Data Compliance Management in Banking: Your Complete Guide in 2025
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Data compliance management in banking is essential for ensuring secure, transparent, and efficient operations. Beyond handling sensitive customer data, the challenge lies in managing the complexity and speed at which vast volumes of data are captured every second.
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Data assets often originate from numerous sources and exist in various formats, adding to the difficulty of maintaining compliance at scale.
With an evolving regulatory landscape that includes established frameworks like GDPR, PCI DSS, Basel III, and BCBS 239, banks must continuously adapt their data practices.
This article explores the critical aspects of data compliance management in banking, its significance, and how to tackle challenges to drive operational efficiency, informed decision-making, and faster innovation.
Table of Contents #
- What is data compliance management in banking?
- Why do you need data compliance management in banking?
- Who is responsible for data compliance management in banking?
- How to tackle data compliance management in banking
- Implementing data compliance management in banking: Core capabilities
- Effective data compliance management in banking pays dividends
- Data compliance management in banking: Related reads
What is data compliance management in banking? #
Data compliance management in banking refers to the policies, processes, and systems that ensure banks handle data securely and in alignment with global regulations such as GDPR, CCPA, PCI DSS, BCBS 239, and AML directives.
Its primary purpose is to protect sensitive customer and transaction data with appropriate safeguards, ensuring security, transparency, and compliance with industry standards.
Consider a scenario where a US-based bank operates in the European Union and Asia. By implementing comprehensive data governance and compliance frameworks, the bank ensures that customers’ personal data is protected across different jurisdictions.
Why do you need data compliance management in banking? #
Data compliance management impacts a bank’s operations and business outcomes. For instance, the penalties for EU GDPR non-compliance can reach up to €20 million or 4% of global annual turnover. This incident would require the bank to divert attention from innovation or market expansion and instead, focus on strengthening internal data infrastructure.
Strong data compliance management in banking provides transparency in data usage, strengthens security frameworks, and ensures banks remain audit-ready at all times. As a result, banks can:
- Increase trust in their data
- Reduce compliance risks and improve operational stability
- Enhance productivity and operational efficiency by reducing errors, delays, and redundancy
Data compliance management in banking: How Austin Capital Bank reduced risks and improved productivity and data trust #
Austin Capital Bank had a vast data estate with lots of sensitive customer data, including addresses, names, birth dates, social security numbers, and account numbers. Part of making sure that their data is secure and compliant with regulations was to set up proper controls – only the right people had access.
“The first step was creating masking policies, ensuring that only authorized employees of Austin Capital Bank would be permitted to access sensitive data.” - Ian Bass, Head of Data and Analytics at Austin Capital Bank
The bank used an active metadata management platform like Atlan as an interface on top of Snowflake to implement data masking policies.
As a result, Austin Capital Bank could finally offer self-service to its data consumers without sacrificing strong access and masking policies, thereby improving data discovery and enhancing trust in their data.
Also, read → Gartner Active Metadata Management Research Guide (2025)
Who is responsible for data compliance management in banking? #
Clear accountability ensures banks remain compliant while enabling cross-functional collaboration. Data compliance management in banks involves several key stakeholders across various departments:
- Compliance officers: Responsible for ensuring that the bank meets all regulatory requirements.
- Data governance teams: Oversee the overall management and governance of data within the organization.
- Data stewards: Manage data assets, ensuring that data is properly classified and protected.
- Risk management officers: Assess potential risks associated with data breaches and non-compliance.
- IT and security teams: Implement the technical infrastructure and security measures needed to protect data.
- Data Protection Officers (DPOs): Specifically focused on ensuring compliance with data protection laws like GDPR.
These roles work in tandem to ensure that data compliance is maintained across the organization. It’s important to note that each institution structures these roles differently based on its size, regulatory obligations, and operational complexity.
How to tackle data compliance management in banking #
To navigate the complexities of data compliance management, banks need to implement a comprehensive, organization-wide approach that goes beyond strategy. Here’s how to tackle the key challenges:
- Understand the key data compliance regulations in banking
- Understand the data landscape and identify compliance gaps
- Establish a unified control plane for compliance requirements
- Leverage automation and AI for compliance at scale
- Foster an organization-wide data culture
1. Understand the key data compliance regulations in banking #
To manage data compliance effectively, knowing the relevant regulations is essential. Here’s a quick overview of some of the key regulations for banks:
- GDPR (General Data Protection Regulation): GDPR focuses on data protection and privacy for all individuals within the European Union. It mandates strict guidelines for data collection, processing, and storage, with heavy penalties for non-compliance.
- CCPA (California Consumer Privacy Act): CCPA is a data privacy law that protects consumer data rights in California. It includes requirements for businesses to disclose what personal information is being collected and how it is used.
- BCBS 239 (Basel Committee on Banking Supervision 239): BCBS 239 is a regulation that focuses on risk data aggregation and reporting within financial institutions. It mandates that banks ensure accurate and timely risk data aggregation to support effective decision-making, and requires robust governance to ensure compliance with risk management practices.
- PCI DSS (Payment Card Industry Data Security Standard): PCI DSS is a set of security standards designed to ensure that businesses handle payment card information securely, preventing fraud and data breaches.
- Basel III: Basel III is a global regulatory framework focused on the management of risk in banking institutions. It ensures transparency in financial reporting and addresses systemic risk concerns.
