Driving Banking Engagement with Customer AnalyticsHow transaction data will help you grow revenue, reduce operational costs and make

customers happy.

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OverviewTop retail banking priorities – specifically, recognizing new revenue opportunities, improving customer relationships and reducing operational costs – all require a deeper understanding of where, when and how customers interact with various self-service channels. The key to understanding customers and improving channel profitability lies in making rich transaction data readily available and easy to use by line of business managers, marketers and operations teams.

“62% of financial institutions in a recent Celent survey strongly believe that customer analytics offers significant competitive advantages and 53% strongly feel they need a granular, holistic and forward-looking view of customers to be competitive. One key to understanding customers and improving banking channel efficiencies lies in making rich transaction data accessible for actionable customer analytics.”

BOB MEARA, SENIOR ANALYST CELENT

When it comes to understanding banking engagement, transaction data is a gold mine. Each transaction contains useful information that answers questions such as:

●● What are my customers experiencing?

●● What is the business value of each customer interaction?

●● What can we do better to improve customer engagement, drive revenue up and costs down?

●● How are my various customer-facing technologies, networks and applications performing?

Mining customer transaction data can be a costly and time consuming task. Retail banks, credit unions and payment processors are now dealing with enormous volumes of transaction “Big Data” that needs to be gathered over sprawling, multi-vendor network and application infrastructures. These transactions are often routed through a variety of service and fraud applications, adding another level of complexity when it comes to gathering customer data.

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As transaction data continues to grow in size and scope, the way you work with it needs to change, as well. To get the most out of customer transaction data without exploiting resources and budgets, you need to simplify the way this data is collected, stored and visualized across each banking channel, including:

●● ATMs●● Point-of-sale●● Branches●● Mobile Banking ●● Internet Banking ●● Payments

In this whitepaper, we will discuss new approaches to transaction data collection, storage and visualization that are making it easier for line of business managers, marketers and operations teams to perform more robust customer analytics. Discover new ways to build loyalty, spot customer acquisition opportunities and enhance multi-channel profitability through better placement decisions and targeted service offerings…without getting lost in the data.

Customer happiness and loyalty – an ongoing pursuit for retail banks As financial institutions large and small continue to battle low interest rates, heavy regulation and a weakened economy, customer analytics is becoming an essential core capability. For most retail banks, understanding customer usage patterns and adopting data-driven retention and acquisition strategies is the easiest way to increase profitability and gain competitive advantage. And all of these tasks can be successfully achieved with transaction data.

FIGURE 1: Source: Celent survey of North American FI’s, October 2014, n=156 Question: What are your institution’s top retail banking priorities?

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Transaction data - An “EKG” into your customers’ banking activities Similar to an electrocardiogram that checks for problems with the activity of your heart, transaction data displays problems and interesting information related to your customers’ banking activities. Transaction data not only contains information on network communications, third party connections and application response times, but also rich intelligence related to:

●● Customer profiles

●● Event times

●● Self-service technologies being used

●● Card types

●● Service requests (or series of service requests)

●● Dollar amounts

●● Host authorization responses

●● Network routing paths

●● The performance of many “moving parts” such as transaction switches, firewalls, service applications, or host security modules

FIGURE 2: Who uses transaction data? Operations support teams responsible for availability and performance of all applications within a banking environment. Line of business managers, marketers and data analysts responsible for channel profitability and end customer experience.

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Transaction data is the richest and most complicated data found within any payments or retail banking environment. When it comes to today’s complex networks, it is often the case that one transaction is made up of sub transactions – many moving parts between a start point such as an ATM, and the end point, such as a host authorization. No two customer transactions are exactly alike.

Electronic transactions are also the largest, fastest growing subset of “Big Data” within financial environments. Although the complexity and volume of this data may seem overwhelming, line of business managers, marketers and operations teams realize that—when harnessed and leveraged correctly—transaction data also represents a live, “always on” feed into how the organization is performing, how services are being delivered and how happy end-customers really are.

FIGURE 3: Displayed in Feb 2015 Celent webinar titled, Customer Analytics in Banking - What’s the Hold Up? Source: The real world of Big Data, IBM & University of Oxford. Respondents with active Big Data efforts were asked which data sources are currently being collected and analyzed as part of active Big Data initiatives.

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Collecting and storing transaction “Big Data” As more and more banking services go digital, the skillful collection and storage of transaction data will become increasingly important. Consider the value of collecting and storing transaction data in a centralized location, across all your moving parts and channels. It means that you don’t have to go searching for it when you need it the most.

It is also important to remember that your analytics will only be as complete as your data source. That is why, when line of business managers, marketers and operations support teams use customer transaction data for analysis, this data will ideally be captured across an entire “end-to-end” transaction path. Each structured individual customer transaction record will contain a wealth of information, including:  

●● Data on device ID numbers and geographic locations

●● Transaction approval and event completion status

●● Transaction types and dollar amounts

●● Card types and host authorization responses

●● Response timing and failure information for each “moving part” on the transaction path

FIGURE 4: Capturing transactions: Who owns the data? How do you extract if from all these different places? How do you correlate fragmented pieces into a complete view? How do you deliver this data in a “ready to analyze” state?

