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.
The average person receives around 605 e-mails and 16.8 piece of mail per week—many of these are from companies and businesses that use email and direct mail as channels of communication.1 Driving marketing efforts through both channels can generate more leads, build relationships with consumers, and increase business sales. This success starts with the right data. Trustworthy email and address data are essential to competitive email and direct mail marketing campaigns. Without it, there’s a chance you could be sending email or mail to invalid mailboxes, costing you unnecessary mailing fees, risking your status as a unreputable sender, and even impacting the customer experience. Now, we know direct mail sounds old fashion. In our digital world, it would be easy for companies to assume that direct mail is an outdated form of marketing that is being replaced by e-mail marketing. In reality, both direct mail and email are still being used in today’s marketing landscape, and they each are a unique form of marketing with different benefits and costs. Let’s take a look at what direct mail and email could mean for you—and where data quality fits in. Direct mail definition Direct mail is when a company connects with its customers by sending them content through the mail. Direct mail can come in the form of: Flyers Brochures Catalogs These are delivered to a potential customer’s home. The goal is to identify a need the customer may have and show how your company can satisfy that need. Direct mail can help: Educate customers Build customer relationships Offer sales promotions to incentivize purchases. Email definition E-mail is a form of direct marketing where companies can connect with customers through electronic mail. These e-mails can include: Newsletters Information about products Sales promotions Email is a less intrusive form of marketing that can help build customer relationships in a quick and easy manner. Differences between direct mail and email Direct mail pros With direct mail, you can create targeted mailing lists to reach your key demographics and make them aware of your brand. By being able to reach these potential customers in such a personal way, you increase the chances of making a sale. Along with this, you can easily find the response rate of direct mail by tracking how many of the recipients used the coupon or promo code that was offered. To get the most out of your direct mail marketing and ensure high ROI, consider integrating an address verification solution into your tech stack. Not only will you know if your brochure is going to a commercial or residential address, but you will feel confident that it’s landing on the right doorstep. Direct mail cons While direct mail is very personal, it can be costly, and the response rates could be low. If you have the wrong address for a target consumer, and you accidentally send their direct mail to someone else, you have lost an opportunity to connect with that customer. On top of this, if you correct their address after sending it, you can incur an address correction fee. This is where contact data validation software can help. These unnecessary costs can add up overtime for your business. A way to avoid this issue is by integrating an address validation software, just like the one we mentioned above. This tool can validate customer addresses to help prevent spelling errors, inaccurate formatting, and mismatched city and postal code data. Email pros Email marketing is a cheap and easy way to reach your target customers. Email marketing has a quick turnaround time, with the first responses occurring around 48 hours after the email is sent. These responses can also be easily tracked by tracing how many recipients opened it, clicked on the links, or sent it to someone else. This kind of feedback can help you understand how to reach your audience better. Similar to direct mail, you want to make sure you are getting the most out of your email marketing campaign, and to do so, you want to validate your email list with an email verification software. That way, you know you are reaching the right customer and you remain a reputable sender. Email cons One issue with email marketing is that customers can feel annoyed with the sheer volume of emails they are receiving, and they may ignore many of these brand emails. There can also be issues if you don’t have the right email address. If your company sends too many emails to wrong or inactive email inboxes, you may be placed on a list of unreputable senders, which can prevent you from being able to send e-mails. To avoid this, integrate an email verification solution. This will validate customer emails to make sure you are reaching the correct inboxes. Using direct mail and email together Nowadays, using a single channel to reach customers isn’t good enough. Many companies are now taking a multi-channel approach to marketing, where they use several channels to reach target consumers. Having several channels, like email and direct mail, can help spread awareness for your brand and allows for more personalized selling. Multi-channel marketing allows your company to reach a single customer several times. You can track the customers behavior at the first touchpoint, and then customize the message at the second touch point to match their behavior. This creates a customized experience for your consumer, which can improve their experience with your brand and increase the chance of closing a deal with them. With around 72 percent of consumers preferring this kind of integrated marketing approach, having a multiple channels can help you build and retain a loyal consumer base.3 With the correct customer contact data, like email, address, and phone data, you can ensure you are effectively reaching your customers while seeing high return on investment on your multi-channel marketing campaigns. Interested in learning more? Speak to a data quality expert today:
As organizations collect more customer data than ever before, one question continues to come up: should data validation be handled manually or automated? For small datasets, manual validation may seem like the simplest option. But as data volumes grow, relying on people to identify and correct errors becomes increasingly time-consuming, costly, and difficult to scale. When deciding between manual and automated data validation, it’s important to consider both the short-term effort and the long-term impact on data quality. Manual data validation Pros: Works well for small datasets Gives teams complete control over validation rules Doesn’t require new technology Cons: Time-consuming and resource-intensive Prone to human error Corrects issues after bad data enters your systems Can impact customer experiences before errors are discovered For organizations with limited data or one-time cleanup projects, manual validation can be an effective solution. However, as data volumes increase, maintaining accuracy through manual processes alone becomes increasingly difficult. Automated data validation Pros: Validates large volumes of data quickly and accurately Reduces manual effort and operational costs Applies consistent validation rules across systems Supports real-time validation at the point of data entry or scheduled batch processing Helps prevent data quality issues before they affect your business Cons Requires implementation and integration with existing systems Involves adopting new technology and processes While implementing an automated solution requires upfront planning, the long-term benefits often outweigh the initial investment. Automated data validation helps organizations maintain accurate, reliable data at scale, allowing teams to spend less time correcting errors and more time using data to drive business decisions. For many organizations, manual data validation is no longer practical. Customer data is constantly changing, and maintaining its accuracy requires more than occasional cleanup. Automated data validation helps ensure data is accurate from the moment it’s collected, giving teams greater confidence in the information they use every day. Ultimately, the question isn’t whether to automate data validation—it’s whether your current process can keep pace with the volume, speed, and complexity of today’s data. Learn how Experian helps organizations improve data quality with automated data validation solutions.
