A community bank with offices in Virginia and North Carolina.
The customer had different systems to handle different aspects of their customer business. It was difficult to bring the information together to be able to understand the relationship the customers had with the bank. THInc.IT worked with the team to integrate five separate systems so that the bank could understand the current relationships with the customer and open the opportunity for cross-selling other services.
Each system had its own customer identification number and supporting information. Because each system stood alone, the process of bringing data together to understand how each customer worked with the bank required a significant manual process. THInc.IT’s solution uses master data management principles to pull customer information into a customer master list so that each relationship with the bank can be identified and understood.
How it works...
A customer may have multiple relationships with the bank. It could be through any or all the core systems: Banking, Mortgage, Investments, Wealth Management or Insurance. Each system has its own customer record, so to understand all the ways the customer works with the bank was difficult.
Using existing software and principles of master data management, THInc.IT created a custom process that combines data from the core systems using a matching algorithm. If the match falls below a certain confidence level, the customers are loaded into a list that creates a workflow where a person performs the match function. Any new matches then get incorporated automatically into the next integration process. Once the customers are matched, the data is loaded into systems for marketing and for analysis.
Why it works…
Because the systems had different customer identification methods, there was never going to be a trustworthy way of always finding matches. The process THInc.IT built in cooperation with the bank understands that there are times when human intervention is necessary for the success of systems. The process works because each manual match is fed back into the process and helps to inform future matches, minimizing the human intervention to the greatest possible extent.
Sometimes the only way to make things work is to get people involved in the process, even processes that work best automated. The key is to minimize the involvement and provide a way for feedback to constantly improve the process.