Remember the days of “going to the bank?” This used to be a “thing,” a regular occurrence, often a destination, to withdraw money, make a deposit, speak to a financial planner, or just to see the friends that had been made throughout the years. With the advent of online banking, “going to the bank” is no longer somewhere you go, but something you do. Despite offering the same services, the inability to build as many personal relationships has forced financial institutions to come up with new ways to differentiate themselves to help retain their customers.
According to The Financial Brand, to remain competitive, banks are investing extensively in IT systems because institutions have started to recognize that their vast data can help build relationship advantages, which is the first step to safeguard customer loyalty.
But with so much data flowing into and out of these systems, the only way for it to be useful is if it can be vetted and guaranteed to be of the highest quality. To check for data quality, organizations can use an Enterprise Data Analysis platform, which certifies the success of any data migration and system conversion project by helping to eliminate inaccurate information or process errors.
With automated, independent and real-time analysis, financial institutions can reduce the risks associated with migrating data or converting systems, while ensuring the accuracy and completeness of the entire process.
Only an Enterprise Data Analysis platform can produce quality control systems to prevent the propagation of bad data. The platform must provide a mixture of techniques to deliver valuable data and those include:
Customer experience is a major determining factor when it comes to a person sticking with their bank. The ability of an Enterprise Data Analysis platform to create personalized customer experiences doesn’t depend on the quantity of your data, but rather the quality of data that can be translated into actionable intelligence to build customer loyalty.