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How Banks Can Overcome the Challenge of Data Overload

Banks must master the use of unstructured data if they want to seize competitive advantage, enjoy productivity gains, and improve customer service.

Although estimates vary, there is no doubt businesses, individuals, and computer systems are generating data at a rate unprecedented in human history. One estimate, from Computer Sciences Corporation, estimates the total pool of data, worldwide, will be 35 zetabytes (1,000 million gigabytes) by 2020. That's 44 times more data than existed in 2009.  

For banks grappling with data management issues, a bigger concern is that the majority of new data is "unstructured data" -- collections of data that are not integrated into databases and do not have tags or relationships to make structuring them easier. Compounding the challenge, unstructured data, which already accounts for at least 80% of data, is also growing at the fastest rate. 

Of course, data isn't a storage problem, with hard drives becoming less expensive every day. So why is harnessing unstructured data so important? Unstructured data is an incredible source of information, much of which may not be captured in any useable format. Banks that can capture and organize their unstructured data in a meaningful way can gain a significant competitive advantage, enjoy efficiency and productivity gains, and improve customer service.

[Banks Battle For Big Data Talent]

Often, the solution to unlocking the potential of these data resources is a purpose-built business intelligence (BI) platform. These powerful tools process the data in its native format and organize it in meaningful ways.

Extracting the power of data
There are numerous methods banks can use to better structure and analyze data. A few include:

  • Identifying account-holder preferences from credit card purchases and using that information for marketing purposes.
  • Using teller transaction data to determine and predict busy and slow periods and scheduling branch staff for optimal coverage.
  • Collecting account-holder data in the lobby at sign-in and during the wait and assist periods to maximize customer service and identify cross-selling opportunities.

Many banks are hesitant to invest an appropriate amount of money to build or license a BI framework that can put unstructured data assets to good use. Given the current competitive landscape, we believe that banks cannot afford not to take full advantage of their data.

Banks can save hundreds of thousands of dollars a year by implementing just one of the examples in this article: analyzing transaction rates and using them for better scheduling.

Real-world results
One bank FMSI works with -- New Windsor State Bank -- achieved a 15% reduction in its average labor cost per teller line transaction using a BI solution. By using BI to align teller schedules with account-holder traffic patterns, over a year-and-a-half period the bank reduced its labor cost per transaction from $0.97 to $0.82. At the same time, the bank reported improved employee morale, customer service, and sales.

These figures may not sound impressive on their own, but collectively they are quite powerful. Even for a bank like New Windsor (six branches), that $0.15 per transaction drop would add up to thousands of dollars per branch, per month.

Tips and tricks
An executive with another financial institution (FI) with which we work has these tips to share with other FIs considering implementation of a BI solution to harness their unstructured data:

  • If your BI solution provides real-time visibility into the activities of service representatives, use it to inform waiting customers whether or not their requested representative is busy, and give them the option of seeing the first available representative instead.
  • Use any data-capture features built into the solution to track discussions between customers and service representatives. This information is valuable in cross-selling and helps ensure representatives are informing everyone about an appropriate variety of products/services.
  • To efficiently use your solution to track multiple, dedicated activities (for example, cross-selling and helping customers with online banking), segregate them into different data pools so you can better analyze the performance of your branch.

There is an adage in the BI industry: You cannot manage what you do not measure. In the case of big data, just because you have heaps of it does not mean you can manage it. BI solutions give you the power to actually harness this invaluable data.

W. Michael Scott is President and CEO of Financial Management Solutions, Inc. (FMSI). FMSI provides business intelligence and performance management systems that facilitate efficient staff scheduling and lobby management of the branch.  View Full Bio

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FMSI_Inc
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FMSI_Inc,
User Rank: Apprentice
7/11/2014 | 10:29:54 AM
Re: lobby data
Nathan, Any type of product interest data that can be collected through website searches and /or talking with representatives over the phone would be ideal.  There are technologies that allow the collection of website data through cookies, etc.  CRMs can be utilized for conversations via the phone.
Byurcan
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Byurcan,
User Rank: Author
7/10/2014 | 9:50:01 AM
Re: lobby data
In general, it would be nice if the data across the whole enterprise talked to eachother better, like when I am transferred even within the call center to another person and have to re-tell the new person everything I just told the last person.
Nathan Golia
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Nathan Golia,
User Rank: Author
7/10/2014 | 7:56:25 AM
lobby data
What kind of data do you think would be useful for banks to collect before patrons enter the line? And how do you suggest they collect it? I feel like there's a little bit of this done already, but it's more ad-hoc than operationalized.
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