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3 ways retail banks can improve performance of their ATM operations

swamy_ramchandran.jpgBy Swamy Ramchandran, Business Consultant, HP Software Professional Services

 

Swamy Ramchandran has more than 12 years of experience in Process and Services Outsourcing and Retail Payments. He consults with HP FSI and retail enterprise customers specifically around ATM and EFT POS monitoring and management.

 

Retail banking is an extremely competitive landscape. For consumers, the cost of switching to another bank is minimal. So banks must look for every edge they can when it comes to attracting and retaining customers. One way to find competitive advantage is by optimizing ATM operations.

 

ATMs have evolved a long way since 1967 when they were first introduced to automate cash withdrawals and help reduce queues in front of the banks. Today, the ATM is an  intelligent self-service device. Financial institutions across the world use them to promote, up-sell and cross-sell new services; enhance customer experience; improve efficiency and increase profitability.

 

Consumers list location of ATMs as one of their most important criteria in selecting a financial institution, thus pushing banks to invest in more ATMs to provide greater convenience and attract more customers. As these self-service terminal (SST) networks grow, real-time monitoring and management and investment decisions into the network has become critical.

 

Managing your SST network for more than just availability

To support this dynamic business, transactions need to be measured in business terms, using the kind of metrics managers at various levels expect. Throughout the enterprise, managers should see, at a moment’s notice, how well their ATM network is performing and where to best focus their attention.

 

There is power in information; specifically around the transactional data which most banks already leverage. When it comes to ATM operations, some banks are using transactional data to do more for their business beyond just monitoring for availability.

 

Here, for example, are three use cases where banks can dissect the wealth of transactional data from ATMs to increase revenue as well as customer satisfaction.

 

1. SST profiling

Based on the volume, linearity and flow of transactions, a bank can segment their SST network in different profiles. For example, ATMs in the airport or train station can be grouped as high-performing ATMs with more stringent service levels and cash thresholds compared to ATMs in less-busy areas. One the large bank in the U.S. assembled a specialized team to monitor ATMs during big conventions or game days. This team is not only tasked with network availability but also business outcomes. The “SWAT” team works together to deploy mobile ATMs and brand existing ATMs to attract “Not-On-Us” transactions (i.e., transactions from consumers who use another bank), which translates to revenues.

 

Transactions are also profiled and used to measure how effective new and existing channels/services are performing. Strategies around deployment or re-deployment can be easily deduced by profiling the transactions. A large bank recently redeployed a portfolio of “non-performing” ATMs and increased transactions by over 100%. (Non-performing ATMs are those that don’t attract enough transactions to be profitable given location, costs, seasonality, etc.) These non-performing ATMs were subsequently redeployed to new locations based on data about where the bank was losing transactions. A sophisticated tool that goes beyond availability monitoring can help provide this level of business information, making it possible to increase revenue by changing ATM location.

 

2. Proactive maintenance

Real-time management of ATM transactions - including ATM usage, transaction throughput, accepted and denied transactions, reversal rates, stand-in transaction rates and interchange response times - ensures that IT departments react quicker to failing transactions. Faster recovery means higher availability. A large bank increased availability by calculating hardware maintenance based on transaction levels. For example, a receipt printer needed attention every 10,000 transactions. Trending information from transactional data gave the optimum time for maintenance to take place.

 

3. Cash management

Banks also do cash-level monitoring for the individual ATM, region and whole business, and receive alerts when cash levels are becoming low. Increasing visibility of the cash levels ensures each ATM or region has a higher availability, resulting in less of a chance that your customer will use other institution’s ATM. A large bank in Southeast Asia uses trend analysis on the cash withdrawal pattern of a particular ATM and sets cash-out thresholds depending on where the ATM is located. Specifically in rural areas - where customers typically withdraw smaller bills - the bank now triggers “cash out” alerts based on smaller denominations.

 

HP has a solution that delivers real-time SST monitoring, diagnostics and reporting. For more information on ATM and POS management; please contact swamy.r@hp.com.

 

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Labels: FSI
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