POS Server Mobile Server

Middleware

Core Card Networks Partners

Security

ATM Server 3rd Party

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Relying on transaction monitoring software to do the heavy lifting – not your operations team Capturing “end-to-end” transaction data has been a longstanding challenge for many financial institutions. This is not only due to the amount of data, but also the increasing variety of applications and the decentralized, silo’d ways transaction data is often captured. Traditionally, line of business managers and marketers have lacked on-demand transaction data access, and have had to rely on their operations team to spend many expensive, time consuming hours piecing together fragmented data collected from multiple sources – many of which are unreliable. These traditional data collection and storage issues surrounding transaction data have also impacted the ability of retail banks to produce dynamic dashboards and customer analytics reports without long lead times.

Thankfully, due to major technology advancements, the days of deep dependency on IT for customer intelligence are now over. Many of today’s retail banks now depend on software to do their heavy data lifting - not their operations team. This makes transaction data collection and the pursuit of customer analytics easier, more cost efficient tasks. You can now focus on making timely and actionable decisions rather than waiting weeks or months for key questions to be answered.

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Collecting and centralizing your customer-centric data in an easy to access, cost-effective wayNetwork-based software solutions such as INETCO Insight® are built to handle high-volume electronic transaction environments, easily monitoring any and all types of electronic customer interactions happening within multi-channel retail banking networks. Protocol and platform agnostic, this software platform captures and correlates real-time consumer transaction data in a secure, light-weight fashion, enabling financial institutions to overcome past data mining limitations and avoid high cost, manual data collection and correlation tasks.

With on-demand access to structured transaction data, line of business managers, marketers and operations support teams can analyze information such as:

●● The types of customer interactions being performed by top customers and where

●● The number of customer transactions being performed and where

●● The transaction types conducted by channel, including dollar amounts

●● The transactions broken down by service and card types

●● Transactions broken into on us versus not on us traffic

FIGURE 5: INETCO Insight light weight data collection: Use server agents, SPAN/TAP port mirroring or client agents to collect all your transaction data in real-time.

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With a “bottoms up” view of your network traffic, your operations team can collect all the real-time transaction data line of business managers and marketers need with lower implementation costs than ever before:

●● Without having to instrument applications and deal with traffic load, flow or debugging issues

●● Without having to spend hours sorting through log data

●● Without impacting the electronic payment systems and applications running within your multi-channel banking environment

Using transaction data to drive banking engagementThe centralized data collection and structured transaction correlation provided by INETCO Insight means that line of business managers, marketers and operations support teams can now access complete, “ready to analyze” transaction data on-demand. This timely and actionable data can be easily parsed into channel-specific views for ATM, POS, Branch, Mobile Banking and Internet Banking.

Once you have secured a transaction data feed, it is important to think about how you want to use that data. To address specific customer use cases or quickly execute data-driven actions, the front end customer analytics solution being used for data visualization needs to meet the following vertically-focused criteria:

●● Contains multiple preconfigured dashboards designed to expedite the analysis of customer engagement patterns and conduct predictive analytics

●● Can embed transaction data and other feeds for specific use cases

●● Contains reports that can be run on-demand and easily understood by line of business managers and marketers

Investing in self-serve analytics applications tailored for business users A self-serve, analytics application such as INETCO Analytics™ is an easy way to see your wealth of customer transaction data – ready to be analyzed any time you need it. With on-demand access to rich records of every consumer transaction, line of business managers and marketers can apply their rich domain expertise, and understand customer behaviors throughout any banking channel, such as:

●● Who uses which ATMs or POS terminals?

●● What kind of interactions are customers having at my Internet Banking or Mobile Banking application, and when?

●● What quality of service are customers experiencing?

●● How profitable is this customer or group of customers?

●● How did that latest outage affect channel profitability?

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Transaction data is continuously streamed from the INETCO Insight real-time transaction monitoring software platform into the INETCO Analytics application using a secure protocol. This data is processed on a daily or hourly basis, transforming it into an appropriate form for analysis and modelling (e.g. queuing, transaction sequence, cash balances). You can also ingest complimentary third party data sources such as BIN lists, ATM configuration data, competitor location information and customer demographics for more enriched data visualization and decision making.

Storing transaction data within a Hadoop data storeThe INETCO Analytics architecture was designed to streamline the storage of transaction data across your entire network. Data ingested by the INETCO Analytics application is warehoused within a Hadoop data store, giving you the ability to easily scale to a cluster without costly, additional licensing required. Transaction information stored for data mining includes:

●● Meta data such as ATM terminal ID’s, geographic locations and transaction status information

●● The application payload information such as transaction types and transaction amounts

●● Response code and error information for each transaction

This data, along with any complimentary third party data you wish to store, can be extracted from Hadoop using the friendly Tableau interface or simple SQL queries – no extra code writing required.

