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.
Learn why accurate employee data is essential for HR and how address verification helps keep employee records current and compliant.
Learn how to choose the best address verification software to improve data quality, reduce delivery errors, and maximize your business ROI.
Holding onto data is almost useless for a business if it does not have a proper data management strategy. A robust data management strategy relies on a methodical, step-by-step approach—much like how you’d approach building a house. We’ve used this analogy many times here at Experian Data Quality, but that’s only because it makes a lot of sense when referencing data standardization. Data standardization is but one step to building a good data management strategy, but it is a fundamental step in making your data actionable. Just as a solid foundation is essential for a strong house, data standardization is necessary to build a strong data management program. As a result, it is in your best interest to invest in a data standardization system. Data standardization allows organizations that strive to be data-driven to make decisions quickly and efficiently. What is data standardization? Data standardization is the process of transforming or manipulating data into a consistent format. As businesses collect data, the information most likely settles into multiple, disparate systems, all of which may have slightly different rules and formats for how the data is stored. These small differences can result in misunderstandings and misinterpretations of your organization’s data. Inconsistent data leads to distrust, second-guessing, and time lost completing checks to verify that the conclusions made off that data are actually correct. In a data-driven business, time will be far better spent acting on data than manually verifying and reformatting it. Standardization takes manual checks out of the equation. With the right data standardization tools, you can spend your time using your data rather than fixing it. How does data standardization work? The business data standardization process takes data from multiple disparate sources and, based on rules you define, transforms it into a consistent, usable format. It gets rid of anomalies and outliers, so that you can identify errors in your data and make it easier to analyze. Due to differing requirements across different systems, along with typos and human error, the data that flows into your organization comes in a variety of formats. Using multiple data entry systems can lead to inconsistent capitalization, punctuation, obscure acronyms, alpha-numeric characters living in fields they shouldn’t be, and so on. Data standardization tools eliminate these inconsistencies and help you define how data should appear in your database. Unlike data cleansing, which periodically corrects and eliminates errors in data, data standardization is an ongoing process to connect and sync formatting across multiple data entry systems. Data standardization is helpful for properly formatting: Country and state abbreviations Email addresses Company names Addresses Common typos and mispellings Phone numbers How does data standardization benefit my business? Data standardization is crucial for a data-driven business. Any business can store data, but clean, clearly formatted data that can inform business operations will set a business apart. The advantages of data standardization allow your business to do the following: Improve data accessibility Data is most effective when it is accessible to as many people in an office as possible. When data can be easily shared between staff members and departments, businesses are more efficient in decision-making and developing action steps. Consistent data allows everyone to be on the same page at all times without needing to reconsider or reformat data. Save time and money Second-guessing your data has consequences. The need to manually verify and correct data uses valuable time that could be spent making decisions and taking action. Data standardization confirms that your data is formatted consistently regardless of which system was used to collect it, and consistent data means you can trust your investments. Make more informed decisions Data that follows a common format is easier to interpret, sort and analyze. Easy-to-interpret data allows you to recognize trends and gain further insight into your customer base, allowing you to better informed decisions as a result. When you make data-supported decisions, you are able to strategically target your spending and investments, providing you with a higher return. Reach your customers Standardized data plays a key role in reaching new and previous customers. Consistent formatting for data like email addresses and postal addresses ensures that you can reach your customers through targeted marketing campaigns. With reliable data, you position your campaign to be as successful as possible and do not waste money sending to incorrect or improperly formatted addresses. Why should my business standardize data? Ultimately, standardized data increases efficiency and potential. If you’re still in need of convincing, I’d be happy to share a personal use case. My organization relies on a marketing automation platform, a CRM, and Google Analytics, in addition to more platforms that all collect and store data. This data is crucial for business-wide forecasting and projections. As we strive to gain insight from our data, it is imperative that everyone has a standardized view and understanding of the data being used to make these decisions. Unstandardized data would be a nightmare in these processes, leading to confusion between departments and wasted time spent manually converting data. It is necessary that everyone in the business is on the same page and is able to easily interpret and analyze data, otherwise, data is more of a burden than a value. If you’re undergoing a data migration or modernization project or if you’ve been charged with cleaning up your customer database before initiating a loyalty program or marketing initiative, data standardization is a non-negotiable first step in the process. Data is one of the most important assets businesses hold today. It can either empower your organization to connect with new customers and reach new heights or be a deadweight that wastes time and drags your team down. I think the choice here is clear. Standardize your data for a higher return on investment Why run the risk of letting inconsistent data sabotage your success? Treat your data as a strategic asset. Easy-to-interpret and reliable data is invaluable for decision-making, systems efficiency and building customer connections. Standardization is the key to maximizing its potential and seeing higher gains from your data. At Experian, we can help you standardize your data to increase its value. Fill out the form to learn more:
