About four years ago, Banco Bilbao Vizcaya Argentaria (BBVA), an innovative bank from Spain, deployed Lola, a virtual banking assistant. In May last year, Ally Bank launched Ally Assist, a virtual assistant who answers basic questions about bill payments and recent transactions.
To those belonging to the branch banking generation, this must be automation enough. But the rate of progress in digital technologies says that we've barely started.
Imagine, for instance, how Internet of Things (IoT) of 50 billion connected devices could automate virtually every banking operation, not just at the back-end, but also at the front-end. A very small preview of that is already visible in the form of intelligent and automated investment platforms like Wealthfront, which are replacing traditional wealth managers to take investment decisions on behalf of their clients. With increasing automation, it is very likely that even basic banking systems will become more intuitive and intelligent to suggest or even trigger services before customers ask for them.
Note how the nature of automation itself is changing, from mere enablement of scale and efficiency to intelligent, self-learning and proactive. The pre-defined business rule, which used to be at the heart of automation, is giving way to cognitive computing and systems that are smart enough to suggest the right financial product for each customer and context, as well as contrast the implications of competing choices.
In its new avatar, automation will also focus on improving the banking experience to a level where there is no break in service to customers, where for instance, the digital experience covers not only banking transactions but also account origination. However, this will only be possible when banks leverage automation on a large scale, across all front and back-end systems and processes.
That's an ambitious agenda, which comes with its own challenges. While there is no template for how banks should automate, there are some recommended practices, which go some way in mitigating risks and accelerating results. The first is to simplify the technology landscape so that the banking organization can use as much data as possible, and do it effectively. Most banks are saddled with silo based business applications that cost to maintain and integrate. These can be rationalized by switching to enterprise-class components. Similarly, banking processes need to be redesigned to make them suitable for the truly digital bank of the future. Once processes and applications are simplified, rationalized, integrated and unified, it will enable data to flow seamlessly through the enterprise to make it ready for end-to-end automation.
The second recommended practice is to gradually develop use cases for automation, and implement them one-by-one, rather than waiting to unveil a grand automation master plan. Again, there's no silver bullet; this is something that can only be learned from experimentation and experience - in a true design thinking spirit.
Last, but by no means least, is to prepare the banking workforce for the tremendous change that automation will bring in their lives. It's quite certain that routine, process-driven roles will be lost to machines, which will perform them better for the most part. Bank workers must therefore look beyond the logic-driven services to perform uniquely human functions, such as building emotional connect with customers. Yes, machines will take over some part of their world, but they will also open up new ones where the banking workforce can amplify their human potential.
Guest Author
The author is global head of marketing at Infosys Finacle
