It is no secret that the financial industry is completely changing the way that it functions. Financial institutions are expected to have a comparable user experience to retailers, and at the same time continue to uphold regulatory compliance. It is important for financial organizations to understand what steps are necessary in satisfying these marketplace essentials. The more they are able to balance and prioritize compliance and providing a frictionless and automated experience for customers, the more financial institutions are able to remain competitive in a changing industry.
One key initiative that can be employed to satisfy both of these requirements are data quality solutions on the front end of systems and workflows. If there isn’t anything being done to ensure only quality and accurate data is being entered into a system, then both compliance and a frictionless customer experience are in jeopardy. Without data quality solutions, financial institutions will inevitably be working with incorrect contact data which will hinder their ability to remain compliant and have accurate reporting in place. Furthermore, Know Your Customer (KYC) initiatives are greatly impacted by poor quality data. How can an institution know their customer on an individual level if they are not collecting accurate contact data? Initiatives like fraud and identity checks, credit lending, new account set up, compliance screening, and decisioning tools will all benefit from having data quality solutions on the front end of systems.
On the same note, if quality and accurate data is not being entered into the system, then there is probably going be the need for manual interaction from the customer. Whether this is because there is invalid data stored and the customer is not recognized, or there are duplicate records in the database, a customer is going to be required to interact therefore defeating the goal of providing a frictionless and automated user experience. Poor data quality can even result in manual exception reviews, creating more manual effort and time spent from employees. It is important to ask what more valuable initiatives could that employee time and business money be spent on? Where could that time and energy be spent more effectively?
It is important to note that our 2017 global data management benchmark report revealed that 74 percent of financial institutions believe that data quality issues impact customer trust and perception. This is another important component in the evidence that financial institutions need to be proactive in their data management practices. If a customer does not trust the institution they are banking with, then this can negatively impact the financial institution’s image in the marketplace as well as their ability to grow their customer base. A financial institution should exude trust and confidence and a lack of data quality can prevent this necessity. It is clear why a customer would feel as though their financial institution is not trustworthy if the institution is collecting, storing, and using inaccurate data. It is even more important to consider how this lack in customer trust will impact the organization as a whole.
It all boils down to one question—if there are no processes in place to ensure data quality on the front end, then how are financial institutions jeopardizing their organization from a compliance standpoint and how is it affecting their overall customer perception?
The good news is that there are steps that financial institutions are taking to meet regulatory and customer expectations. By adding real time contact data verification on the front end of workflows, a financial institution can have measurable improvements in customer experience, a reduction in manual exception reviews, more confidence in the quality of customer data, and much more!
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