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.
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Insurance companies face new challenges as they compete in the digital age. Consumers can research rates, contact employees and even sign up for service without meeting agents face-to-face or calling the company’s phone number. This can be a blessing because it provides consumers with the convenience to sign up through their preferred channels when they find the best deals. However, in a competitive market, insurance companies must be able to reach new consumers and gain enough information to meet their needs or risk falling short. With a comprehensive data management strategy and effective data collection tools, insurance companies position themselves to better meet customer needs and demonstrate a strong commitment to developing customer trust. Understanding how your company can leverage consumer data can set you apart from the competition What data do insurance companies collect? Insurance companies collect a variety of data from various sources to better serve customers and respond to their needs. Like other industries, insurance companies collect contact information during customer interactions for the sake of being able to stay in touch with customers and provide them with valuable information and updates. However, insurance companies also have unique, industry-specific data collection methods. Data collection has become especially useful at the scene of an accident or incident. Many companies use mobile apps that allow consumers to report the details of an incident. These reports can collect information like contact details, time and date of the incident and location details. This data is valuable for recognizing trends, understanding individual incidents and properly addressing claims. The importance of data in insurance When insurance companies focus on their data collection tactics, they can be certain they aren’t losing any prospects in the pipeline and are providing their customers with the best product options. Data collection for insurance companies provides the ability to gain a single customer view, a complete data profile of a customer and their interactions with your company. This profile, when developed with quality data, provides a useful overview that can inform future interactions and potential ways to reach the customer. However, companies that want to leverage these capabilities must be certain to use data collection tools like address management to perform email verification at the point of entry. Improved data collection processes and better analysis tools allow companies to enhance the quality and utility of their data to better serve customers. With reliable data, companies can focus on using it to find new potential clients, promote new products and even improve the customer service experience for existing customers, demonstrating a commitment to valuing customers on a personal level. Establishing a more structured method for data collection and handling can also improve information security and help insurance companies avoid circumstances such as those that recently affected the Investment Industry Regulation Organization of Canada (IIROC), where the organization announced that an employee lost a personal device that stored 52,000 customers’ personal information. Because insurance companies deal with such valuable and personal customer information, a secure data management system with security tools is necessary. Maintain high-quality data While insurance providers once relied on staff members to type in customer data, companies are now saving time and money by supporting self-service, the source adds. Unfortunately, this can also lead to a higher error rate if the proper tools are not installed to flag inaccurate or incomplete fields before they are saved and processed. Issues like typos, human error and improper formatting are prevalent during the data-entry process. Insurance data collection tools are highly valuable for maintaining high-quality data, flagging data quality issues and preventing incorrect or incomplete data from entering the database. Incorporating the correct measures at the point of entry is one way to eliminate mistakes when larger volumes of data are being processed. Another strategy involves deploying a system that regularly cleanses information in its flow throughout departments. Data cleansing tools like email address verification are helpful at the point of entry, while tools like data monitoring regularly check the quality of stored data. These tools prevent incorrect information from entering databases and correct mistakes when it does. Verification methods are particularly important when firms are supporting online channels, which are very common sources of data entry errors. Improve your insurance data quality Effective data collection and data quality practices play a critical role in helping insurance companies meet customer expectations, improve operational efficiency and remain competitive in a digital marketplace. By implementing tools that validate, standardize and monitor customer data throughout its lifecycle, insurers can reduce errors, strengthen security and create more personalized customer experiences. Solutions such as address verification, email verification and ongoing data quality monitoring help ensure customer information remains accurate, complete and reliable. Investing in a strong data quality strategy enables insurers to make better decisions, streamline claims and underwriting processes, and build lasting customer trust. Fill out the form below to get started:
