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.
Our team recently attended MRC San Diego 2025, hosted by the Merchant Risk Council, the go-to event for fraud, payments and risk in digital commerce. Bobby Colombi, our Director of Strategic Accounts, came back with some powerful takeaways that are already shaping conversations with our clients and partners. Here’s what stood out: 1. AI is reshaping the fraud landscape, both as a threat and a tool Agentic AI refers to autonomous systems that can act independently, make decisions and carry out tasks without constant human input. Fraudsters are now using these AI agents to launch coordinated, human-like attacks at scale. These agents can mimic real user behavior, bypass traditional security checks and even adapt in real time, making them incredibly difficult to detect and stop. At the same time, businesses are also turning to AI to fight back. AI is being used for fraud detection, data enrichment and behavioral analysis, helping teams spot anomalies and suspicious patterns more efficiently. However, many companies still rely on manual review for final decisions, which can slow down response times and leave gaps in protection. The takeaway? AI is no longer just a tool. It’s a player. And in this new era, staying ahead means understanding how both malicious and defensive AI are evolving. 2. “Identity is the new defensive perimeter” This quote from keynote speaker Gordon Sheppard, Consultant of Digital Identity and Authentication at Sage West Associates, captured a major theme of the event. Bobby observed that identity verification gaps, especially in guest checkout, account takeovers (ATOs) and synthetic ID creation, are fueling e-commerce fraud. The solution is a risk-based, evolving approach to identity. Merchants must find the right balance between fraud prevention and customer experience, ensuring that security doesn’t come at the cost of revenue growth. 3. Traditional fraud prevention is no longer sufficient Static rules and legacy systems are struggling to keep up with today’s dynamic threats. Bobby emphasized the need for a multilayered defense strategy that adapts in real time. Fraud is evolving, and our defenses must evolve with it. 4. The rise of agentic commerce requires new standards and strategies Agent-driven transactions are emerging as a new customer class. Think AI agents making purchases or managing subscriptions on behalf of users. This shift introduces new challenges in fraud prevention, including: Intent verification (Did the consumer authorize the agent?) Dispute evidence Robust trust frameworks Bobby highlighted the need for industry-wide collaboration to define standards and guardrails that protect consumers while enabling innovation. 5. Fraud isn’t just a security problem. It’s a revenue problem. False declines cost merchants significantly, impacting both revenue and customer lifetime value. Subscription abuse is also on the rise, driven by poor cancellation flows and consumer expectations shaped by regulations like the FTC’s “Click-to-Cancel” rule (even though it was blocked in July 2025). Consumers are acting as if the rule is in place, working directly with banks to cancel, bypassing merchants and triggering chargebacks. Bobby’s tips: Humanize cancellation flows. Communicate before renewals. Automate to reduce disputes and protect brand reputation. Final thoughts Fraud prevention is no longer just about stopping bad actors. It’s about enabling trust, protecting revenue and delivering seamless customer experiences. As e-commerce continues to evolve, so must our strategies. The future belongs to those who adapt — with AI, identity innovation and agentic commerce readiness. Want to see how Experian helps clients stay ahead of fraud? Contact us to learn more
Explore the biggest takeaways from MRC Vegas 2026, from emerging fraud threats to the future of digital payments and commerce.
Explore how data quality impacts AI performance and learn how to reduce AI data risk for more accurate, reliable business decisions.
