Bank 4.0 Read online

  This begs the question: if products have to make way for contextual experiences what does a bank org chart look like? Where do all the products and channels go?

  BBVA will be a software company in the future.

  —Francisco González, Chairman and CEO BBVA, Mobile World Congress in 2015

  The Bank 4.0 organisation chart looks very different

  If you want to truly understand the impact of first principles you need to look at the step change effect that first principles thinking has on ecosystems.

  When the automobile was invented the dominant form of urban transportation was horses—within 30 years that had all changed, along with it the shape of cities, manufacturing, and support systems around cars. When the telephone was invented, it rapidly changed communication. The same is patently true with the impact of the iPhone—not only has it changed the way people think about their “phone”, but it created entirely new ways of doing business via apps, it changed the music and taxi industry markedly, it changed the hours we spend on our devices, and it changed the way people consumed and created content. The businesses that emerged on top of mobile didn’t look like those that came before them, and some of those businesses are now worth billions of dollars, and yet they wouldn’t exist without the smartphone.

  Just take one small area of the smartphone’s impact—photography. Prior to commercial cameras only a few million photos had ever been taken. When Kodak introduced the Brownie in 1900, it rapidly changed photography, with over a billion photos a year being taken by 1930. The emergence of digital cameras meant that by the year 2000 we were taking about 86 billion photos a year across the planet. But then the smartphone arrived. In 2017 it is estimated13 that 1.2 trillion photos were taken, and we’ll be storing 4.7 trillion photos through our smart devices and on the cloud. Of the 1.2 trillion photos taken in 2017, only 10.3 percent of them came from digital or conventional cameras; 85 percent of those photos will come from smartphones.

  Welcome to the broader impact of first principles thinking. It’s why Tesla is not just about building electric vehicles (EV), but also about supercharging networks, solar-charging stations, and autonomous systems.

  When we think about the impact that the smartphone has already had on banking, it is clearly significant. 2015 was the first year that more people used their smartphone to bank than visited a bank branch, call centre, ATM or bank website. It took just eight years for the smartphone to become the dominant form of day-to-day banking access14. Despite that, we’ve not really made major changes to the bank org chart to cater for this behavioural shift. Today, heads of mobile, CDOs (chief digital officers) and the tech guys have moved up the org chart hierarchically (sometimes), but structurally the rest of the bank has not significantly changed. But as indicated by Francisco González’s quote above, as technology comes to dominate the banking experience landscape, the organisation chart must change to reflect entirely new operational competencies.

  What’s missing?

  When I’m asked by bankers who they should hire for what’s coming next, I always begin with “Stop hiring bankers!” The skills needed to be competitive in the future won’t require any banking experience, but these new skills are what banks could live and die on. Over the past few years I’ve been surveying my FinTech friends on what hires will be most critical to the growth of their businesses and watching job boards and the like. The qualitative research I’ve carried out has come up with just a few of the jobs that will be considered critical in revenue and capability growth in financial services over the next five years or so.

  1.Data Scientist

  Data scientists are a new breed of analysts and data architects who have the technical skills to solve complex problems and to answer big questions. More often than not, data scientists find themselves exploring exactly what problems need to be solved, based on where the data takes them. They’re part mathematician, part computer scientist and part trend-spotter. They sit between the business and IT worlds.

  2.Machine Learning Specialist

  Machine learning or algorithm specialists are specialist programmers, architects and modellers that built the systems that use cutting-edge artificial intelligence. They design ML algorithms, source data, train, evaluate and deploy ML models, and work to develop predictive and cognitive processing capabilities. The ability to test systems quickly and deploy at scale rapidly are key.

  3.Experience Designer/Storyteller

  Experience designers and/or storytellers can place the bank and its utility in customers’ lives through technology in the most frictionless manner. They look at aspects of design like interaction and interface design, rapid prototyping and usability to develop highly compelling, low-friction engagement. The ability to think differently, circumvent existing processes and policies and challenge the organisation are key.

  4.Behavioural Psychologist

  When it comes to designing interactions and new systems, the capability to understand how someone will react, what behavioural models they will apply in certain scenarios, and the use of conscious and sub-conscious triggers to gamify behaviour will soon become levers for short-term and longer-term engagement and loyalty.

  5.Blockchain Integrator

  As blockchain becomes critical to money movement, IoT wallet capability, identity passporting, trade finance, etc—the core systems of today will not cope with the level of change thrust upon transaction banking. Thus, as banks can no longer afford the time for full core replacements, cloud integration of blockchain capabilities that extend the bank platform and allow integration into new plumbing will be critical.

  6.Compliance and Risk Programmer

  All compliance, law and risk will be embedded in automated processes before long. This will shift the functions of compliance and risk away from human processes and bank policy, to a system of monitoring, alerts and action triggers. Within 20 years most regulators will also have moved to similar systems—so the bank AI will talk to the regulator AI.

  7.Community Advocate

  Community advocates look at placing the new experience in the best places to get the fastest traction and scale. Community advocates look at consumer trends, network effect and emerging technologies to see where the bank needs to be most active in the future to engage customers, just like planners used to look at foot traffic and vehicle flows in a city to decide where a branch needed to be physically situated.

  8.Identity Broker

  In the future non-bank entities will have much, much better identity, heuristics, biometrics and behavioural information than that of banks, so we’ll need brokers to identify customers accurately and in real-time. Identity brokers will construct the new IDV (identity verification) systems that replace our current KYC (know your customer) processes. This will be about real-time customer profiling and verification, not onboarding through a process.

  I refuse to add Robot Psychologist, Emoji Translator and Customer Experience Ninja to this list. However, I might be tempted to add an AI Ethicist, for example.

  Some roles I’ve left out that are critical for future development already exist in numerous banks, but they will become increasingly important in building a bank platform that is competitive. They include business analysts, venture capital teams for investing in FinTech, those that manage and grow technology partnerships, hackathon and incubator labs, etc—basically the ability to rapidly grow the bank’s technology capability without building it internally. The real challenge for banks, of course, is that if you’re a tech graduate coming out of a university looking for a job today, would you be looking to work for a startup, a tech major like Facebook, Apple or Google, or would you want to join a bank? Recruiting these skills will surely be a challenge for financial services organisations culturally, as we’ll discuss in later chapters.

  Technology partnerships with organisations outside the bank will become increasingly commonplace as banks realize that they no longer have the technology expertise that outside actors do, and that to build
it themselves will cost much more and take much, much longer than simply partnering with a FinTech or tech firm that excels at that same competency.

  At Moven we call this the ability to bend space and time for our partners15. To deliver the same or better technical or customer experience capability the bank requires, but at a fraction of the time and cost it would take to deliver using internal resources. I know there are bankers who will remain sceptical about this assertion, but let me throw down some home truths here using Moven as an example.

  After we launched Moven in 2013 we had an approach from one of the big four Australian banks. They engaged with us multiple times, we presented to them in Australia, they flew to New York twice to meet with us, and they even looked to engage us offshore in Asia on some specific projects. They visited our partner bank TD, to check out Moven’s white label product we launched for them branded “TD My Spend”—one of the most successful product launches in TD’s history, according to their CEO16. But over time it became clear that even after two to three years of engagement, that they were tire-kicking, trying to glean as much technical detail as possible about our product roadmap, but they had no real intention of buying our services or partnering.

  Then in 2015 things got interesting when they recruited our chief product officer, offering him in excess of US$500k per year to leave Moven. Over the next two years they proceeded to spend a reported $20–30 million to finally launch their own “financial wellness” capability called… yes, you guessed it My Spend—very original fellas.

  Yes, in two years at a cost of $20+ million they launched their own version of Moven’s financial wellness, which they could have launched in three months for under $1 million if they had partnered with us rather than going it alone. Not only that, but the features of My Spend reflect essentially the capability Moven had in 2015, and today we’ve advanced features on our product for behavioural savings and contextual credit that will likely cost them another $20–30 million to develop and take another two to three years. Partnering with us could have given them that capability today.

  Now I’m sure a player at that leading financial institution will have a very sound explanation for why they went down this path, and they’ll talk about how agile they’ve become. But at the end of the day, it cost this bank 20 times more and took them 10 times longer to build it internally than if they had simply partnered with us. Now I’m not telling you this story because I’m upset they didn’t partner with us, they had that right. I’m telling you this because in hindsight it was clearly a poor economic decision. Should this sort of case really be a surprise, though?

  Who is going to be faster and cheaper at building new tech for financial services? A company that only focuses on tech, has a smaller more agile structure, works with multiple FIs around the world and has to answer to a board full of venture capitalists? Or a bank that has to deal with legacy systems, compliance and risk issues, and significant challenges with recruiting the right skills to build these new technologies in the first place?

  More and more this will be a question that the CEOs of major institutions are going to have to answer. Do they retool to become an agile, technology organisation, or do they look increasingly to partner with those that are technology-first, and are cheaper and faster at innovations?

  Anecdotally a story is doing the rounds right now that Jeff Bezos is big on AI and data science, so big that he told his team he wanted to recruit a thousand new data scientists and to do whatever it took to get them. Reportedly, this effort gleaned only 600 new recruits, working for one of the hottest companies on the planet in this arena, paying better than average salaries. Now think about a bank trying to recruit just 20 or 30 data scientists, and tell me they’re going to be more effective than Amazon. Tough problem to solve—and one that may require even sponsoring university scholarships or creating internal training programs to home-grow those skills.

  This all speaks to the broader capabilities of a bank. How do you organise these new competencies in a 21st century, Bank 4.0 bank? Do you simply create new roles in the existing business, or does it require reorganising the business to be more effective?

  An exercise like this in organisational design theory could take many years of rooms full of academics to crack. Explaining this is beyond the parameters of this book, so instead let me try to take a shot at it in simple competency terms. Let’s start with what a typical bank organisation chart might look like today, in very general terms.

  Figure 4: Representative organisation chart of a commercial bank today.

  An organisation chart in today’s modern bank reflects an evolution over decades—incremental change as a result of market focus, increased regulation, and technology impact. In reality it’s not all that different from an organisation chart you might have seen 30 or 40 years ago in banking, but there have been new competencies and capabilities inserted into the structure. A first principles approach to banking is necessarily going to have a significant impact organisationally.

  What is most noticeable about an organisation chart of a bank in the future is that the bank functions as a “platform”—it has the ability to surface the underlying utility and capability of the bank. In a Bank 4.0 organisation it is not omni-channel capability that is the key, it’s complete channel agnosticism, engagement and revenue-pragmatic focus. In a world where you compete on utility, product structures and channel capability are what lie under the surface, whereas the tip of the iceberg is all about experience mechanics. In an experience world, the whole business is geared towards great banking experiences—it’s not a channel-based afterthought where you retrofit a credit card into Alexa so a customer can make a payment on time.

  When it comes to AI, which will by nature seek to automate much of what we have hard-coded in legacy architecture and process today, this won’t just be a department that sits under IT. Artificial Intelligence will likely eliminate whole swathes of the org chart as it stands today, but AI and data mining and modeling will power elements of almost every interaction. If you are tempted to think of AI like you do your bank’s website (a piece of tech), then iterative thinking (design by analogy) will dramatically limit your ability to compete because you’ll end up with competing AI projects, data silos, competing teams, fractured budgets, and inconsistencies in process approach. You’ll have highly automated processes in retail, but tons of retained friction in corporate banking, because the retail guys will get more budget.

  The table on the next page breaks it down into potential core competencies by functional area, showing how revenue might be delivered and people and resources managed in the near term:

  Table 3: Corporate function versus core competencies by functional area.

  The organisation becomes less hierarchical and more collaborative as product structures and channel capabilities don’t compete for budget, but are just levers for engagement, relationship and revenue. This approach, in theory, allows for much greater leverage of technology agnostically across the utility spectrum and allows for use of distributed technologies like blockchain or IP-based solutions from partners, without running into sacred cows or silos. The is a much more agile banking organisation structure, one that can compete side-by-side with technology pure play competitors. The modern banking organisation is focused around customer delivery, whether retail, SME, corporate or otherwise. As such, the organisation becomes much more mission-focused when it comes to revenue delivery.

  When you look at the likes of Ant Financial and others attacking this space, they have business units around core competencies, but not organisation charts focused on product. Their organisation chart is unconventional, focused on KPIs that measure active users, daily engagement, cumulative actions such as borrowing over the lifetime of the customer, and year-on-year growth. Their collective business unit growth is designed to speed up the reach of their network as it grows17.

  This leads us to think of the new Bank 4.0 organisation structure not as a chart showing strategic business
units, but as core competencies across the organisation that can share missions, customer goals and so forth in a matrix form that a typical bank today would encounter huge challenges to accomplish.

  Figure 5: The Bank 4.0 Core Competencies Chart (circa 2025).

  In terms of competencies, we see that “banking” per se just becomes one of the competencies of the bank, and in equal terms Delivery, Business Operations and Technology Operations are just as critical.

  While we might see today that AI and something like Amazon Alexa or the latest mobile app would sit under the purview of the information technology or digital team, in this new world delivery capability becomes a customer experience and engagement platform that is far reaching—essentially the new driver of revenue, relationship and reach. In this new model, technology operations become the underlying platform capabilities that are needed to surface utility and experiences in real-time. Instead of traditional operations, we have technology and business operational competencies, as both are just as critical, but require very different skill sets and division of labour.

  A few new areas emerge that you wouldn’t find on an organisation chart today. Namely, Research & Development, Partner Management & Operations, Data Modelling, Experience Design and, of course, Artificial Intelligence. Many of these functions are counter-intuitive for the banks that have iterated from the Bank 1.0 world—their immune systems of internal core systems, legacy process, compliance, and entrenched product teams are extremely likely to push back against these new strategic business units. If these competencies aren’t built, however, the ability to deliver revenue in a real-time tech-first world will be tough.