Bell Bank eliminates data silos to get a single, consolidated view of customers

Company Profile

Bell Bank is one of the largest independently owned banks in the nation, with assets of more than $6 billion and business in all 50 states. Founded in 1966, the bank embodies the slogan of, “Happy Employees! Happy Customers!” As part of core value of providing unequalled personal service, the bank wanted to obtain a consolidated, holistic view of customers. At the heart of this initiative lies the goal of understanding the customers’ relationship with the bank and using this knowledge to provide better, more personalized experiences.

Business Use-Case

As a large private bank, Bell Bank deals with many vendor partners and dozens of service lines – from mortgage to insurance, from retirement to wealth management and many more. Each of these services comes with their respective core platforms, data models and customer repositories.

For example, if Customer A has a mortgage, insurance and a 401K plan with the bank, their information is stored in three different platforms with each platform had its own data requirements. With information siloed away and stored in disparate data sources, the bank found it challenging to get a single, consolidated view of its customers; not to mention, they also were incurring unnecessary expenses as a result of sending multiple mails to one vendor or customer. This disjointed view impacts business operations, customer service, and customer experience.

Challenges and Solutions

Disparate sources of data with varying types of information made it difficult for the bank to determine an accurate, single customer view. The bank needed to find a solution that could easily and quickly help them consolidate data from different channels to give a singular view of their customers and the relationship they have with the bank: enter DataMatch Enterprise.

Using DataMatch Enterprise to Get a Single Customer View

DataMatch Enterprise forms a critical part of the bank’s larger in-house data management solution, allowing them to easily group results and hand back the list of records of all customer records that are believed to be of one entity. This consolidated view will help the bank truly understand their customer’s association with the bank and the steps they can take to further strengthen this association. Furthermore, this consolidated view drastically cuts down unnecessary costs and helps the bank manage its operational efficiency. This, in turn, will help with the bank’s customer service and customer experience enhancement goals.

Benefits of DataMatch Enterprise

Bell Bank was able to:

  • Integrate data from files as well as multiple database technologies into the software for direct data treatment and matching.
  • Match and group records across all customer repositories that are believed to be of the same entity.
  • Implement a data quality management plan easily, quickly, and cost-effectively

“The step by step and wizard-like tool that walks you through the process of setting up a project. It’s very intuitive and allowed us to build all kinds of projects and bring in all kinds of data sources. One of the reasons we chose DL was because there is a DB2 import feature that allows us to go right into our DB2 database. The interface allowed us to get good results and it’s very simple to use.”

– Scott Ford, IT Solution Architect

Conclusion

It’s not uncommon for businesses to suffer from disparate data sources and while it may seem efficient for each unit to have its own data model and repository, in the long run, this disjointed view impacts customer service, operational efficiency and customer experience. In this digitally empowered age, businesses must have consolidated views of their customers to provide them better, more personalized, and human-centric experiences. For this purpose, a data quality tool like DataMatch Enterprise allows businesses to merge different data sources in an easy-to-use, intuitive interface, taking them through all the necessary steps of data optimization, cleansing, and matching.

About DataMatch Enterprise

DataMatch Enterprise is a user-friendly and powerful software that helps business users across many industries manage their data more effectively and drive their bottom line. Our enterprise-grade matching tool has been proven to find approximately 5-12% more matches than leading software companies IBM and SAS in 15 different studies. Let Data Ladder be your partner in your next marketing campaign. Increase your sales by offering data cleansing services through DataMatch™.

To get started with DataMatch Enterprise for your needs, click Contact or Download Trial.

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Merging Data from Multiple Sources – Challenges and Solutions

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8 principles of data management

An average enterprise – with 200-500 employees – uses about 123 SaaS applications to digitize their business processes. With large amounts of data being generated

8 principles of data management

An average enterprise – with 200-500 employees – uses about 123 SaaS applications to digitize their business processes. With large amounts of data being generated