Data Retention Policies in Finance: How To Ensure & Scale Compliance in 2025

Updated March 13th, 2025

Share this article

Data retention policies in finance define how financial data is stored, managed, and disposed of when no longer required. These policies help organizations comply with regulations, mitigate risks, optimize storage costs, and ensure audit readiness.
See How Atlan Simplifies Data Governance ✨ – Start Product Tour

This article will explore the concept of data retention policies in finance, emerging trends and regulations, benefits, the need for automation, and how a unified control plane like Atlan can help.

Table of Contents #

  1. What are data retention policies in finance?
  2. What are the key components of a data retention policy in finance?
  3. Data retention policies in finance: Business benefits
  4. Data retention policies in finance: Key challenges
  5. Data retention policies in finance: Policy setting and enforcement
  6. How Financial Institutions reduced compliance risks and improved GDPR compliance
  7. Bottom line
  8. Data retention policies in finance: Related reads

What are data retention policies in finance? #

Data retention policies in finance are guidelines that determine how long financial data should be stored, how it must be managed, and when it should be securely deleted. These policies specify the duration for which different types of financial records must be kept and outline procedures for their secure handling and eventual disposal.

According to Gartner, data retention policies ‘focus on the life cycles of D&A artifacts — how long they are retained and archived, and when they are disposed of.’

Data retention requirements can vary depending on your business activities, types of data collected, and regulations governing your industry and geography.

For instance, according to the Sarbanes-Oxley Act of 2002, financial audit and review data should be retained for seven years. Meanwhile, the BSA requires banks to retain PII data on a customer for five years after the account’s closed. For credit card accounts, the retention period is five years after the account’s closed or dormant.

Why are data retention policies important? #


Effective data retention policies ensure compliance, reduce legal risks, and protect sensitive information. Without clear retention and deletion guidelines, organizations risk regulatory penalties and data security issues.

For example, in 2019, the Danish DPA (Data Protection Agency) reported IDDesign A/S and proposed a DKK 1.5 million fine for failing to delete personal data of 385,000 customers, violating GDPR data retention rules.

During a 2018 inspection, authorities found that IDDesign’s older system still stored names, addresses, phone numbers, emails, and purchase history, with no defined deletion policy. The company never removed outdated personal data, failing to comply with GDPR’s requirement to erase data when no longer necessary.

This case underscores the risks of non-compliance and the importance of implementing data retention policies at scale to prevent unnecessary data storage, security, and compliance vulnerabilities.

Data retention policies in finance: Key regulations to follow #


Financial institutions must navigate a complex landscape of regulations that govern data retention. Key regulations include:

  • GDPR: The General Data Protection Regulation is a European Union law that mandates organizations to retain personal data only as long as necessary for its intended purpose. Factors influencing retention periods include legal obligations, the nature of the data, and the organization’s legitimate interests.
  • SOX: As mentioned earlier, the Sarbanes-Oxley Act requires public companies to maintain accurate financial records, including accounting and audit documents, for at least seven years.
  • Dodd-Frank Act: This U.S. federal law promotes financial stability by improving accountability and transparency in the financial system. It requires financial institutions to retain swap transaction records and related communications for at least five years.
  • GLBA: The Gramm-Leach-Bliley Act requires financial institutions to explain their information-sharing practices and to safeguard sensitive data. While it doesn’t specify exact retention periods, it mandates that institutions develop and implement policies ensuring the confidentiality and security of customer information throughout its lifecycle, including proper disposal when no longer needed.
  • PCI DSS: The Payment Card Industry Data Security Standard outlines measures for protecting cardholder data. Regarding data retention, it requires organizations to limit storage duration of cardholder data to that which is strictly necessary for legal, regulatory, and business requirements, and mandates secure deletion of data when it is no longer needed.
  • SEC rule 17a-4: Enforced by the Securities and Exchange Commission, this rule mandates that entities such as brokers and dealers retain records of transactions for a minimum of six years, with the first two years requiring immediate accessibility. The rule specifies that records must be stored in a non-rewritable, non-erasable format to ensure data integrity.

For financial institutions operating in multiple jurisdictions, retention policies must be aligned across overlapping regulations to ensure full compliance.

What are the key components of a data retention policy in finance? #

Key components of such a well-structured data retention policy in finance include:

  1. Legal requirements and scope definition: Identify and document all relevant legal, regulatory, and industry-specific obligations that dictate data retention periods and practices. Clearly define the scope of the policy to specify which data types and business units are subject to these requirements.
  2. Data identification and classification: Systematically identify and categorize data based on its type, sensitivity, and importance. Classifications may include categories such as personally identifiable information (PII), financial records, transactional data, and audit logs. This process aids in setting and enforcing appropriate retention periods and handling procedures for each data category.
  3. Retention policy metadata: Develop and maintain metadata that outlines retention rules for each data category. This metadata should detail the retention format, duration, privacy, legal justifications, and any specific handling instructions.
  4. Storage period specifications: Clearly state the duration for which data must be stored before it becomes eligible for archival or deletion.
  5. Archival and deletion processes: Establish procedures for the secure archival of data that is no longer actively used but must be retained for compliance or historical purposes. Additionally, define processes for the secure deletion of data once it has surpassed its retention period, ensuring that data is irretrievable and disposed of in accordance with legal and organizational standards.
  6. Audit logs for compliance monitoring: Record actions related to data retention, such as access, modification, archiving, and deletion activities. Maintaining detailed audit logs supports internal reviews and provides a traceable history of data handling practices.

