How Financial Institutions Can Cultivate Reliable Core Data for More Productive Lending
Core data is the foundation of financial institutions. But how solid is your foundation? Do you trust your data? Has it been transformed? The bigger question is, what can you do to clean it up?
When considering commercial or consumer loan automation, one of the biggest areas of lift an institution can get is by leveraging the information that exists within their core. That should be the foundation of your single source of record.
With so many areas of data governance and regulations, banks and credit unions must re-evaluate their current state. We have all heard the quote “Garbage in, garbage out”, and when it comes to lending, starting with garbage will lead to nowhere but the dumps (not to mention an unhappy client).
How solid is your foundation?
Every system has its limitations, and with that, comes the potential for custom operating environments. While this allows for institutions to configure a system to their needs, it can lead to an unstable foundation. A strong foundation will depend on the successful utilization of whatever it is that you are building upon.
Where things start to crack is when institutions choose to customize fields to make a core (or other systems) do what it is not meant to do. Taking a step back to understand your system requirements, the desired end results, and implementing best practice recommendations on the platforms you use will help you build a strong foundation.
What does your data and the environment look like?
Reviewing what exists is the first step; the current set-up is most likely inherited or previously configured. There could be custom fields, required fields, and perhaps missing data.
Looking at the user interface to see what fields you have and what information is missing is important; eliminate extra fields to provide a better user experience, convert custom fields to standard fields, and clean up bad or missing data.
Lastly, ensuring that your environment has unique identifiers is important for any connection, mapping, or integration you may want to make. Likely, Tax ID numbers are not the way to go but rather a unique client ID. Remembering that you need to have a like for like connection will lead to cleaner passing of data.
Do you trust your data?
As conversions happen, data could potentially have been lost or never collected in the first place (assuming it was not originally required). Other possibly impacted areas are restrictions of the previous platform as well as how the data was collected and/or imported in.
Regulators are constantly looking to find your source of records containing pertinent data for reporting, monitoring, and auditing purposes. The first step towards cultivating reliable, trustworthy data is by identifying old, missing, erroneous, improperly mapped, or partial data, so you can fill in those cracks and repair data that’s essential to all downstream systems and reporting you may need in the future.
Leveraging systems like lending platforms or data warehousing can help you easily identify what is wrong with the data itself.
The second step is cleaning up—you can leverage the data warehouse to initiate a review and update of those data points. If that is possible then hopefully your core allows for mass updates, which you can use to swiftly solidify those data points.
Both these steps allow for risk reduction when deepening your relationship with your clients, especially in lending and other areas of your business. Define your data management utilizing platforms to automate risk reductions and continue building on that foundation to ensure your regulators are confident with what is presented. Remodeling the work already done on a regular basis will ensure you are staying up with the times and be ahead in a fiercely competitive industry.
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Posted on Thursday, July 7, 2022 at 8:15 AM
by Jennifer Foraker