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4 way you can identify credit reporting issues using data quality

As financial institutions digitally transform, credit reports become more accessible, giving consumers more visibility into credit history—including any potential errors. Customers may report the errors and financial institutions must investigate and fix the issues, if appropriate, which creates more obstacles for both parties and, in some cases, putting the customer relationships at risk. Credit report errors has the potential to result in loss of revenue or non-compliance penalties associated with the Fair Credit Reporting Act (FCRA). 

Is this sounding familiar? We’re here to help you identify possible credit reporting errors using trustworthy data.

As financial institutions digitally transform, credit reports become more accessible, giving consumers a more visible into credit history (including any potential errors). Customers may report the errors and financial institutions must investigate and fix the issues if appropriate (creating more work for both parties and in some cases putting the customer relationships at risk). Credit report errors has the potential to result in loss of revenue or non-compliance penalties associated with the Fair Credit Reporting Act (FCRA).

In the last 10 years, financial institutions have paid up to $18 million in legal damages for consumer credit reporting errors and deficiencies in their data reporting policy and procedures.1 As customer and FCRA expectations for accurate credit reporting have evolved, it’s important to think about leveraging data quality practices to catch errors early on and to minimize risk of customer disputes as a result of data quality issues. We have tips that can help you get a handle on your data quality and improve the accuracy of your credit reporting process.

We have tips that can help you get a handle on your data quality and improve the accuracy of your credit reporting process.

1. Keep accuracy top of mind.
In our latest Global data management report, 85 percent of organizations see data as one of the most valuable assets to their business. Those same organizations also say 28 percent of current customer/ prospect data is suspected to be inaccurate in some way. The accuracy of your data can be the reason why risk of critical errors could lessen when data quality control checks are put in place. In turn, giving you the chance to streamline processes and improve customer experience.

Steve Philpotts, general manager of Data Quality & Targeting divisions for Experian AUS, says in our 2020 Global Data Management report, “Poor data is often entangling entire organizations with crippling effects, preventing timely decision-making and negatively impacting customer experience.” If you equip your team with data quality management tools, it’s possible to minimize errors.

2. Proactively spot and fix errors.
Make sure your staff is equipped with the knowledge to spot and fix mistakes early on. For example, does your staff have a process or mechanism to proactively identify data reporting errors? Do they perform proactive root cause analyses or fix issues as they arise? Having internal training sessions and workshops on how to proactively identify and remediate errors can be immensely helpful in educating your staff, minimizing operational costs and identifying possible risks. 

These efforts could help transform your organization into a culture of data quality. Learn how you can drive a data culture with these tips.

3. Automation is your friend.
Automation can be seen as yet another tool for credit reporting. By building preprogrammed data quality rules into an automated workflow, you have the chance to identify errors and anomalies in large data volumes and monitor data quality. Not only can the right tools help you meet standards relative to reporting, like the Metro 2® format, but it also gives you the chance to help save your employees time and boost productivity.

According to our 2020 Global Data Management report, maintaining a high-quality data management strategy can help increase efficiency (60%), increase customer trust (44%), enhance customer satisfaction (43%), enable more informed decisions (42%), and save costs (41%).

4. Nip errors in the bud.
Think about turning to technology to help identify and fix errors early on. Data profiling tools, which offer visual dashboards and reporting capabilities, could provide immediate insight into your Metro 2® file. This can be used to identify and resolve reporting errors that could result in a dispute. With greater transparency and control over what you report to the credit bureaus, you have an opportunity to potentially reduce disputes resulting from data quality concerns, therefore spending less time reviewing and responding to them, and more time creating positive customer experiences and interactions.

Catching errors early in the credit reporting process can potentially save your institution a great deal of time. However, don’t feel like you’re alone in the process. A solution like DataArc 360™ can help you to spot mistakes early, can help you to improve accuracy, and can help you submit consumer credit data in alignment with the Metro 2® format.

Take a proactive approach to data quality and identify credit reporting errors today. Learn how DataArc 360 can help you.

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