Regulation is no longer just about policies, paperwork and audits. It is increasingly about data.
If your organization needs to meet requirements such as the Basel Committee on Banking Supervision’s Principles for effective risk data aggregation and risk reporting (BCBS 239), the General Data Protection Regulation (GDPR), the California Consumer Privacy Act (CCPA) or new environmental, social and governance (ESG) expectations, you need to show that the data behind your controls is accurate, complete and reliable. It is not enough to have controls in place. You also need to prove the data supporting them can be trusted.
That is why data quality is no longer a back-office technical task and is becoming a core regulatory control.
Why regulators are looking more closely at data
Regulators are asking tougher questions:
- Can you trace reported figures back to source systems?
- Can you show that data is consistent across different platforms and teams?
- Can you spot and fix errors quickly?
- Can you explain how data moves, changes and is used?
These questions matter because weak data creates real regulatory risk. Inaccurate financial reporting, incomplete customer records and poor visibility across systems can all undermine compliance efforts, including know your customer (KYC) and anti-money laundering (AML) processes.
Why a reactive approach no longer works
Many organizations still handle data quality reactively. When a problem appears, one team fixes it. But without a broader approach, the same issue often appears again in another system, process or team.
Today, you need to build data quality into the full data lifecycle. That means monitoring data continuously, applying consistent rules, and automating validation, cleansing and enrichment wherever possible. It also means making every step visible and explainable.
Benefits of turning data quality into a control framework
When you treat data quality as a control, you move from reacting to issues to preventing them.
That shift helps you:
- Reduce compliance risk
- Produce more consistent, audit-ready reporting
- Improve trust in the data used across your business
- Respond faster to regulatory questions
It also helps your teams spend less time correcting problems and more time acting on reliable information.
How Experian helps your build trust in your data
Experian helps organizations put data quality into practice as a structured, repeatable control framework.
With Aperture Data Studio, you can profile and explore complex data, uncover anomalies and spot hidden relationships across systems. That gives you a clearer starting point, especially when legacy platforms and silos make it hard to see what is really happening in your data.
Aperture Data Studio allows you to define and apply standard rules that support regulatory expectations. Instead of relying on manual checks or disconnected processes, you can monitor data continuously and produce consistent, audit-ready outputs.
- Improve accuracy at scale
Reliable reporting starts with reliable inputs. Trusted data quality helps you cleanse, standardize and enrich data at scale, including capabilities such as address validation, deduplication and data enrichment. That helps you keep customer and operational data accurate and consistent. In areas such as AML and KYC, even small improvements in data accuracy can make a big difference. You can reduce false positives, improve risk detection and strengthen compliance processes overall. - Create a clearer view of customers and counterparties
Many regulations depend on having one accurate view of a customer, counterparty or exposure. Matching and entity resolution capabilities help you connect fragmented records across systems with greater precision. That makes it easier to spot relationships, reduce duplication and avoid missing the links that matter most. - Make your controls easier to explain
Strong controls need strong visibility. Regulators expect you to explain how data is created, transformed and validated. To accomplish this, you’ll need data lineage and governance capabilities that help you document rules, transformations and controls clearly. That visibility makes it easier to answer regulatory questions and demonstrate confidence in your data processes.
Compliance is only part of the value
Better data quality does more than support compliance. When your data is trusted, you can make decisions faster, reduce manual effort and improve the experiences you deliver to customers. What starts as a regulatory requirement can quickly become a business advantage. In other words, data quality does not just help you stay compliant. It helps you work smarter and compete more effectively.
As regulation evolves, organizations need to see data for what it is: the foundation of compliance. By identifying critical data elements, setting clear quality standards and monitoring data continuously, you can turn data quality into a stronger control. With the right tools in place, that control can scale with your business.
Data quality is no longer just a supporting function. It is becoming one of the clearest ways to build trust, improve resilience and turn compliance into competitive advantage.
Get in touch with a data expert to explore how Experian can help your organization.
