Imagine if tennis coaches could engage with players and influence their performance with real-time insights during match play.
Hard to imagine? This capability is a reality today, and it has been for some time.
The sports and fitness industry has certainly embraced the power of real-time insights, and so have other industries – including utilities, retail, and consumer products.
What about the banking and financial industry?
Banks know they are under pressure—no longer do they need to be convinced of the need for innovation. But even as they acknowledge the need to change, some banks remain focused on the front end, continuing to blissfully head down the path of piecemeal digitisation and perpetuating the siloed world. Some, helped by digital pathfinders, are embarking on well-intentioned end-to-end redesigns, but with outdated technology their intent remains just that. Too often, voices echoing “we can’t do it” stifle potential innovation, which typically results in a “circle-in -a-square-box” rejection.
However, Gartner tells us that the coming year will be the year that data and analytics go mainstream. In today’s “data and analytics everywhere” world, as Gartner calls it, banks that are not empowering business operations with a real-time data view risk becoming little more than utilities in a new financial ecosystem.
This topic of data and analytics is not new. As technologies have advanced, data scientists have emerged with well-defined data applications for the banking industry. The proliferation of unstructured data and advancements in machine learning also adds potent fuel to the ensuing data blaze. But just a few of the Herculean challenges to a real-time vision include data siloes, data quality, ownership, and comprehension, and perhaps most significantly, data security.
Intelligent insights: The banking nirvana
What, then, constitutes this nirvana state of real-time intelligent insights?
- The ability to know about things you didn’t know in the past, or that you didn’t even know you could ask
- The ability to act on real-time insights while gaining new insights that are generated as actions are executed
- The ability to predict behaviours, risks, and opportunities, and to be proactive
- The ability to extract value of organisational data (remember that employee insights can be as valuable as those of customers)
- The ability to break through functional data silos and “connect the dots” to gain a well-integrated view across front, middle, and back offices
- The ability to implement real-time capability without needing to destroy and undermine every data and analytics investment made to date
Now let’s assume, in recognition to innovative CIOs/CDOs, that at least some of these goals already in play or are planned. The reality is that data innovation has likely been limited to the CEO’s vision and to the extent that technical architects have sought solutions that can overlay current capabilities.
Let’s explore some applications.
The front-office potential
Retaining focus on the front office remains key. The need for real-time financial planning is gaining energy, particularly with the new banks promising that capability, and with fintechs bringing innovative financial features and consolidation capabilities.
Another area generating enthusiasm is behavioral analysis (applying behavioral science) and adapting customer engagement based on buyer confidence (nervous passive versus actively engaged).
Generating value also remains a strong priority, whether this means managing churn or driving an innovative, open API-enabled collaborative end state in which inter- and intra-industry collaboration drives new market propositions.
Middle- and back-office possibilities
The employee agenda also warrants careful attention. Employee well-being encompasses a much broader scope than, say, how many daily steps one takes. Process analytics can generate efficiency data, and digital signatures can simplify processes and generate data to help regulators.
Optimism is key to accelerating the real-time vision (and I am not even touching the Big Data debate here). “Are we making the most of the data we hold?” needs to become an immediate board-level challenge.
And of course, other challenges remain. Even if banks are able to fight through the siloes and the opposing mindsets, there are emerging requirements that need careful attention – for example, potential data breaches with open APIs and contradictory expectations from GDPR.
Each step in the digital journey requires careful thinking and planning, but what is clear is that it requires a new level of vision, digital fluency, and a consumer-centric digital re-boot toward the new normal that banks face today.
Banks that survive the future will be the ones that drive intelligent insights through real-time analytics, generating value for themselves and for their customers.