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.
High-quality leads are crucial for sales success. These leads are not just names and phone numbers on a list; they represent potential customers who have shown genuine interest in a company’s products or services and are more likely to convert. By focusing on lead quality, sales teams can allocate resources more effectively, prioritizing leads that are more likely to result in successful sales, increasing the conversion rate, and enhancing overall productivity. Enter phone validation, the process of verifying that a phone number is accurate, active, and capable of receiving calls or messages. Ensuring it is correctly formatted and belongs to a legitimate carrier, and an essential tool in enhancing lead quality. This reduces time on invalid leads and improves the chances of successful communication and engagement with potential customers. Furthermore, phone validation can help identify fraudulent or duplicate entries, maintaining the integrity of the lead database. Benefits of implementing phone validation Implementing phone validation helps maintain a clean database, streamline operations, and maximize the return on investment in marketing and sales efforts. Here are some of the key benefits our clients have reported. Improved accuracy: By verifying the accuracy of phone numbers, including format, country code, and activity status, you can enhance your overall communication strategy, ensuring messages reach the intended recipients seamlessly. Enhanced efficiency: Phone validation allows you to quickly identify and eliminate invalid phone numbers from their contact lists, allowing sales and marketing teams to focus on leads with higher conversion potential. Efficient lead management translates to a more productive workforce and quicker response times to potential customers. Cost-effectiveness: Removing invalid or inactive phone numbers helps avoid costs associated with unsuccessful outreach attempts, allowing investment in quality leads with a higher conversion potential. Better targeting: Validated phone data enhances audience segmentation, enabling more effective targeting to specific customer profiles. With validated phone numbers, tailor marketing campaigns to specific demographics or customer profiles, ensuring messages are relevant and engaging. This enhances customer relationships, increases conversion rates, and drives higher revenue. Steps to implement phone validation Ready to onboard a phone validation solution into your existing tech stack? Keep these steps in mind when choosing the right solution for your business. Choose the right phone validation service provider: Consider deployment options, accuracy, reliability, user-friendliness, data freshness and advanced software. Integrate phone validation into your existing sales process: Prepare your CRM or sales software to incorporate the validation service, ensuring real-time verification without disrupting workflow. Train your sales team on the new process: Conduct comprehensive training to familiarize them with the technology and explain how it enhances lead quality and customer interactions. Experian Phone Validation offers simple and actionable validation responses, flexible deployment methods to suit any environment, and a user-friendly portal. Our phone validation solution covers 1500+ telecommunication providers in 240 countries and territories that standardize the format, add international dialing codes, and process data checks with telecommunication providers. In addition, we offer Phone Append that return the phone number associated with the user’s name and address and Reverse Phone Append that helps tie your existing phone data to other important customer data. In today’s competitive market, ensuring the quality of leads is crucial for any successful sales strategy. Phone validation stands out as a powerful tool in enhancing lead quality, improved data accuracy, cost efficiency, increased conversion rates, and improved customer engagement. By integrating phone validation, you can enhance lead generation processes, boost efficiency, improve client communication, and ultimately achieve higher success rates. Implementing this technology can help sales solidify a foundation for sustained growth and competitive advantage. Start today with a free trial of Experian’s Phone Validation solution. Reach out to one of our data quality experts to learn more about our comprehensive product suite. Fill out the form to learn more:
Data-driven decision making has become a necessity for the best businesses to stay on top of their daily operations and respond to areas for improvement. However, the quality of this data will greatly affect how useful it will be. Maintaining a high quality of data allows you to make decisions that improve customer relations and increase revenue. Poor quality data informs poor decisions and restricts access to customers while also using up time and resources to correct. Because of its capabilities, data should play a vital role in informing your business decisions. As a result, your business should have a clear and well-thought-out plan for how data will be collected, maintained and analyzed. Improving your data quality through careful data collection and maintenance should be a key part of your business operations and will set your business apart from the others. Benefits of improved data quality Improved data quality gives you a complete, accurate picture of your business and the customers you serve, allowing you to make more informed decisions that save time and money. High-quality data can be used to inform marketing campaigns that increase customer engagement, develop more trust in customer relationships and receive a higher return on investment in sales and marketing strategies. Access to accurate data takes the guesswork out of key business decisions, increasing efficiency and saving costs. By following just a few steps, you can set your business up for success with a clear plan for collecting more valuable data and using it to inform critical business decisions. Steps to improve data quality Many organizations manage data quality through separate departmental strategies, which can lead to inconsistent standards, duplicated efforts and less effective outcomes. Assigning a single data owner, such as a chief data officer, creates clear accountability for the quality, governance and standards of your data assets. Centralized