High-quality data provides an innumerable amount of benefits for businesses, but there is one hangup that often gets in the way. By addressing the challenges of duplicate or inaccurate records head-on and developing a strategy for success, businesses are able to create what is called a golden record, one of the biggest achievements in the world of data-driven businesses. In achieving a golden record, businesses can build stronger relationships with customers and enjoy all-around greater success. All it takes is a strategic approach and the proper commitment. What is a golden record? A golden record is a guiding light in the world of Master Data Management (MDM), an achievement that every business wants to accomplish for each entry in their database. A golden record is a single data point that provides all of the important information about a customer, client, or resource with total accuracy. For example, a golden record would provide correct address information, an email, a phone number, and more, all in a single data entry. In MDM solutions, a business is responsible for connecting data from multiple areas and systems and is tasked with combining that information into a single record. Businesses that collect data from multiple sources or store data using multiple databases usually have to put extra thought into creating a golden dataset. Businesses that achieve a golden record are better able to understand their customers and clients, build relationships, and take actions that generate more overall success. Why is a golden record important? Although it is always the goal to create a comprehensive and accurate profile for each individual customer, it is often easier said than done. There are many issues that can occur during data collection methods that harm your chances for a golden record. The golden record provides a single customer view that allows businesses to better understand each customer. By achieving a golden record for as many customers as possible, your business is more informed and able to use data insights to strategize on moves for success. In the process, you will also be able to maximize your ROI on marketing tactics. Despite the awareness of the benefits of a golden record, many businesses fail to achieve it and end up with several cases of the following scenario: Last NameFirst NameEmailPhoneAddressSmithRobertrsmith@email.com(555) 200-1234418 Maple St. Port Claire, RI 76068SmithRobrsmith@email.com(555) 200-1234418 Maple St. Port Claire, RI 76068 The information here is largely the same, except for the name and a typo in the ZIP code. One small difference can create an entirely separate data entry, treating the entries as two separate people. This difference causes ambiguity and confusion, preventing your business from having an accurate picture of the customer. Even worse, if you base your marketing or communications on the wrong entry, your business might not reach this customer at all and waste valuable time and resources in the failed attempt. Altogether, this confusion makes it difficult to reach customers and requires time and energy for your team to find and correct duplicate or inaccurate records. Unfortunately, this issue is all too common in the world of data-driven businesses. On the bright side, businesses are far from powerless in their ability to take steps to reduce duplicate entries and achieve a golden dataset. How to implement Master Data Management solutions Achieving a golden record in Master Data Management requires a comprehensive approach to data management with thought-out systems for collecting, verifying, and managing data. There are three key ways that you can begin implementing an effective MDM solution. Merge and match records Duplicate records are the biggest culprit for preventing businesses from achieving a golden record. When your database contains many instances of duplicate records, the best approach is to merge and match. MDM solutions are valuable in matching records based on the information that is provided. Given the above example, a system would identify that there is significant crossover between the two entries. Since the two entries have different information in the same field, the system will prioritize the field with the most reliable information and combine the records to create a single entry. In cases with multiple areas that are different, the system has to review the source for each data field. You can also specify whether the system should prioritize a single field. For example, if the first source is more accurate for the address and the second is more accurate for the first name, you can control which the system uses to complete the record. By combining and consolidating the data into one entry, the system creates a single golden record. Develop a cohesive data management strategy Of course, you can correct duplicate records after the fact, but why take that approach when you can prevent them from occurring at all? Developing a strong strategy for Master Data Management allows you to be proactive and keep duplicate or inaccurate records out of your database before they even enter. With hundreds of thousands of entries in your database, it is easy for the entries to get out of hand if not properly managed. As a result, you need to be forward-thinking and consider how you will collect and maintain quality data in a consistent manner. Your strategy will depend on your business’s specific needs and strengths. In developing your data management strategy, you should consider several questions: What information is necessary to create a golden record? How many data entry sources do you use? How are all data sources connected and integrated into the database? How often can your business utilize automatic merges? Who will review records for accuracy during merges? When can you use tools? And who will be responsible for manual intervention? A comprehensive strategy should include consistent standards for how data is collected, stored, and reviewed. It should also highlight who is accountable for reviewing data accuracy and how often. Use the proper tools One of the most vital components of a good strategy is data management tools. Data management tools will help you maintain high data quality by ensuring only quality and checking your data accuracy over time. Some excellent examples of useful tools include the data matching tools mentioned above, batch cleansing tools, data record apps, and real-time verification toolsBatch cleansing can be used to comb through a database and highlight duplicate records, either on a consistent schedule or on demand. Meanwhile, real-time verification tools help to keep your database free of inaccurate email, address, or phone number records, as they prevent you from collecting inaccurate data at all. By preventing errant information from entering your database, you reduce the chance of duplicate entries that harm your database.Even better, data management tools help you save time and resources by doing the work for you. As a result, your staff can focus on other ways to boost your business operations. Achieve the golden record in Master Data Management A golden record is much more than just an achievement–it is a precious resource for businesses to leverage. With a golden record, your ability to reach your customers skyrockets as you gain better information through a complete golden dataset. However, you still need an effective, proper strategy. To learn more about how to achieve a golden record in Master Data Management, contact us at Experian Data Quality. Our comprehensive suite of data quality and data management tools will help your business maintain a high-quality database free of duplicate entries. Explore our tools for yourself and discover how you can get started with achieving golden records in your database. Connect with a rep to learn more:
