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.
As a marketing or data professional, you may be familiar with the term “data profiling”. It is the process of examining a dataset to glean information about its contents. This can include statistics about the distribution of values, patterns within the data, unusual values or outliers, and in-depth analysis of its accuracy, or quality. Data profiling can be used to get a better understanding of your data, identify potential issues, and make sure that your data is clean and ready for analysis, or use. In this article, we’ll take a closer look at data profiling and examine some of the common use cases where it is most useful. Why profile your data? Before we explore some of the common use cases for data profiling, we’re going to look at the reasons why it can be so beneficial: Understand your data assets – it is extremely common for large and complex organizations to not fully understand their data landscape. Multiple territories and varying legacy systems that store data lead to data living in silos with varying levels of quality. A data quality report card helps you understand what data your organization holds and how it could be handled going forward. Boost accuracy and quality – by the very nature of the processes you undertake when profiling your data, you will spot inaccuracies and inconsistencies very quickly. Putting plans in place to fix these errors and long-term plans to prevent the same issue in the future will help you protect the value of your data assets. Improve decision-making – in the same way that data profiling can help you spot data inaccuracies, it can also ensure that your core data assets provide more reliable results when used for forecasting or planning. The old saying of “rubbish in / rubbish out” still holds very true and you want to give your organization the best chance to make the right decisions the first time round. Common use cases for data profiling Below, we discuss some of the use cases where data profiling offers the most value: Data governance is the key to sustainably unlocking the full value of the data you own – so that it can underpin your data strategy, not just today, but on a long-term basis. Customer segmentation is an excellent use case for data profiling and something that every organization should undertake. By segmenting your customer data effectively and building a single customer view you unlock a wealth of insights, such as, who is most likely to purchase your products, where you should put physical store locations, and what marketing channels will be most effective to grow your sales. Data migration is a complicated and time-consuming process, but one that is essential for large organizations to be proficient at. A common mistake is for organizations to rush the investigatory phase of their migration, shifting to data movement before a true understanding of the data is present. Data profiling is a crucial stepping stone in the migration process so that you know with supreme clarity what data you have, what will be moving, and where to. Talk to Experian about profiling your data Experian has a range of tools and services to help you profile your data. Our intelligent, self-service data quality and enrichment platform, Aperture Data Studio, can provide you with all the tools you need to understand and utilize your data assets. Get in touch today:
Discover how Experian prioritizes data integrity to deliver trusted insights and help businesses make confident, data-driven decisions.
See why data quality is critical for holiday success across retail, e-commerce, logistics, customer service, and financial services.
