Showing posts with label analytics. Show all posts
Showing posts with label analytics. Show all posts

Monday, 31 August 2015

What makes a challenger bank a digital challenger bank?

Let’s face it challenger banks are nothing new they have been around for a long time. In the UK there has always been a large number of challenger banks – the Co-op, Yorkshire Bank, Clydesdale Bank, Alliance & Leicester, Bradford & Bingley, Abbey National, Nationwide Building Society to name just a few past and present challengers. In Australia you would look at the likes of Bendigo, Bank West, BoQ as examples. However despite there being the challengers in the market, the share that the Big Four (in the UK) or the Four Pillars (in Australia) have not fundamentally been impacted by the presence of the challengers.

Over the last few weeks in the UK a number of the new challenger banks have been reporting their results. The UK’s Sunday Times produced the chart below: 
 
This shows just how the share price of some of the challenger banks has risen despite the stormy market conditions due to delivering a good set of results. Whilst the market share all three of these banks have picked up is good considering where they have started from, it is still tiny in comparison to the share of the Big Four banks. Even if they continued at the rate that they are growing at it would take years for them to have a significant share.
What each of these challenger banks have in common is that there basis for competition is entirely traditional and they are competing in exactly the same way, albeit providing a marginally better service, that the Big Four banks go to market, so why is there any surprise that their impact is so little?
Some of the other challengers will argue that they are providing customers with a better experience by providing customer lounges, opening longer hours, providing a debit card immediately in branch on opening an accout, offering drive through services or putting edgy images on credit cards. However these are cosmetic changes and are not fundamentally challenging the way that banking services have been procured for the last two hundred years.
For the challenger banks to make any significant impact on the incumbent players they need to become digital challenger banks.
What is a digital challenger bank?
The terms ‘challenger bank’ and ‘digital’ are continually bandied around with little common agreement as to what they mean.
For the purpose of this argument a digital challenger bank is one that fundamentally changes the way that customers experience and procure banking services, that acts in real time based on customer insight and demand, is available 24x7 and is accessible across any channel and most importantly is agile being able to rapidly adapt to changes in the way that the customer wants and needs to do business.
Taking each of these parts of the definition what does that mean for a bank wanting to become a challenger bank?
Being truly driven by the customer
For too long banking has been operating on a push model where the bank is in the driving seat pushing its products, operating its processes. While many banks talk about being customer centric they still take an inside out view of customers that asks the question what can the bank sell/do for a customer rather than an outside in view which is answering the question what does the customer want of its financial services providers. Without this fundamental change in thinking it will not be possible to be successful in the long term.
Real Time
The whole banking system is still upon a branch based architecture, even those without branches. The fundamental philospohy is that branches hold accounts (hence the sort code that each account has), that at the end of the day branches tally up their accounts (which is why they traditionally closed at 3pm so the branch staff could do this before going home) and then post those accounts to Head Office. Overnight the transactions between branches and other banks are reconciled and at the beginning of the day the cycle all starts again. However in the digital ages consumers expect their service provider to not only to be available 24x7 but also the information that they share to be absolutely current and accurate. While most banks simulate real time to more or less an extent their IT architectures are batch-based and historical. Hours of every night are spent reconciling accounts and establishing at one moment of time the financial position of the bank.
With the arrival of mature real time, high performance supercomputing platforms true real time banking has finally arrived.  This means that it is possible at any time to have a real time financial position.
Customers have grown used to expecting real time. When they search Google they don’t expect to see only search results as of last night. When they go on Facebook they expect to see their friends’ latest updates not as of two hours ago. They expect the same from their banks.
Without using supercomputing realtime platforms the digital challenger bank will not be able to deliver the experience that customers are demanding.
Driven by customer insight
Customers do not expect to have to repeat the information that their banks should already know about them every time they interact with their bank. When they go onto Amazon, Spotify or any other digital native business they expect tailored recommendations and therefore they should be able to expect the same from their bank. Underpinning the recommendations that these digital native organisations make is real time analytics.
Many banks have large and sophisticated analytics teams, however they are almost exclusively working offline i.e. not based on current, real time transactional data let alone the masses of amount of data that customers generate from their use of social media.
The digital challenger bank will be driven by real-time customer insight and predictive analytics that has drawn on structured and unstructured, internal and external, transactional and social data. This will allow them to provide a far better service than the incumbent banks can.
Available 24x7 365 days a year
Customers do not want to do their banking when the bank says they can. They want to be able to do it whenever they want to do it from wherever they are in the world. This means that banks need highly resilient, high performance IT infrastructures.
The costs to own, manage and run such an IT infrastructure is likely to be prohibitive for almost all challenger banks except for those with the deepest pockets. However the smart challenger will not look to own this, but rather give responsibility for delivering this to organisations whose core competence is delivering this type of service.
You only have to look at the hundreds and thousands of small businesses that rely on Amazon Web Services to host and manage their websites allowing the SME to focus on their customers to realise that ownership of IT is no longer an essential part of running a successful business.
Omnichannel
An ugly word and one that doesn’t encapsulate the full meaning of what customers want, however as it is in common usage the one that is used here. Customers wants to be able carry out their financial services transactions using any channel whether it be in a branch (yes some customers still want to use them despite what every Fintech evangelist says), Apple Watch, mobile or tablet. Not only that they want to be able to move around channels during a financial transaction seamlessly without having to re-enter data or waiting for one channel to catch up with another. The way that the experience of interacting on the channel is presented must be in the context of that channel. Too often banks believe they have achieved this when they have simply automated a form on a mobile device.
Without offering a functionally rich mobile experience a bank cannot be a digital challenger.
A digital challenger bank should have a contextual presence on all the channels that their customers want. However some digital challenger banks, for instance Atom (mobile banking), will choose to support only some channels  and so will dictate the customers that they will attract.
Agile
The one certainty in banking is that there is no certainty. Who could have predicted five years ago that largest taxi company in the world would own no taxis? The pace of change means that no one can predict how financial services will be delivered in five years let alone any longer than that. This means that for the digital challenger bank the most important competence is agility. Agility is a core weapon that a digital challenger bank needs to have to overcome the incumbent banks many of whom are saddled with legacy processes enforced by legacy IT.
One significant way of addressing agility is by the use of standardised software operating in the cloud. The reason that this aids agility is that whereas typically on premise software is updated once very eighteen months by half of customers, cloud software providers are able to automatically update the software as frequently as once a quarter or whenever needed. This means that a challenger banks that uses standardised software can adapt its customer proposition far faster than a similar organisation with an on premise solution.
The need for agility has a fundamental impact both the way that the business is run and how it is supported by IT. A unified, simplified business and IT architecture provides an advantage for a digital challenger bank. Picking best of breed solutions without the context of an overall architecture brings the danger of building a new inflexible legacy. Even with the benefits of an overall architectural framework it still means that there will be high amounts of integration effort.
CRAMS
The IT and consultancy industries are full of acronyms, but for a digital challenger bank to be more than a nuisance to the incumbent banks then it really needs to adopt Cloud, Real time, Analytics, Mobile and Social technologies.
While the incumbents can also adopt these for the digital challenger bank to succeed it must be a master of agility.

