: The State of Data Security in Financial Services

In our 2024 ‘The State of Data Security in Financial Services’ report, we dissect our own proprietary data to understand how financial services companies are navigating data security. You'll find:

• The pivotal data types that hold significance for Financial Service Companies
• A comprehensive understanding of the risks posed by stale data and effective management strategies
• Compelling reasons why financial institutions should prioritise attention to access controls

Why is it important for financial organisations to classify data?

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.

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 they 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 the 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.

For more details on compliance regulations and how they apply to financial services, check out Metomic’s checklist of financial services regulations you should know about.

Best practices for financial data classification

To keep financial data safe and compliant, 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.

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 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.

Getting started with Metomic

Getting started with Metomic is simple and can significantly enhance your data classification and compliance efforts.

Here’s how to begin:

• Free risk assessment: Kick things off with a complimentary risk assessment to identify potential vulnerabilities in your data security. Metomic can pinpoint risks across platforms such as Google Drive, Slack, and various other cloud services.
• Book a personalised demo: If you’re interested in seeing how our solutions can benefit your organisation, book a personalised demo with our security experts. They’ll walk you through how Metomic can be customised to meet your specific needs.
• Contact us: If you have any questions or need more information, don’t hesitate to reach out to our team. We're here to help you implement a comprehensive data classification strategy and address any inquiries you may have.