4 minute read
Self-service in the age of data
There is no question that self-service is transforming the world around us. Self-checkout accounted for 55% of all grocery store transactions in 20221. Ticketing booth kiosks and online banking are also growing quickly as preferred transaction methods. This growth is expanding across all markets—so much so that self-service technology is expected to reach a market value of more than $77.7 billion by 20272. So it should be no surprise that much like consumers, issuers are also seeing the benefits.
Self-service delivers a laundry list of pros for issuers. It can even begin to solve one of the age-old headaches many organizations face—data analytics. Modern enterprises generate huge amounts of data. This often buries IT and engineering teams with requests to ingest and deliver reports across multiple business functions. Even with the mountain of reporting requests, most teams only use a small sliver of their data—much of which is siloed, limiting discoverability and accessibility. Self-service data gives the power back to each of these business domains across the whole enterprise.
When an organization can self-serve its analytics, it not only increases their efficiency but enables the ability to reach new markets and create new revenue streams. How is this possible? Self-service democratizes an organization's data. It puts actionable intelligence in the hands of key stakeholders to drive positive business outcomes.
The key is utilizing self-service in tandem with flexible data-sharing. Self-service enables domain users to access, integrate and analyze. Data sharing delivers real-time collaboration. This is essential for improving data availability and extending the capacity to make data-driven decisions.
One size does not fit all
It is crucial that issuers have access to their payment data. Having accurate insights into this data is essential in avoiding financial loss and to acting upon revenue opportunities. However, when it comes to the need for analytics—every issuer is different. No data approach should be “one size fits all.” Issuers need a personalized data approach built into their self-service analytics.
Take Bank A for example, a small regional bank. Their IT team is drowning in a sea of data requests. They simply do not have the resources or technology to fulfill the requests before the data becomes stale and the business misses out on potential revenue opportunities. Bank A addresses this problem by having a partner build them a self-service, analytical dashboard that provides needed transparency across their whole payments business. Now, business domain owners from all across the business can utilize this tool, increasing efficiency and optimizing their data strategy.
Bank A did not have the resources to develop an analytical platform in-house, however, Bank B is a large financial institution with a massive IT team. Despite their large team, they still have prevalent IT resource limitations. They lack timely insights from their payment processing side of the business. A major issue as 90% of a bank's useful customer data comes from payments3. Without insights into their payments, they could miss out on new revenue streams or identifiable risks. Bank B needs to ingest its payment data in real-time. This will enable them to quickly see insights across their entire enterprise.
While Bank A and B may have had similar struggles, they needed different solutions to solve their analytics problem. It’s crucial to meet issuers where they are in their data-driven approach by providing a menu of self-service options.
The next major payoff for issuers
Personalizing the data approach is essential from issuer to cardholder. Enabling better data-driven decisions through enhanced analytics will allow issuers to deepen their customer understanding to drive better outcomes.
Today, 71% of consumers expect companies to deliver personalized interactions4, and 76% are upset when this is not the case4. There is a major growth opportunity available to issuers by utilizing transaction data to develop a personalized cardholder strategy. Missing out on this opportunity could lose issuers up to 40% revenue growth if they choose not to personalize4. The first step is data analysis.
A powerful competitive advantage
It is no secret of the major value delivered from data. Utilizing transaction data could support issuers in overcoming new competition and digital saturation. These powerful payment insights pave the way for new high-value products and revenue drivers. Using this strategy alongside a cardholder outreach approach will support creating a competitive advantage.
With thousands of data points reaching issuers every day, using the right analytical infrastructure—backed by self-service technology—will guide smarter decision-making.
Find out more
An analytical infrastructure that enables collaboration and real-time insights is key to achieving a competitive advantage. Self-service analytics can provide issuers the opportunity to make more data-driven business decisions while personalizing their consumer outreach approach.
If you are interested in learning more about how to grow your data and analytics strategy with TSYS next gen analytics solutions, click here.