The sports and fitness industry has certainly embraced the power of real time insights, so have others – utilities, retail and consumer products.

What about banking? Surely that is also the case for banking as well? Isn’t it?

Banks know they are under threat. No more do banks need convincing on the need for innovation.

Whilst we are in violent agreement about the need to change, as I look around the industry, I see some banks blissfully heading down the path of piecemeal digitisation mostly front end focused; creating (while unintentional) yet another silo-ed world. Some are embarking on well intentioned end to end re-designs; helped by their respective ‘digital pathfinders’. With an outdated technology estate however the intent remains just that. Loud voices echoing ‘can’t do it’ often stifle the potential of an innovative end state; that typically ends up getting a “circle in a square box” rejection. (Unfortunately, this is surprisingly common!).

Gartner tells us that the coming year will be the year that data and analytics go mainstream.

In a ‘data and analytics everywhere’ world, as Gartner calls it, if bank’s are not empowering business operations with a real-time data view, one risks becoming little more than a utility in the new financial ecosystem.

This topic of data and analytics is not a new one. 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 is also adding potent fuel to the ensuing ‘data blaze’. Sadly however, one wouldn’t have to think too hard to list data challenges that highlight the ‘Herculean’ nature of a real time vision. That list of challenges would of course start with data siloes, data quality, data ownership and data comprehension; with data security no doubt ending up top of the pile.

“Intelligent Insights” – the ‘nirvana’

What then could be a real time nirvana state – an idea of ‘intelligent insights’?

• Be able to know about things you didn’t know in the past or even knew you could ask

• Be able to act on real time insights, while gaining new insights that are generated as actions are executed

• Be able to predict behaviours, risks and opportunities and act ahead of the benefit or be able to ‘avert’ appropriately

• Be able to extract value of organisational data; after all, insights of an employee are as (if not more at times) valuable than that of customers

• Be able to break through functional data silos and ‘connect the dots’; to get a well-integrated view across front, middle and back offices

• Be able to implement such a real time capability without needing to destroy and undermine every data and analytics investment made to date

Now let’s assume as a recognition to innovative CIOs / CDOs that a fair bit of such an end state is already in play (or is planned); the reality is that ‘data innovation’ has been limited to where there has been a will (that of the CEO), and where 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. Need for real time financial planning is gaining energy, particularly with the emergence of new banks promising exactly that and FINTECHs bringing innovative wallets, financial consolidation capabilities. Another area generating enthusiasm is analysing behaviours (applying behavioural science) and adapting customer engagement based on buyer confidence (‘nervous passive’ versus ‘actively engaged’).

Generating value remains high on the agenda, be it managing churn or driving an innovative, open API enabled collaborative end state where inter- / intra- industry collaboration drives new market propositions.

The middle and back office possibilities

Moving from the front office, the employee agenda is warranting careful attention. Well-being is a topic (and that’s not just how many daily steps one has taken) but more about whether the employee (mis-) behaviours are worthy of attention (in terms of effective working or risk of misconduct). Exploring further and one can start discussing process analytics and how it generates efficiency data or how digital signatures are not only simplifying processes but generating data that regulators will find useful on whether the customer read (and re-read) the important bits.

So, now what?

Optimism is no doubt the only ‘vitamin pill’ that can accelerate the recognition and application of this real time vision to leverage organisational data (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.

There are ‘slippery banana skins’ of course. Even if banks are able to fight through the siloes and the mind-sets, there are emerging requirements that need careful attention – data opening with Open APIs and the potentially contradictory expectations from GDPR.

Of course, each step in a digital journey will need careful thinking and planning, but what is undebatable is that it requires a new level of vision, digital fluency and consumer-centric digital re-booting to drive towards the ‘new normal’ that banks now find themselves facing.

Banks that survive the future will therefore will be the ones that re-focus their digital spend on driving ‘intelligent insights’; insights that generate value for the bank and delivers added value to its customers.