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Three ways to justify a data management initiative at your financial institution

Jordyn Tetler Data quality

Financial institutions know data provides opportunity—opportunity to mitigate risk, comply with regulations, innovate operations, and understand customers on a deeper level. But, do you know not all data is trustworthy?

Data is only as good as the quality behind it. The saying ‘garbage in, garbage out’ holds true. If you use inaccurate data for analytics, customer insight, or reporting, your institution is open to poor customer experience, inefficiency, or even non-compliance.

However, most institutions deal with a high degree of inaccurate information. On average, we see that institutions believe about a third of their information is incorrect. That means that many of those initiatives are suffering as a result of poor data management practices. 

While many agree that trusted data is a must, not everyone is making the investments needed to make that a reality. Here are three ways to justify a data management initiative within your institution.

99 percent of financial institutions believe being data-driven gives their organization a competitive advantage.

#1: Review marketing campaign bounce rates.
One easy way to spot if you have a data quality problem is through marketing campaign bounce rates. Typically, marketing keeps track of how many emails bounce or when letters are returned from a direct mail effort. The higher the bounce rate, the higher the chance you are dealing with poor quality data.

Customer contact information changes on a regular basis. People get married, move, change email addresses, change jobs, etc. However, the institution certainly needs to stay on top of those changes. In addition, we often see the largest degree of inaccurate information contributed from human error. Wrong information can easily be put into a database and then used across departments without proper safeguards in place.

By looking at the campaign bounce rate, you can quickly see the amount of bad customer data that may exist and what that is doing to not only marketing conversion, but potential operational efficiency.

With accurate, relevant, and complete data, you will see more and more customers coming your way, that competitive edge you’ve been looking for, and more accurate reporting. Take a look at those three areas to better understand the level of trusted data in your institution. If you spot a problem, those metrics can be very valuable in driving change.

#2: Check basic data quality metrics and how poor data impacts customer insight.
There are common data quality metrics that most companies look at, which can be a good indicator of the level of trusted data within your system. You can profile your data to see the status of information and obtain these metrics. These look at items like the volume of duplicate records, completeness of fields, uniqueness, and accuracy. Customer data is often the most commonly used information within a financial institution. The level of trusted data across this data set can give you an indication of the level of accuracy for your analytics or even regulatory reporting. Take a quick look at these metrics. They can be valuable in driving some change in data management practices.

#3: Gain insight into your regulatory reporting process.
Typically, within institutions, compliance departments can be very instrumental in driving change. If there is an issue with reporting or the chance of inaccurate information making it into the reporting process, institutions will start to make changes. This is how many data governance initiatives are starting today. There are more and more regulations around consumer privacy and many instances where reporting is required around customer data. Be sure to understand your reporting practices and how your compliance team is safeguarding against inaccurate data.

With accurate, relevant, and complete data, you will see more and more customers coming your way, that competitive edge you’ve been looking for, and more accurate reporting. Take a look at those three areas to better understand the level of trusted data in your institution. If you spot a problem, those metrics can be very valuable in driving change.

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