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6 Steps to Achieve Data Quality and Meet Compliance Standards

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The financial services industry continues to face mounting pressures to meet the highest standards of data reporting and accuracy.

New regulations and mandates are introduced regularly, impacting the way companies do business. And a more credit-educated consumer base is seeking insights into their own credit data, providing a separate second of eyes that demand accuracy.

Not only has the Fair Credit Reporting Act (FCRA) set requirements on dispute investigation and response, but the Consumer Financial Protection Bureau (CFPB) is also paying close attention. Recent announcements indicate the CFPB wants more information about the credit eco-system to gain more data about consumer disputes.

According to the CFPB, it’s a joint problem – “the NCRAA’s, data furnishers, public record providers, and consumers all play roles which affect the accuracy of the information with credit reports.”

And it’s not just the big banks that are being targeted with fines. The CFPB has made it clear it will also direct attention to certain nonbanks and financial products.

In today’s data-driven environment, there are roughly 12,000-plus data furnishers, resulting in more than one billion pieces of information being updated on a monthly basis. Over 220 million consumers have some form of credit information attached to them, and transactional data is flowing all the time.

Fail to update and a furnisher will quickly see flaws in their reporting. In fact, a recent study revealed an estimated 2.1% of contact info goes bad if unattended for more than one month.

Clearly, achieving data quality is an ongoing investment for any organization, but companies often lack a clean plan.

Some data furnishers fail to report, or elect to report to just one bureau, even though providing better data will result in a more complete and accurate credit profile.

So how do you tackle the challenge of data quality? Organizations should consider implementing these six steps:

  1. Review data governance.
  2. Correct errors in data submissions.
  3. Complete an audit of data submissions.
  4. Evaluate disputes and resolutions.
  5. Compare data to peers and the industry.
  6. Review existing policies and processes.

Follow these steps and your organization will earn a reputation among both regulators and consumers for clean, credible data. Plus, the investment in better data will reduce the need to resolve future disputes and fines.

To learn more about meeting your FCRA responsibilities and best practices around data quality, check out our on-demand webinar or data integrity services site.