Wednesday, 19 November 2014

Why Big Data and analytics aren't the answer for banks

‘Big Data’ and ‘analytics’ are amongst the most over-used and abused terms currently in the business world. They are often sold as the panacea to all known problems by snake oil sellers across the globe. Banks should focus on true insights and consequential actions to differentiate themselves and take an industrial view to data and analytics.

Big Data and analytics have generated lots of revenue for hardware suppliers, software providers and consultants. They have also created lots of jobs for people with skills ranging from basic statistics to advanced mathematical modelling skills. What is highly questionable is whether all this expenditure has generated value for the banks that have invested in them?

Like many new business philosophies and technologies the approach banks have taken to adopting them is to build them in-house. Just like when computers first emerged and individual departments took it on themselves to buy their own computer, hire their own programmers and write their own code to address their department’s specific requirements (as an aside, It is one of the reasons why so many banks still today have such dysfunctional IT departments and systems), banks don’t appear to have learnt the lessons from the past and are adopting the same approach when it comes to data and analytics. Functions such as risk, mortgage underwriting, card product management, marketing, finance and treasury are creating their own local data marts, hiring their own data scientists and modellers and buying their own query and advanced analytics tools. They are building models, sometimes in inappropriate tools, with inadequate testing that the bank’s executives are making critical decisions based on the output from them.

The fact that individual departments are doing their own thing is very cost inefficient is the least of the problems with this approach. Even for banks that have elected to go for a Centre of Excellence operating model for data and analytics whereby a central pool of data and analytics experts provide services to whole bank there is a fundamental problem with this way of addressing data and analytics.

Building models in-house is predicated on the basis that every bank is so unique that the models will provide differentiation from the competition. However banking, and particularly retail banking, is based around standardised products with standardised ways of underwriting those products, standardised ways of funding the products and very largely standardised way of moving the customer’s money. Therefore spending large amounts of money hiring expensive data scientists and modellers and then lots of time building models when there are standard models available to either buy or pay for the use of from the likes of Experian, SAS and other data and analytics specialty firms makes no sense. Not least of all because true data scientists need to be continually fed interesting and challenging problems to crack (something few banks will be able to consistently provide enough of while specialty firms will be able to) otherwise they get bored and stressed – a bit like caged lions that are fed raw meat rather than having the excitement of the hunt.

Unfortunately the peddlers of Big Data and analytics solutions don’t point out to their customers and the IT users who buy their solutions don’t acknowledge the critical fact that:

Data and analytics without context and insight is of no value to a bank.

Insight is an unfortunate word because many banks take it to mean having a better understanding of what is going on inside their banks. However that is only the half of it. As critical is to have an understanding and the context of what is going on in the environment that the bank is operating within. What are the competitors doing, what is happening and could happen in the macro economic environment and how would that impact the bank’s customers are just some of the potential questions that need to be answered to create insight. If there had been a better understanding of some of these questions then it is possible that the financial crisis of 2008 could have been avoided.

However insight of its own is not enough. A number of banks across the globe could rightly claim that they have teams of data scientists who like the PreCogs in the Tom Cruise film ‘Minority Report’, who were able to predict crimes before they were carried out, know so much about their customers that they can predict what they will do next. However having that knowledge but not having a means of sharing it in a simple and usable way with the banks’ systems and the people who use those systems means that it is of no value at all.

Insight with the ability to know the ‘Next Best Action’ and execute on it is what will define the banks that will emerge as the winners.

This ability to apply data and insights to bring about great outcomes should not be limited to use with customers but should also be applied to other areas of the bank such as pricing models to allow personalised offers, to fraud detection, to identify money laundering activities and to make better funding decisions. The list of areas where this could be applied to banks is almost limitless.

However what it requires is a very different approach to data and analytics then is largely adopted today. It needs to be driven down by the desired business outcome with the data required being seen as the very last thing. It needs to be driven by the business executives not from IT or worst still technology vendors. It needs to be driven as an industrial process rather than as a cottage industry. Banks need to understand that where they will be able to differentiate themselves from their competitors is on their insights and how well they execute on those. For the rest they should look for best in class products and services for data and analytics from organisations that are truly expert in those areas.