At its core, the financial industry is a data business. We find that 86% of financial institutions see data as an integral part of forming business strategies. Banks and other financial service firms have always relied on data to make informed decisions. From lending money and approving credit, to managing investments, business leaders rely heavily on information gathered from data. Still, as the volume of available data grows exponentially every year, many financial institutions are struggling to best understand who their customers are and how to meet their needs effectively. The answer: Data enrichment. Data enrichment enables financial institutions to cater better to the needs of customers and make online banking more convenient while increasing efficiency through a tailor-fit user experience. Data enrichment is based on real-world data obtained from customers that explore more than what is stated on an application. Let’s take a look at what data enrichment is, its relevance to financial institutions, and the ways that data enrichment can help those in the financial sector make smarter business decisions. What is data enrichment and how can it help financial institutions? Data enrichment are the attributes appended into a database—so you can get to know who your customers are and what they care about. Enriching the data can ensure that financial institutions don’t overlook valuable customer attributes, such as age range, marital status, financial data, buyer propensity, and automotive data. Not only could these changes be critical in helping institutions identify whether a customer is a risk or a good fit as a potential client, but it enables institutions to personalize their messaging and offerings. Data enrichment can help banks increase their revenue as it improves customer service and enables them to make products relevant to customers based on their specific needs and desires. Utilizing data enrichment tools will allow financial institutions to take raw customer data, data that tends to be incomplete and unreliable, and turn it into an accurate and high-quality resource for better decision-making for marketing campaigns to loan approvals. Data enrichment gives the financial industry a competitive advantage Enriching your data is getting to know who your customers are and what they care about through appending insight to your existing records. With this insight, you can better understand your customers’ needs and help them achieve whatever financial goals they came to your bank or financial institution for. Data enrichment gives banks and others in the financial sector a competitive advantage in this age where organizations are pushing to be more data-driven. Financial institutions with enriched data have an edge over those who don’t because it enables them to: Know their customers deeper than competitors by identifying trends in customer spending habits, product usage, and lifestyle preferences. Further understanding of what leads people toward certain decisions (like opening new accounts) so that banks can focus on initiatives that drive results for both parties involved in the transaction Find opportunities to partner with tech companies and other financial institutions (banks, credit unions) for innovations that could lead to collaborative partnerships or joint ventures where each party can leverage each other’s strengths while helping themselves grow at a larger scale and increase their revenue. How to get started In the end, data enrichment is a powerful tool that can help companies of all sizes compete in this new data-driven world. Whether you’re a small startup or a large bank, it is important for everyone in the financial industry to make sure their data is working as hard as possible for them. Data enrichment is a great way to do just that: By taking raw information and turning it into meaningful insights that can help your business grow. As financial institutions continue their efforts to make sense of their data and develop more sophisticated ways of analyzing it, we expect that enrichment will begin playing an even bigger role in this process. If you haven’t started enriching your data, connect with our team and learn how Experian can help you get started. Speak to a data quality expert today
With cyber threats rising and consumer privacy at the forefront, organizations must prioritize protecting sensitive information while navigating the complexities of data privacy and compliance. Data compliance is a significant aspect of keeping your customers’ data safe, as it fosters trust and transparency in the current digital landscape. What is data compliance? Data compliance makes sure that an organization adheres to all legal, regulatory, and operational standards regarding data collection, storage, processing, and management.Overall, data compliance involves: Adherence to Laws and Regulations: When handling sensitive data, organizations must follow relevant data compliance standards, such as the GDPR in the European Union or the CCPA in the United States. Responsible Data Handling: Data compliance verifies that data is collected, stored, and processed safely, preventing unauthorized access or misuse. Mitigating Risks: Businesses reduce the risk of data breaches that can lead to financial penalties and reputational damage. An organization needs strong data governance for effective compliance and data protection. Data governance is the framework for checking that data meets business standards as it is entered into systems by focusing on people, processes, and technology. Data compliance is also integral to cybersecurity and protecting personal information through data security practices, such as conducting regular audits and