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Example - The INETCO Analytics for ATM solutions packThe INETCO Analytics for ATM solutions pack was designed for ATM channel managers and marketers interested in using transaction data to:

●● Make better ATM placement decisions

●● Improve cash inventory and replenishment schedules

●● Simplify profitability analysis and reporting

●● Run ad hoc queries and analyze outage impacts

●● Customize service offerings

Using these interactive dashboards and report library, ATM channel managers and marketers can analyze:

1. ATM profitability (and performance by formats)

2. ATM placement

3. Customer interactions and behaviors

4. Cash replenishment patterns

5. Failure/outage impacts

6. Service task times and flows

On the following pages are a few example screenshots of the INETCO Analytics for ATM workbooks. You can also explore various use cases and transaction data insights on the INETCO website for:

●● Omni-channel banking and customer engagement analytics

●● ATM channel analysis

●● POS channel analysis

●● Mobile and Online channel analysis

●● Debit, prepaid and credit card analytics

●● Fraud management and analytics

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1. Analyze ATM profitability

Use transaction data to understand revenue mix, transaction volumes and profitability of each ATM, group of ATMs, or the entire ATM fleet. Analyze who uses the ATMs, what types of transactions they perform, and when. Monitor customer usage by location, and identify targeted opportunities where you may want to run marketing, retention or acquisition campaigns to increase ATM profitability.

FIGURE 6: ATM Performance Workbook Example

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2. Make better ATM placement decisions

Customer transaction data combined with competitive location data will help you understand the placement and profitability of every ATM in your fleet. You can use this workbook to analyze customer usage at the ATM fleet level, group level or individual cash point level. Built-in algorithms enable you to investigate queue lengths.

FIGURE 7: ATM Placement Workbook Example

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3. Understand customer interactions and behaviours

Access rich, structured records of every customer transaction performed at the ATM to quickly understand where, when and how they interact. Spot top customer and acquisition opportunities, or drill into details about ATM cash positions and cash availability.

FIGURE 8: Customer Locations Workbook Example

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4. Optimize cash levels and replenishment at each ATM

View your cash positions for each ATM in your fleet. Parse out transactions related to replenishment events to minimize costly activities such as cash surpluses, emergency cash replenishment and cash outage situations. Also use this workbook to measure cash utilization against targets.

FIGURE 9: Cash Utilization Workbook Example

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5. Measure the impact of ATM failures

If your ATMs are experiencing an abnormal number of partial or complete failed customer transactions, this workbook will help you investigate and track specific error types. This data can also be used to measure the lost revenue and customer impact of these service disruptions.

FIGURE 10: Customer Frustrations Workbook Example

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6. Conduct robust customer task flow analysis

This workbook enables you to identify customer transaction sequences at the ATM, and monitor the most

commonly completed tasks. ATM channel managers can use this data to streamline their ATM screen flows,

or measure the transaction duration and impact of ATM interface or functionality enhancements.

FIGURE 11: Transaction Analyzer Workbook Example

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Building on-demand dashboards and reports

These examples are just some of the reports and workbooks that have been pre-built within the INETCO Analytics product. The easy to use Tableau interface enables line of business managers and marketers to also build their own workbooks, or perform their own on-demand reporting and ad hoc queries. Transaction data is continuously refreshed and easily blended with complimentary data sources such as BIN lists, competitive locations and demographic data.

FIGURE 12: ATM Formats Workbook Example

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Conclusion Customer happiness and channel profitability depends on your financial organization’s ability to analyze banking behaviors and make timely, data-driven decisions. Your growing need for customer analytics, coupled with INETCO’s technology advancements in transaction data collection, storage and vertically focused visualization applications, means your bank is now set to win.

INETCO’s transaction monitoring and analytics products are proven solutions that make the real-time extraction of transaction data into an operations and business view easy and cost effective. This enables line of business managers, marketers and operations support teams to focus on what they want to accomplish rather than spending days and dollars gathering transaction data from multiple silos. Easy access to transaction data and analytics, combined with rich domain expertise, will enable your bank to make data-driven decisions that will lead to increased revenue streams, reduced operational costs and more happy customers.

“…Gaining (general consumer financial) insights has traditionally been a big IT job – it required the creation of data warehouses, the wrangling of some pretty intense analytics querying solutions and a bunch of technicians to make it all work. INETCO is trying to collapse that all into a single product…Vertical specific analytics is going to be a big trend in 2015. INETCO is offering the banking sector something valuable here.”

BEN KEPES, FORBES CONTRIBUTOR(http://www.forbes.com/sites/benkepes/2015/01/15/more-vertical-analytics-solutions-inetco-goes-analytical-on-atm-data/)

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About INETCO®—Every transaction tells a story®

INETCO® Systems Limited provides market leading transaction monitoring and analytics software that helps line of business and IT operations teams improve profitability, reduce operational costs and deliver an amazing customer experience. INETCO’s proven solutions are currently deployed in over 50 different countries. Happy INETCO Insight® and INETCO Analytics™ partners and customers include some of the world’s largest companies spanning the banking, ATM, retail, telecommunications and payment processing markets. www.inetco.com

© 2015, INETCO Systems Ltd. All Rights Reserved. All referenced trademarks, registered trademarks, trade names, service marks and logos belong to respective companies. +1.604.451.1567 | info@inetco.com | www.inetco.com