Case Studies > MasterCard Improves Customer Experience Through Self-Service Data Prep

MasterCard Improves Customer Experience Through Self-Service Data Prep

Technology Category

Application Infrastructure & Middleware - Data Visualization

Applicable Industries

Finance & Insurance

The Customer

MasterCard

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About The Customer

MasterCard is a technology company in the global payments industry and the second largest processor in the world. They operate the world’s fastest payments processing network, connecting consumers, financial institutions, merchants, governments and

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The Challenge

Derek Madison, Leader of Business Financial Support at MasterCard, oversees the validation of transactions and cash between two systems, whether they’re MasterCard owned or not. He was charged with identifying new ways to increase efficiency and improve MasterCard processes. At the outset, the 13-person team had to manually reconcile system interfaces using reports that resided on the company’s mainframe. Their first order of business each day was to print 20-30 individual, multi-page reports. Using a ruler to keep their place within each report, they would then hand-key the relevant data, line by line, into Excel for validation. “We’re talking about a task that took 40-80 hours each week,” recalls Madison, “As a growing company with rapidly expanding product offerings, we had to find a better way to prepare this data for analysis.”

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The Solution

Derek Madison, Leader of Business Financial Support at MasterCard, oversees the validation of transactions and cash between two systems, whether they’re MasterCard owned or not. He was charged with identifying new ways to increase efficiency and improve MasterCard processes. At the outset, the 13-person team had to manually reconcile system interfaces using reports that resided on the company’s mainframe. Their first order of business each day was to print 20-30 individual, multi-page reports. Using a ruler to keep their place within each report, they would then hand-key the relevant data, line by line, into Excel for validation. “We’re talking about a task that took 40-80 hours each week,” recalls Madison, “As a growing company with rapidly expanding product offerings, we had to find a better way to prepare this data for analysis.”

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Data Collected

Labor Costs, Operating Time, Process Procedure, Transaction Amount

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Operational Impact

[Efficiency Improvement - Labor]
Saved the staff between 40-80 hours of work a week
[Data Management - Data Availability]
New data and metrics can be incorporated easily

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