assessments to find potential risks. Why data compliance matters Data compliance is a strategic necessity that can impact a business’s reputation. Not following data protection laws can result in severe legal and financial repercussions. Regulatory bodies can penalize and fine organizations mishandling data, potentially compromising financial stability. Non-compliance can inflict lasting reputational damage, as data breaches or lapses in data handling erode consumer trust and diminish an organization’s credibility over time. Embracing robust data compliance measures yields significant benefits for organizations. Implementing stringent security protocols can dramatically reduce the risk of data breaches and unauthorized access. This approach secures sensitive information and elevates operational efficiency by standardizing data management processes. Prioritizing data compliance also builds customer trust, as individuals are likely to remain loyal to organizations committed to safeguarding their personal information. Key data compliance regulations and standards Data compliance regulations and standards protect sensitive information and ensure robust data security. One example of these data compliance regulations is the Data Protection Act from the United Kingdom. Other examples of data compliance regulations include: GDPR (General Data Protection Regulation): Sets a global benchmark for data privacy, enforcing strict guidelines on data collection, processing, and storage. Enacted by the European Union, it reinforces individual privacy rights regardless of an organization’s geographic location. CCPA (California Consumer Privacy Act): A U.S. regulation that enhances consumer control over personal data by making businesses transparent about their data practices. It guarantees consumers understand how their information is used, shared, and stored while promoting higher accountability in data management. HIPAA (Health Insurance Portability and Accountability Act): A data compliance regulation protecting patient information by establishing strict protocols for handling medical records and personal health data. This set of data compliance regulations enforces administrative, technical, and physical protections so that patient information is confidential and secure. PCIDSS (Payment Card Industry Data Security Standard): A critical framework for securing financial data in payment transactions. It enforces network security, encryption, and regular monitoring to prevent breaches and fraud for secure payment processes. ISO 27001 (International Standard for Information Security): An international standard supporting a structured framework for managing information security. It helps organizations establish, implement, and improve an Information Security Management System (ISMS) while promoting ongoing risk management and resilience against evolving threats. These data compliance laws and standards address everything from consumer privacy and healthcare data protection to the secure processing of financial transactions. Common challenges in data compliance Navigating data compliance presents several challenges for organizations, such as: Managing secure and compliant data storage and access: To protect their storage and access, organizations must implement solutions that protect sensitive information and ensure that only authorized personnel can access it. Maintaining data accuracy and integrity: Errors or inconsistencies in data collection, storage, and access can compromise reliability, decreasing data integrity and compliance. Managing consent and user rights: Organizations need robust systems to promptly address requests for data access, correction, or deletion. Organizations must balance and uphold data security and regulatory adherence when developing processes aligning with data compliance standards. Best practices for achieving data compliance Achieving enterprise data compliance requires a multi-faceted strategy centering on establishing robust data governance frameworks, maintaining high data quality, and implementing continuous audits and monitoring. Data governance frameworks: Effective data governance begins with defining clear policies and assigning specific responsibilities to employees so everyone understands their role in safeguarding data. This structured approach standardizes data management practices across the organization and aligns operations with regulatory compliance data management. Data quality: Verifying that data is accurate, consistent, and complete minimizes errors that could lead to breaches or misinterpretations. Regular audits and monitoring: Regular audits and risk assessments reinforce this framework by providing ongoing oversight, identifying potential vulnerabilities, and enabling proactive adjustments to data compliance strategies. Together, these best practices form a comprehensive approach that protects sensitive information and demonstrates a firm commitment to data integrity and security. Future trends in data compliance regulations The future of data compliance is poised for significant evolution as emerging laws and evolving regulations reshape global and regional standards. Governments worldwide increasingly focus on tightening data privacy and security mandates, responding to technological advancements, and heightened public expectations for transparency and accountability. This trend could result in more comprehensive and harmonized legal frameworks addressing the complexities of cross-border data flows and digital innovation. Another trend in data compliance regulations is integrating artificial intelligence and automation, which is transforming how organizations manage compliance. AI-driven compliance tools