Yesterday, we heard from data governance expert, Ben Leeson, about why financial services companies should be using a master data management (MDM) solution. In case you missed it, you can read part one of the MDM Q&A here. Today we’ll be talking more about the value of MDM in banking IT and how to overcome the elusive aspects of using customer data to improve decision making and add new product and service capabilities.
Don’t forget to register for our MDM webinar on Feb. 26 at 12:00 pm CT to hear from our financial services experts on how leading banks and financial services companies are using information management strategies to help with compliance, synchronizing data across the business and platforms, and leveraging customer information to improve or add new capabilities like mobile and targeted offers, improve customer service, identify cross-sell/up-sell opportunities and prepare for the Big Data ecosystem.
Elizabeth: Let’s talk more about the payoffs for financial services.
Ben: Having a data focal point drives reuse, controls redundancy, and reduces confusion – which all lead to major improvements in efficiency for financial institutions. MDM allows the business to shift risk to data stores that are primed to manage it. Suppose for business and privacy reasons a credit card application process doesn’t retain Date of Birth past the initial submission of the account. To improve conversion rates, the design of the process is meant to be lean. But then the Credit Card Act of 2009 comes along and says anyone who has a card must be at least 18 years old and if you can’t verify the age then you have to assume they’re under the age of 18. By design, the credit card system wouldn’t necessarily have the information, so asking it would produce many false positives. But with a MDM customer hub that does maintain Date of Birth, many of the blank fields and false positives, would be filled in allowing the company to prove the age of most of its card holders. The business gets to continue with its lean application process and not take on more privacy risk while still proving to regulators that their accounts are age appropriate.
Elizabeth: That’s a great example of how banks can use MDM for conformance to compliance, security and privacy requirements. I know you’ll be sharing some other use cases during our webinar around mergers and acquisitions, improving the customer experience across banking channels, tracking customer information and using master data to make better business decisions.
Elizabeth: With benefits like that, why does MDM prove elusive?
Ben: MDM is just like other enterprise level programs that struggle with implementation, adoption and maintenance. The first question I typically ask is what is the data strategy for the company? Is MDM part of that strategy? You have to consider the economic, execution, social, and political impacts within the company. The common thread is Data Governance. It’s vital to partner MDM with Data Governance. It’ll help with stakeholder buy-in, process flow, architecture, and the politics of “data ownership.”
Assuming MDM is part of a financial institution’s data strategy, then the governance debate begins. What data does the company want to be mastered? Remember, this data has to have high data quality, metadata, and integration worked out. Next, you’d have to sort out business rules to settle data conflicts. Suppose I’m a financial services company with several lines of business. Within the company are retail banking customers, small business owners, trusts and clients. It’s inevitable someone will be in more than one group and chances are the data, such as primary phone number, will be different. For MDM, which one is ruled authoritative? We’ve now circled back to the question what data should be mastered; you have to be careful about what data is context dependent and which isn’t. A primary phone number changes depending on the context.
Elizabeth: It sounds like to make MDM a success, a lot of collaboration is needed between the different business departments and then the technology group?
Ben: Yes, each stakeholder must take into consideration all the other domain perspectives and then be willing to compromise to achieve the benefits of MDM. When fully implemented the company benefits similarly to when quality programs (TQM and Six Sigma) were instituted in the ‘80s and ‘90s.
Elizabeth: Where do you see MDM heading?
Ben: I recently read a mind boggling stat, “from the beginning of recorded time until 2003, mankind created five billion gigabytes of data. In 2011, the same amount was created every two days. By 2013, that time will shrink to 10 minutes.” That’s a lot of data. My take is data is an ambiguous resource that can head in any direction except reverse. Because of this I see MDM becoming more statistical in nature. For example, instead of verifying my address as fact, there’d be no verification but rather a statistical certainty based on all the data that is collected.
I also believe since data is getting increasingly discrete and real time, the use cases for master data will grow as the financial services industry continues to push the limits with technology innovation. From a solution provider perspective, MDM vendors will need to develop more out of the box templates around processes for quick starts. In turn, we’ll see more organizations able to move to developing a “golden profile” versus a “golden record” for their customers.
Original Post: http://blogs.perficient.com/financialservices/2013/02/14/perficient-qa-the-payoffs-of-mdm-for-banks/?utm_source=rss&utm_medium=rss&utm_campaign=perficient-qa-the-payoffs-of-mdm-for-banks