Whether you’re implementing the latest blockchain technologies, or you’re just using your smartphone once a month to pay the utility bills, you’ll have noticed things are evolving. The banking industry is on the frontline of technology adoption, and with the rise of fintech, banks are facing increasing pressure to evolve all aspects of the traditional ‘brick and mortar’ model.
Whilst many of the technologies in fintech focus on making previously tedious tasks simple for end users or customers, it is the work behind the scenes which will have the greatest impact on shaping the future of the banking sector.
This article looks at a selection of emerging trends and the role they will play in solving problems for the banks of tomorrow.
Ten years ago, if I told you the role of a data scientist would be flaunted as the sexiest job of the 21st century (no, really!) you might have told me to go back to my statistics textbooks and check the numbers… I’ll admit, on first look there is nothing sexy about data management, but the rise of big data is changing the landscape. Big data is now a commonplace term in boardrooms across the globe and data management has never been more important. As for the teams and individuals enabling these advances? They’re the corporate rock stars of the day.
“Technology when used as an amplifier of human potential allows us to “do more with the same””
The importance of data management scales with the amount of data an organisation utilises (or wishes to effectively utilise). With a large proportion of corporate data, including forecasts and plans, sitting in unstructured stores such as spreadsheets, the banks of tomorrow will need to adopt innovative enterprise-level systems to ensure the high level of data quality and integrity required.
A recent survey found that 27.5% of accountants attributed human error to mistakes in their spreadsheets. We’ve all been there; the slip of a clumsy finger, copying and pasting into wrong cells, or even a simple typo. It’s easy to do.
Whilst recognising the unique skills we humans possess in problem-solving and analytical approaches, we mustn’t overlook the fact that there are some activities – particularly those involving repetitive and mundane tasks – which are better suited to those less inclined to momentary lapses in concentration, fat finger syndrome, or even spreadsheet related repetitive strain injuries (yes, they do exist).
“Algorithms have been demonstrated to review commercial loan agreements with astonishing accuracy and speed”
Computers do what we tell them to do, when we tell them to do it, and at an incredible speed. Banks of tomorrow should use this to their advantage and invest in automation where available, freeing up their workforce to spend time on tasks where their brainpower is far more valuable.
For some, automated technologies could be regarded as a threat to certain existing job roles within banking. But, as time has shown us repeatedly, technology when used as an amplifier of human potential allows us to “do more with the same”, and often opens and creates new and exciting roles within the sector.
Banks of tomorrow are likely to make extensive use of advances in analytical techniques such as deep-learning and machine-learning. In the US, leading investment bank JPMorgan Chase & Co have introduced machine learning in a new application termed COIN (Contract Intelligence). The algorithms have been demonstrated to review commercial loan agreements with astonishing accuracy and speed, saving time on the 360,000 years annually spent by teams of lawyers and skilled loan officers.
With well-structured systems in place to manage data from all aspects of banking, future algorithms will be well equipped to anticipate complications before they become problems, automatically predicting future data trends or even spotting mistakes in spreadsheets before they wreak havoc.
Alongside banks and other service providers, customers and end-users are becoming increasingly tech savvy. In under a decade, an entirely new generation of customers will make up a large proportion of banks’ key customers. Sometimes referred to as “Generation Z” and at other times referred to as “Generation Y on red-bull”, these customers have never lived in a world where information was not readily available at the swipe of a finger, or through other novel interfaces such as voice command or fingerprint recognition.
To stay competitive, it’s clear that banks will need to continue to improve the readiness of data, combined with accessible cloud analytics platforms allowing customers to conduct their own what-if analyses. If they don’t evolve, they risk falling behind or even falling from relevance.
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