streamline processes with real-time monitoring, risk assessments, and automated reporting, enhancing the accuracy and efficiency of compliance efforts. As these technologies become more sophisticated, they let businesses adapt swiftly to regulatory changes and mitigate potential risks proactively. How Experian helps with compliance Robust data compliance is a regulatory necessity and a strategic asset that can protect your organization from legal risks while further developing customer trust. We cutting-edge solutions, empowering your organization to maintain high-quality, compliant data. Our advanced compliance automation and reporting capabilities allow you to streamline your regulatory compliance data efforts, reduce operational risks, and focus on strategic growth. Contact us today to learn how Experian Data Quality can help you with your data protection compliance strategy and protect your business for the future. Connect with an expert to get started
Major consumer credit bureaus require data furnishers to submit consumer credit information using the Metro 2® reporting format, the industry standard for credit reporting. While the Metro 2® format is designed to promote accurate and consistent reporting, maintaining high-quality data and meeting evolving compliance requirements can still be challenging. Many organizations rely on manual processes to review, validate, and reconcile Metro 2® reporting files. These workflows can be time-consuming, resource-intensive, and increase the risk of errors. At the same time, consumers are more informed than ever about their credit reports and are more likely to identify and dispute inaccurate information, making data quality a business and compliance priority. Poor data quality can lead to reporting inaccuracies, increased operational costs, slower issue resolution, and greater regulatory risk. It can also reduce confidence in analytics and make it more difficult to deliver a positive customer experience. If you’re looking to simplify your Metro 2® reporting process while maintaining FCRA compliance, focus on three key areas: Accuracy Automation Resourcefulness Data accuracy When data furnishers, like you, prepare their Metro 2® reporting files, it’s important that they be as accurate as possible. Incorrect data means inefficiencies across your processes which will negatively impact your resources and ability to quickly respond to customer dissatisfaction, disputes, media backlash, and regulators. In the credit reporting lifecycle, as files are sent to the Credit Reporting Agencies (CRAs), the furnishers are receiving information in return to reconcile discrepancies and rejects, among other data points. All this information can be overwhelming to manually aggregate, address, and appropriately update. More importantly, manually managing your data limits your ability to build risk controls. This is where automation becomes your best ally. Data automation Experian’s DataArc 360™ powered by Experian Aperture Data Studio is a data quality management tool that automates the data quality process to help data furnishers comply with credit reporting industry standards and the Fair Credit Reporting Act (FCRA). This is a tool that helps your organization build risk controls. DataArc 360™ is a powerful solution that removes manual processes and enables you to proactively manage your reporting analysis. It will flag any discrepancies against a pre-built set of rules and measure the results through an interactive dashboard where a user can even drill down to account level details for root cause analysis. In addition, furnishers can also run the analysis as often as desired to monitor trending statistics, as well as adapt or create new rules to enhance the process further. With this ability, DataArc 360™ makes it easy to monitor consumer credit reporting and gives you confidence that a solid process is in place to enhance data accuracy. The tool brings discovery in-house to address data quality concerns proactively while helping to reconcile any discrepancies post-submission from the CRAs. Resourcefulness DataArc 360™ can help you stay ahead of the game when it comes to your data integrity. The tool helps you make the most of your resources, allowing your staff to focus on more strategic efforts like understanding risk appetite and tolerance. Homepoint, a DataArc 360 client, saved their team 50 hours per month by automating and operationalizing their data with our tool, boosting productivity, and increasing data accessibility. Jill Cannon, Senior Director of Default Administration at Homepoint, says, “DataArc 360 is accessible to everyone and anyone within the business who wants to see credit reporting and understand exactly what the current status is. It allows management to sign in and view dashboards to immediately see the percentages of loans that are passing, the rules that are failing and at what rate and, then report on this to our leadership in a way that just wasn’t possible before.” When you streamline and automate your Metro 2® analysis with Experian, you will see: Accuracy in your credit reporting. Advanced analytics tools that can assist during regulatory agency visits. Alignment between your credit reporting and larger data strategies like data quality or data governance. With a platform that hosts results, you can easily share information and collaborate across your organization with risk, fraud, anti-money laundering, sales, marketing, and compliance. More accurate reporting also leads to a better customer experience, and ultimately, to greater customer loyalty. Are you interested in easing your Metro 2® reporting quality analysis process? DataArc 360™ can help. Connect with a data quality expert today:
