Daily Fintech Advisers helps financial service providers to compete in a digitized world. This site is our research platform; like open source, this research content is free forever and we charge for the customized advisory service.
Banks go through three maturity levels as they survey the Fintech start-ups:
- Level 1 = Incomprehension. It just all looks so strange. This can translate into two different gut reactions that encourage passivity:
“They want to eat our lunch, grr, but nothing we can do about it”.
“They are a passing fad, phew, pleased we can ignore this”.
- Level 2 = Transactional. Most banks are in this phase today, working through Corporate Venture Capital (CVC) and Accelerators. Some of these deals can be highly lucrative and they fit within a bank’s organizational comfort zone. However they do not change the bank at any fundamental level – they do not “move the needle”.
- Level 3 = Strategic. Daily Fintech Advisers help Banks get to this level. This is where banks enter new markets with new digitized products that create meaningful growth at both the top and bottom line.
We usually start by seeking strategic clarity with this question:
“Does your bank want to be a marketplace or a service business?”
As an analogy, do you want to be a Mall or a Shop within a Mall?
(Some Universal Banks want to be both, but each is run like an independent business; this is the conglomerate model that is only applicable to a handful of banks).
When you look at the growth rates and valuation of marketplaces such as Lending Club, it is easy to get “marketplace envy”. However this question is a reality check.
“Q. Which business is more valuable, Charles Schwab or NYSE?
A. Charles Schwab is a service business valued around $43 billion, which is a lot more than NYSE, which is a dominant marketplace that was acquired by ICE for $11 billion.”
One reason that banks get confused looking at these marketplaces is that in the early days of a marketplace, they act like service businesses. Think of the classic story of the AirBnB founders going door to door in Manhattan to recruit the first customers. Lending Club in its early days was billed as P2P Lending where it was a service business to individual lenders and borrowers. Based on that initial consumer transaction they morphed into being a marketplace where other firms add value to their data.
So, don’t knock a service business. The confusion arises because in the traditional tech business, “service business” meant being a low-margin business where scaling revenues meant linear scaling of headcount. That is rightly given a low valuation multiple by investors.
The new digitized services opportunity is what Daily Fintech Advisers call Rebundling (described in this post).
These rebundled services have some functional complexity. So it usually pays to add humans into the delivery process. The aim of the technology is to automate the commodity layer (e.g. asset allocation) and empower humans to deliver the complex higher value layer (e.g. finding great asset managers and profitable customers). Those humans may be working in branches or in call centers; or travelling to see the customers with their tablets. What matters is these front line knowledge workers are empowered by:
- A technology platform. This combines internal customer analytics with external market analytics to provide a predictive, personalized, seamless customer experience where like ye olde shopkeeper, the vendor seems to anticipate your needs.
- An organizational framework. This encourages decision-making at the front-line. This is where Banks should study Zappos.
Specifically, banks should look at the Zappos experiment in “Holacracy”, which:
Replaces today’s top-down predict-and-control paradigm with a new way of achieving control by distributing power.
For the official Zappos view of Holacracy click here. For a blistering attack on Holacracy at Zappos by Paul Carr click here.
I was intrigued enough by Holacracy to consider it as a model for Daily Fintech Advisers, but it actually looked too heavy-weight for our needs; my concern was that Holacracy could quickly degenerate into politically correct bureaucracy. However I think Paul Carr has it wrong when he attacks the Zappos employees as not being super smart. In a large service driven business you need a lot of people. The tech and the process has to be super smart so that each individual does not need to be super smart.
Holacracy is targeting the right issue, which is empowering front line workers to make decisions. However I am not convinced that Holacracy is the right way to do this. There are simpler, less political ways to achieve this – if you have the right technology.
Here is the core problem:
Front-line knowledge workers have to operate based on what actually just happened, not what a manual tells them should have happened.
IT has done a great job of automating routine work, the type of work that can be neatly standardized into assembly-line processes based on a model of how the world is supposed to work. Think of those annoying call center conversations. Even after the superviser’s superviser has finally given you what you want (and the vendor has spent all that management time), you the customer feel annoyed and motivated to find an alternative. It is much better to empower the front line person to see that this situation is different and quickly and graciously offer something that meets what the customer wants. Of course that has to be measured and managed, but that is the role of technology so that management can get answers to questions such as:
- Who is giving away too much and how can we coach them to improve?
- Who is abusing this (maybe for dishonest reasons)?
- When something was given away, did we benefit in some other way (e.g more business from that customer)?
- When we did not give the customer close to what they wanted, did we suffer in any way (e.g. loss of business or social media brand damage).
The next frontier of IT is helping front-line knowledge workers, the people who really make a difference within the enterprise, to act swiftly, boldly and safely within the context of what actually just happened not just on what some manual tells them should have happened.
Helping these front-line difference-makers has become mission-critical and urgent, because the flood of real time data streaming in from billions of devices (the Internet Of Things) and millions of users (Social Media) and lots of marketplaces opens up strategic opportunities as well as massive risk. This is the era of the real time extended enterprise where we have to react too fast for traditional command and control processes.
One reaction to this reality is highly paid knowledge workers unilaterally declaring independence from IT processes. You don’t tell somebody who generates $ millions for your company to follow the same “always do A before you do B” type of process that is suitable for a junior staffer in a call center. These highly paid knowledge workers choose to use zero-process social media consumer apps and to rely upon their great experience and intuitive grasp of what needs to be done.
The IT response has been to entice these “enterprise rain-makers” in research, development, design, investment and high value relationship-building back into scalable IT processes through a range of social media within the enterprise systems. These have great value, but money is made and lost at the intersection of action and transaction and that link is broken. Social media within the enterprise systems do help colleagues to work better together, but these systems live in a silo that is separated from the transactional systems that record economic events.
Recording a transaction after the fact is essential as that may alert management to risk (and it’s mirror, opportunity) but does not prevent risk or seize opportunity – “the horse has already bolted”. This creates existential enterprise risk, because one false step can unleash a perfect storm of reputation and regulatory risk. Governance Risk and Compliance needs front-line workers to operate within a process and they won’t do that unless the processes adapt automatically to the reality of what actually just happened.
The other reaction is to order lower level front line workers to operate within the constraints of rigid “always do this, then always do that” processes that are optimized to manage small-scale risk (on the basis that small-scale risk at enterprise scale “all adds up” to big risk).
The problem is that systems that prevent small-scale risk have actually created large-scale risk.
This is a huge issue in customer service today. That one customer who has just been “given the company line”, might then send a Tweet (and, even worse, the YouTube video shot with their phone) that goes viral and brings your company to prime time in a very bad way. For an example, look at what happened when a United Airlines front-line worker followed company rules in dealing with a returning veteran (and then behaved badly as well).
It does not matter whether the damage comes from regulatory fines or brand damage; it is often both. The key is preventing that kind of action.
That single Tweet or YouTube that changed your world only did so because it resonated with the experience of all the other customers who suffered in silence or shouted into the void. These front line customer people must be empowered to adapt to what actually just happened. That is not a license to do anything; it is a sensible set of choices created by an intelligent system that creates the next step in the process within context. If the front-line worker takes the right action in front of that customer who is about to change your world, your enterprise will be on prime time in a good way that no amount of advertising or PR can buy.
The big question for IT and risk management is how do you allow that to happen in the 1% of cases when it really matters and still manage the 99% of routine transactions efficiently. This is not an easy challenge.
Great customer service does exist in banking, but it is usually the exception that proves the rule. I have had the pleasure of working with exceptional Bank Branch Managers who successfully provide great customer service despite their employer’s technology or organizational policies. That 1% exception is clearly no way to run a business. Great customer service needs to be baked into the systems and processors used by all employees.
Amex is one financial services business that seems to have got that customer-centricity at scale right. Charles Schwab is another. Neither is dependent on bank branches, but both generate customer trust (aka brand) via good customer service (whether delivered direct online or via a human).