Author: Maurizio Canton, CTO EMEA, TIBCO Software
The Evolution of Banking Channels
Long gone are the days when the only way for customers to interact with their bank was over the counter in a branch. Likewise, once innovative, ATM and telephone banking services seem old-hat compared to the online, mobile and social networking technologies which are being deployed at an alarming rate, in order to satisfy escalating customer demand for access to their accounts using whatever device comes to hand – anytime, anywhere.
Delivering the IT infrastructure needed to support this proliferation of channels is a huge challenge, fraught with potential difficulties. By the same token, however, it also presents banks with the opportunity to make better use of the, now predominantly digital, data being generated to both identify potential risks and exploit new opportunities to deliver an enhanced, more personalised, customer service.
That said, all of this won’t just happen as if by magic. It needs the right IT systems to be deployed with numerous pitfalls to avoid if it is to be done properly. Not least the need to make sure the right kind of infrastructure is in place with the capability to process huge volumes of data from multiple sources and do so in real-time.
The Risks of IT System Fragmentation
Avoiding the silo trap
Maurizio Canton
The move to self-service is, arguably, one of the key drivers behind developments in retail banking IT with automated teller machines increasingly being installed in branches, unmanned ATM malls and kiosks being built and banks encouraging customers to use online and app-driven mobile services. At the same time banks are facing increased competition from new financial organisations and third party payment providers while coming under even more scrutiny from government agencies and becoming subject to ever more stringent regulations.
What banks must not do, however, is react by leaving existing systems and communication networks alone and address each new channel as it arises by adding new portals and processing the data involved independently. Doing so not only duplicates effort and wastes resources, it also leads to the creation of silos of information that make it harder to both identify risks and exploit new opportunities as customers hop from one channel to another.
More than Big Data
Neither is it enough to simply lump all of the collected data together and analyse it later – the archetypal Big Data approach, involving the use of tools like Hadoop, Hive, Cassandra, and others.
In their defence these Big Data tools can help banks find out what their customers are doing and identify trends which might, otherwise go unnoticed, but with processing, typically, done offline following collection, that analysis will always be historical. In fact the very moment Big Data analytics come up with the answer to a query, that answer is unlikely to be 100 per cent correct and the longer from the time of collecting the data the more inaccurate the answer is likely to become.
Add in constant changes in data sources, formats and volumes and you start to see why Big Data by itself simply isn’t enough to enable customer-focused organisations such as banks to deliver flexible services. Moreover, you can start to see why Big Data alone is of little help when it comes to keeping services secure and protected in an omni-channel marketplace demanding instant tailoring of services depending on who the customer is, what they want to do, the touch point involved and so on.
Why Fast Data Matters in Banking
Fast Data = better data
Given that in the future banking customers will be digitally connected, highly informed and expecting a highly personalised service, it becomes necessary to analyse all of their data at source. Moreover, this needs to be done regardless of channel, with context applied to enable the data to be put to intelligent use, calling for a comprehensive distributed infrastructure to both capture and analyse customer information however and whenever they interact with the organisation.
Event-Driven Infrastructure for Real-Time Analytics
That infrastructure also needs to be event-driven leveraging in-memory computing to capture and correlate potentially millions of events in real time to allow banks to identify opportunities and risks as and when they happen. Not just Big Data, but Fast Data if you will, supported by a distributed processing and communication platform for the automation needed to both react immediately to critical events such as suspected fraud and identify and exploit opportunities to present personalised offers and tailor service interfaces to individual customer needs and aspirations.
The way forward
Fast Data supported by an event-enabled platform enables banks to anticipate the future by having the right information, at the right time and act upon it pre-emptively for competitive advantage. The supporting infrastructure can also provide a standard platform for the integration of new systems and the creation of new services, resulting in significantly greater agility by reducing the time and resources needed to bring new applications and partners online. Plus there are efficiency gains and significant cost savings to be had from automation and workforce optimisation, for example, cutting the time and human errors involved in loan processing, creation of new accounts, complaint resolution, and other processes.
Conclusion: Preparing for the Future of Banking
Coping with the proliferation of customer channels is a challenge that banks everywhere need to address and all are doing so already. However, with the help of a suitable event-driven platform able to collect and analyse data and react to events in real-time it can also be significant opportunity and one not to be missed.
Maurizio Canton
As EMEA CTO for TIBCO Software, Maurizio is responsible for ensuring consistency of technology vision, providing strategic sales support and support for AR, PR, marketing and M&A initiatives, as well as serve as a conduit for the Global CTO function. Maurizio has more than 25 years of experience in IT, working for several software vendors, such as TIBCO Software, IBM, Siebel, SOA Software and Red Hat.