- SOX (Sarbanes-Oxley Act): SOX is a U.S. law that mandates financial transparency and accountability in corporate reporting, impacting banks’ data reporting practices.
2. Understand the data landscape and identify compliance gaps #
Before implementing compliance measures, banks must evaluate their data ecosystem to identify vulnerabilities.
Data is often spread across multiple systems, including transactional databases, customer relationship management (CRM) platforms, payment networks, and cloud storage environments. Without full visibility, ensuring compliance with data security, privacy, and reporting standards becomes a challenge.
A comprehensive data audit helps banks pinpoint compliance gaps related to:
- Data storage and retention policies: Ensuring customer information is stored securely and only retained for as long as necessary.
- Access controls: Restricting access to sensitive data based on roles and responsibilities.
- Data classification: Properly labeling structured and unstructured data to ensure it is handled appropriately.
- Data lineage tracking: Understanding how data flows through the bank’s data estate to maintain auditability and prevent unauthorized changes.
3. Establish a unified control plane for compliance requirements #
A fragmented compliance strategy increases the likelihood of errors, inconsistencies, and regulatory violations. A unified control plane centralizes compliance management, ensuring that data policies, access permissions, and regulatory reporting are enforced consistently across the organization.
This control plane enables banks to:
- Ensure consistent policy enforcement across multiple jurisdictions without duplicating efforts
- Get real-time insights into compliance status, policy coverage, and more
- Standardize reporting and documentation to reduce data chaos and operational inefficiencies
Also, read → A unified control plane for data is the future of data cataloging
4. Leverage automation and AI for compliance at scale #
Automation and AI-driven compliance tools allow banks to scale their compliance programs efficiently, reducing operational burdens while improving accuracy.
Key areas where automation can enhance compliance include automated data classification, documentation, compliance reporting, and more.
5. Foster an organization-wide data culture #
Compliance management requires alignment across teams, from executives to frontline employees. A strong data culture ensures that compliance isn’t an afterthought but an integrated part of banking operations.
Implementing data compliance management in banking: Core capabilities #
Successful data compliance management in banking requires a unified control plane for data and metadata with the following core capabilities:
- Metadata management: Automatically capturing, organizing, and governing metadata for compliance tracking. This enables banks to maintain up-to-date records and quickly respond to audits.
- Real-time policy and transparency center: Offers a centralized view of compliance status, policy enforcement, and risk assessment across all banking operations.
- Role-based access controls (RBAC): Ensures that only authorized personnel can access sensitive data, thereby minimizing the risk of unauthorized access.
- Automated data classification and tagging: Identifying and tagging sensitive data like personally identifiable information (PII) or payment details.
- Automated documentation: Leveraging automation to capture data context, ownership details, and compliance metadata, ensuring that every data asset is properly documented for audits and regulatory checks.
- Real-time anomaly detection: Automatically flagging anomalies to detect potential fraud or policy violations.
- Automated audit trails and reporting: Generating regulatory compliance reports with minimal manual intervention.
- Automated cross-system, column-level data lineage tracking: Provides a clear and traceable path for data as it moves through various systems, ensuring transparency and accountability.
- Automated compliance reporting: Facilitates the generation of regular compliance reports, reducing the manual effort required to maintain records and meet regulatory demands.
How Tide embedded data privacy into automated processes with a unified control plane for data and metadata #
Tide, a UK-based digital bank with nearly 500,000 small business customers, sought to improve their compliance with GDPR’s Right to Erasure, commonly known as the “Right to be forgotten”.
Initially, Tide’s engineers anticipated manually identifying, tagging, and securing PII (personally identifiable information), a process estimated to take 50 days.
After adopting Atlan as their unified control plane for data and metadata, Tide’s data and legal teams collaborated to define personally identifiable information in order to propagate those definitions and tags across their data estate.
Tide used Atlan Playbooks (rule-based bulk automations) to automatically identify, tag, and secure personal data, turning a 50-day manual process into mere hours of work. By reducing manual effort and minimizing the risk of errors, Tide safeguarded customer privacy while achieving operational efficiency.
Effective data compliance management in banking pays dividends #
With increasing regulatory scrutiny and evolving data privacy laws, banks must proactively strengthen their data compliance management strategies. This ensures regulatory compliance, enhances trust, improves risk management, and supports business growth.
By investing in automation, centralized governance, and proactive compliance monitoring, banks can minimize legal risks while positioning themselves for long-term success in a data-driven financial landscape.
Data compliance management in banking: Related reads #
- Data Compliance Management in 2025
- What is Data Governance? Its Importance, Principles & How to Get Started?
- Data Governance in Banking: Benefits, Challenges, Capabilities
- Data Governance and Compliance: An Act of Checks & Balances
- Data Governance and GDPR: A Comprehensive Guide to Achieving Regulatory Compliance
- Financial Data Governance: Strategies, Trends, Best Practices
- BCBS 239 Data Governance: What Banks Need to Know in 2025
- BCBS 239 Compliance: What Banks Need to Know in 2025
- Achieving HIPAA Compliance with Data Governance
- FRTB Compliance: Exploring the 6 Core Pillars, Benefits, Impact
- IFRS 17 Compliance: Requirements, Benefits & More
- Data Governance & Business Intelligence: Why Their Integration Matters and How It is Crucial for Business Success?
- Data Migration in Banking: Your Complete 2025 Guide
- Data Discovery in Banking: Get Business Value from Siloed Data
- Unified Control Plane for Data: The Future of Data Cataloging
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