Data retention policies in finance: Business benefits #

Strong data retention policies help financial companies stay audit-ready, follow regulations, reduce risks, improve efficiency, cut costs, and keep data reliable for decision-making. Top business benefits include:

  • Cost and storage savings: Reduces unnecessary data storage expenses by managing retention timelines.
  • Easier audits: Ensures quick access to required financial records for internal and external audits.
  • Better compliance: Helps meet industry regulations, and avoid accidental deletion of critical data or retention beyond the specified period.
  • Lower risks: Minimizes legal, financial, and cybersecurity risks with effective data retention policy setting and enforcement.
  • Improved efficiency: Streamlines data access and reduces manual compliance workload.

Data retention policies in finance: Key challenges #

While data retention policies are essential for compliance and efficiency, financial institutions face several challenges balancing regulatory requirements, security risks, and operational efficiency.

Here are some top challenges in implementing data retention policies in finance:

  1. Evolving regulations: Financial institutions must adapt to constantly changing data retention laws. Staying updated and compliant requires continuous monitoring and policy adjustments.
  2. Cross-border compliance issues: Operating in multiple countries means navigating various data retention laws, which can be complex and sometimes conflicting.
  3. Scalability concerns: Financial institutions handle vast amounts of diverse data, making it challenging to adapt data retention policies as data volumes grow and new regulations emerge.
  4. Data retrieval challenges: Ensuring old records remain accessible and usable when needed, despite the complexity of your data estate is a challenge.
  5. Automated deletion risks: Improperly configured automation workflows for data retention can lead to accidental deletion of data still required for audits or investigations.

Data retention policies in finance: Policy setting and enforcement #

Data retention policy setting and enforcement should be an integral part of your data governance workflows. Start by:

  1. Drafting data retention policy document connecting policies to data assets (identify which data types, regulations, and business needs apply)
  2. Adding exceptions to your policies for every edge case
  3. Building a centralized policy repository to monitor policy coverage and compliance across your data estate
  4. Tracking how well policies are followed with enforcement analytics
  5. Maintaining clear records of policy enforcement with detailed audit trails

Automate enforcement across systems to ensure that data retention policies are connected to your financial data assets continuously and at scale.

How a unified control plane can help? #


A unified control plane for data acts as a single pane of glass to define data retention policies, enforce them, and oversee policy coverage across the entire data estate.

Powered by automation and AI, it embeds policies into data workflows, making sure that they’re consistently enforced across systems and automatically updated.

The key capabilities of such a platform supporting data retention policy enforcement for financial institutions would include:

  • Transparency center: Get a top-down view of data retention policy coverage across your data estate, investigate overlapping policies and non-compliance incidents, update expiring policies, and more from a single location.
  • AI-assisted policy creation: Draft the policy purpose, add technical scope (data source, format, tags, and certification status), and more using AI.
  • Real-time policy enforcement and monitoring: Monitor data usage, access patterns, and compliance with data retention policies in real-time.
  • Advanced audit trails: Record everything from policy changes and access requests to data asset modifications – similar to version history logs tracked by apps like Google Docs or Notion.
  • Automation: Scale tagging and metadata-driven enrichment for your data assets with rule-based automations.
  • Column-level, automated data lineage: Implement real-time, cross-system, column-level data lineage mapping to get complete visibility into how financial data traverses your organization.
  • Real-time alerts: Get alerted about data retention policy incidents and breaches when and where they happen.
  • Endless extensibility with an open architecture: Use an extensible self-service layer to integrate with your tech and data stack.

How Financial Institutions reduced compliance risks and improved GDPR compliance #

Austin Capital Bank: Streamlining Data Access for Compliance #


Austin Capital Bank, transitioning to a digital-first model, needed to manage sensitive customer data while minimizing compliance risks. By implementing Atlan on top of Snowflake, they created strict access controls that ensured only the right personnel had access to sensitive data. This solution helped them comply with both internal policies and external regulations while maintaining a high standard of data stewardship. With Atlan’s interface, managing data access became easier and more efficient. As Ian Bass, Head of Data & Analytics, shared, “We wanted to make sure that only the right people within our organization have access to it and that we have the proper controls around it." He added, “Atlan became a necessity. That’s how we control access in an easily repeatable fashion.”

Tide: Automating GDPR Compliance with Atlan #


Tide, a UK-based digital bank, was focused on ensuring GDPR compliance, especially with the “Right to be Forgotten” requests. To meet these requirements, their data and legal teams used Atlan to define and tag personally identifiable information (PII) across their systems. Through Atlan Playbooks, they automated the identification and management of PII, drastically reducing the manual effort required for compliance and avoiding potential GDPR fines. This efficient solution transformed what was once a 50-day process into a task completed in mere hours. Michal Szymanski, Tide’s Data Governance Manager, explained, “We can avoid fines and handle personal data at a high level," adding, "Atlan turned what used to take 50 days into just hours of work.”

Porto: Ensuring LGPD Compliance with Automated PII Tagging #


Porto, a leading insurance and banking company in Brazil, needed to comply with Brazil’s General Data Protection Law (LGPD). With vast amounts of customer data to manage, Porto faced risks like penalties, lawsuits, and reputational damage if non-compliance occurred. Atlan helped by automating the tagging of personally identifiable information (PII) using predefined rules, reducing the manual effort required for sensitive data management. This automation made it easier for Porto to maintain compliance with LGPD and mitigate risks. Danrlei Alves, Senior Data Governance Analyst, noted, “We need to ensure compliance with Brazilian LGPD laws. We can face penalties for non-compliance, and could be subject to lawsuits if we have a data breach." He added, “This has saved us tons of hours.”

Bottom line #

Data retention policies in finance ensure proper data management, compliance, cost efficiency, and risk mitigation. By leveraging a unified control plane powered by automation and AI, you can streamline data retention policy setting, enforcement, and monitoring across your data estate.

This approach helps financial institutions stay compliant, optimize costs, and ensure data integrity while adapting to evolving regulations.

Share this article

[Website env: production]