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Maximizing data quality across your organization

Ensuring the quality of reported consumer credit data is a top priority for regulators, credit bureaus and consumers, and has increasingly become a frequent headline in press outlets when consumers find their data is not accurate.

Think of any big financial milestone moment – securing a mortgage loan, auto loan, student loan, obtaining low-interest rate interest credit cards or even getting a job. These important transactions can all be derailed with an unfavorable and inaccurate credit report, causing consumers to hit social media, the press and regulatory entities to vent it out.

Add in the laws and increased scrutiny from the Consumer Financial Protection Bureau (CFPB), and Federal Trade Commission (FTC) and it is clear data furnishers are seeking ways to manage their data in more effective ways.

At Vision 2016, I am hosting a session, Achievements in data reporting accuracy – maximizing data quality across your organization, with several panel guests willing to share their journeys and learnings attached to the topic of data accuracy.


Our diverse panel features leaders from varying industries:

  • Jodi Cook, DriveTime
  • Alissa Hess, USAA Bank
  • Tom Danchik, Citi
  • Julie Moroschan, Experian

Each will speak to how they’ve overcome challenges to introduce a data quality program into their respective organizations, as well as best practices around assessing, monitoring and correcting credit reporting issues. One speaker will even touch on the challenging topic of securing funding for a data quality program, considering budgets are most often allocated to strategies, products and marketing directly tied to driving revenue.

All lenders are advised to maintain a full 360-degree view of data reporting, from raw data submissions to the consumer credit profile. Better data input equals fewer inaccuracies, and an overarching data integrity program, can deliver  a comprehensive view that satisfies regulators, improves the customer experience and provides better insight for internal decision making.

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To learn more about implementing a data quality plan for your organization, check out Vision 2016.