ownership can also help align data quality initiatives with broader business goals and improve collaboration across departments. This central data owner should be supported by a team of data professionals—such as data stewards, data service officers, analytics professionals and data scientists—who can help enforce policies and promote the use of data to drive insights across the business. Implement proactive processes Improving your data quality requires careful and constant consideration to help your business maintain a strong and effective data strategy. Your business should develop a clear plan for using and analyzing data as well as keeping that data up-to-date and accurate. To improve and sustain your business’s data quality, you should carry out the following steps: 1. Develop your objectives Data quality means something different across different organizations. For some, it’s ensuring that customer contact data is accurate so that shipments are received in a timely manner. For others, it could be complete prospect profiles that help with marketing segmentation efforts. At its heart, data quality is about being fit for a desired purpose. In order to collect meaningful data, your business should have clear objectives in place for how this data will be used to improve decision-making and daily operations. When developing your objectives, you should consider the following factors: Your business goals How you measure progress towards goals What data you need from customers and clients How this data will be used and analyzed 2. Assess your current data Before implementing any data quality improvement plan, you need to understand where you stand today. Using the data quality sophistication curve, you can determine where you are related to data management efforts and what your next steps should be. There are four stages of sophistication your organization can fall into: Almost half of organizations today fall into the reactive or unaware stage, meaning there is a lot of room for data quality improvement. Data assessment should be a continuous process. The most successful businesses are constantly assessing the quality of their data and the effectiveness of their current data management plan. A constant reassessment of data allows a business to react to areas of concern and make improvements when necessary. 3. Cleanse your existing data Inaccuracies or inconsistencies in your data will harm your data quality and prevent you from using it for effective decision-making. Over time, data sets become riddled with out-of-date or incorrect information as customer data changes or information is improperly added to your database. Data cleansing is the process of correcting incomplete or inaccurate information, fixing formatting issues and more. Issues in your data set that require data cleansing include: Typos in data entries Incomplete data fields Inconsistent formatting of addresses or contact information Out-of-date contact information Duplicate data entries Addressing incorrect information in your database provides you with more confidence that your data provides an accurate picture of your customers and allows you to make appropriate business decisions as a result. There are a variety of tools available to help you cleanse your data. These tools include email address list cleansing, real-time address verification and more to help you cleanse your database of errors and also prevent incorrect information from entering at all. 4. Establish a data collection and management plan Because data collection issues are nearly inevitable, you should have a carefully considered plan in place to prevent these issues from arising and addressing them if they do. Being proactive with your data collection allows you to build a database of accurate and informative data instead of a database that needs to be fixed later. This will allow you to spend more time focusing on making decisions than fixing your data. Considerations for an effective data collection and management plan include preventing poor quality data from entering your database and consistently assessing the quality of the data you already have. Methods to include in an effective plan include: Using tools like real-time email verification to ensure accuracy upon entry Creating required fields on forms to avoid incomplete information Regular, periodic data cleansing to catch errors or outdated information Providing appropriate training to all staff involved in data assessment and decision-making Having a clear data collection and management plan will save your business valuable time and money correcting mistakes and allow you to be confident in using your data for strategic purposes. 5. Develop a plan for maintenance and improvement In order to maintain strong data quality and business growth, your business should have a plan in place to regularly assess the quality of data and its use in decision-making. Data-driven decision-making is a constantly evolving strategy. Effective plans for maintenance and improvement require consistent buy-in from everyone in the business. A data-driven business should foster a healthy culture of improvement where everyone is comfortable acknowledging when change is necessary. The ability to acknowledge when issues like flawed data collection methods or inconsistent data monitoring arise is monumental for business growth. Recognizing these issues and developing an appropriate response helps preserve your investments and will ultimately show greater returns than a business that is resistant to change. How to improve data quality for your business Implementation of data quality technology solutions across a company can streamline and unify data improvement efforts. This will result in the enforcement of consistent data standards across the organization, which means your data can be more easily used for advanced, comprehensive decision-making. To learn more about how to improve your data quality, download our paper on creating a strong and calculated data quality strategy. We also encourage you to try our email verification and data validation tools to strengthen your dataset. Contact Experian today to see how our tools and services can give you the help you need to collect, maintain and analyze accurate and meaningful data. Get help creating a data quality improvement plan
Protect sensitive patient information with HIPAA-compliant verification solutions that improve data quality and support compliance.
