The average bank is drowning in data, from neatly structured numbers to more abstract and hard-to-capture inputs from voice, social media and mobile platforms.
IDC estimates the global generation of data will grow from 16 zettabytes (essentially, 16 trillion gigabytes) to 160 zettabytes in the next ten years, a 30% annual growth clip. And Deloitte forecasts that unstructured data – that hard-to-capture category of data; you can find a primer here – is set to grow at twice that rate annually, with the average financial institution accumulating nine times more unstructured data than structured data by about 2020.
The Reality of Data Overload
The explosive volume of unstructured data that banks are able to process every minute of every day is quickly approaching the point where it can no longer be managed by humans alone. What many banks are realizing is that technology possessing the power to mimic human action and judgment – especially at high speed, scale, quality and lower costs – is necessary in order to keep pace with the looming unstructured data surge on a number of different fronts.
In other words, all of the different technologies that encompass robotic and cognitive automation is fast becoming indispensable necessities to the industry’s data challenge. You’re going to be hearing a lot about this category in the year to come, which includes machine learning, natural language processing, chatbots, robotic processing automation, and intelligent analytics.
The industry’s growing data challenge raises a very important question: Will 2018 be the year of robotic and cognitive automation technologies’ mass adoption by banks big and small?
More Data Requires Greater Automation
The foundation is there for robotic and cognitive automation technology to grow rapidly in the year ahead. It is also being reflected in the marketplace. According to Deloitte’s 2017 “State of Cognitive” survey, 87% of cognitive-aware financial services professionals say that such technologies are important to their products and services, 88% say these technologies are a strategic priority, and just over 35% have invested more than $5 million thus far in such capabilities.
Admittedly, the large, global players in the banking and capital markets sector are in many ways ahead of the curve when it comes to experimenting with, developing and deploying robotics and cognitive solutions. We expect rapid, more democratic adoption across much larger number of banks driven by three factors:
First, banks will increasingly incorporate more information from unstructured data. Regardless of whether a bank has hundreds of thousands or millions of accounts, the rapidly expanding set of unstructured data linked to today’s customers demands that banks will need to develop new muscles to handle that data differently. On a tactical basis, executives will need to evaluate their current processes to determine how to use cognitive technologies to incorporate and sift through the large amount – and different types – of unstructured data.
For instance, banks have historically relied solely on customer-provided data and external sources like credit bureau reports in their account opening process. Today, however, banks must also have more information about an individual or company to affirm an applicant’s identity, sometimes resorting to scouring the Internet or social media for this. This could easily compute to thousands of data points for a single customer.
Second, there is a rapid increase in the level of automation of every bank process. Robotics and cognitive technologies are driving this adoption. Robotics on its own is already well integrated across many banks to complete simple rules-based tasks such as opening email attachments and completing e-forms.
However, the cognitive, analytical element of such tasks is still experimental and siloed. The coming year may be a key turning point in that we are going to see the combined power of robotic and cognitive capabilities become the de facto solution at banks for addressing business process challenges.
Simplification for Improved ROI and a Better Experience
The combination of robotics and cognitive automation could play out in more complex parts of a bank’s business and yield bigger benefits. One such example would be the repairing of payment transactions that currently require manual fixes to remediate issues ranging from the mundane (like sender/receiver information being incomplete) to the highly complex (the payment being a potential fraud case.) If, by combining robotic and cognitive technologies, an average bank could auto-clear even 50% of the original breaks, that could translate into tens of millions of dollar and significantly shorter processing time.
Finally, we believe that automation as a whole will inevitably become transformative for every business process. This will likely begin to play out in 2018. We already are seeing examples of such transformation in pockets — from claims processing completed in seconds, to retail accounts opened in minutes, to loan processing in minutes and hours. Typically, these activities take days or weeks to complete.
No matter the size of your financial institution, the business case for robotic and cognitive automation is robust. Aside from managing dizzying levels of data, it can provide a host of other benefits, including reducing costs, lowering error rates, improving customer churn by providing a markedly higher level of service, increasing the scalability of operations, and improving compliance.
Exploring and adopting these technologies will be critical in order to maintain an edge over competitors in the marketplace and to stay relevant, both next year and in the years to come.