Bank 4.0 Read online

  8See https://www.wellsfargohistory.com/internet-banking/.

  9APR or Annual Percentage Rate, is the standard moniker for the interest rate paid against a savings account annually, or in the case of a credit card the annual rate charged for balance carried on the card.

  10See “This is the end game for autonomous cars” by Marc Hoag—https://www.linkedin.com/pulse/end-game-autonomous-cars-marc-hoag.

  11Source: The Guardian, Stuart Dredge, 18 March 2015; “Self-driving cars could lead to ban on human drivers”—https://www.theguardian.com/technology/2015/mar/18/elon-musk-self-driving-cars-ban-human-drivers.

  12Source: “The Precarious State of Family Balance Sheets”, Pew Research, January 2015—http://www.pewtrusts.org/en/research-and-analysis/reports/2015/01/the-precarious-state-of-family-balance-sheets.

  13Source: Press Release—https://www.moneyadviceservice.org.uk/en/corporate/press-release-65-of-consumers-are-exposed-to-unplanned-financial-shocks.

  14Source: University of Scranton Research, 2013.

  15Source: Wall Street Journal, Conor Dougherty, Dec 2010, “Reward Cards lead to More Spending, Debt”.

  16Alibaba’s voice system.

  17Source: Retail Dive, Starbucks enabling ordering via voice in Alexa-enabled Ford vehicles, March 2017—http://www.retaildive.com/news/starbucks-enabling-ordering-via-voice-in-alexa-enabled-ford-vehicles/438730/.

  18Source: https://techpinions.com/there-is-a-revolution-ahead-and-it-has-a-voice/45071.

  19The Fourth Transformation: How Augmented Reality and Artificial Intelligence Will Change Everything, by Robert Scoble and Shel Israel, Patrick Brewster Press (December 2016).

  Should design have to wait for AI and device capability to catch up, or should we rethink design in a contextual world, where banking is embedded in our day-to-day life? Are banks even capable of evolving the role of data in decision-making and consumer engagement, such as categorized transactions, geo-location and behavioural triggers?

  Are banking chatbots the future?

  According to a report released by Juniper1, chatbots will be responsible for over US$8 billion of cost savings by 2022. Are these savings to the consumer or for the bank?

  I think clearly we would have to answer, the bank. Today, chatbots are regarded by most banks as a potential cost savings mechanism designed to replace call centre personnel. Yet worse, the companies developing chatbots have market and investor pressure on product, preventing them from reimagining customer interactions through the prism of human emotion and real customer needs.

  Investigating how a consumer truly feels, what drives them and makes them happy is time- and resource-intensive. Most of the FinTech providers working on chatbots generally cannot justify undertaking that sort of research either. Instead, they plough ahead, developing incremental AI that tends to focus on product-based and marketing-heavy advice, rather than something more valuable to the end consumer.

  As per Brett’s earlier chapters, the problem here is that most chatbots are derivative of branch-based banking or call centre interactions, thus most of the scenarios or use case resemble current call centre type support questions or cross-sell marketing offers. A first principles approach to a chatbot would start with the day-to-day problems that plague customers around money, and the role of banks in facilitating solutions.

  Over the past few years, with the emergence of Human Centered Design practices, industry press and research organizations have repeatedly shamed incumbent banks for not investing enough time and effort into reducing friction in engagements. Brett makes a strong case at the start of his book for kick-starting the design of banking from scratch using first principles design thinking. A strong argument in support of this proposition is that when we research products designed with the insight of consumer’s needs, they tend to be significantly more profitable than those built without those considerations. Despite it making good business sense, banks have been unable to deliver on that, hampered by compliance issues and heavy legacy in terms of organisational culture, process and technology.

  The FinTech companies that are building AI-powered voice banking or chatbot applications have none of those cultural legacy problems, yet all too often they put immediate operational functionality ahead of designing a product that recognises and acts on emotion.

  “Financial chatbots” are a worrying subsection of AI that is on the rise. The separation between a real, intelligent assistant that makes meaningful contributions to our lives, and a dumber version that can simply infer we mean “interest rates for savings” and “potential gain/loss scenario” when we query, “How much will I get charged if I leave my overdraft in the account”, should not exist.

  To become truly relevant and make an impact on behaviour, AI will have to become a day-to-day companion. It will have to be an entity that understands not only the client’s actions as inferred by location or spending patterns, but their intent, their overall emotional state and even their deepest secrets—and be able to steer their state of mind towards where they are inclined to make better financial choices, instead of solely offering dry, meaningless information. Obviously financial coach will be only a subset of the capabilities that a voice based AI or companion from Apple, Amazon or Google has, and yet banks treat chatbots like Apps today. They think that people will come to their chatbot to interact instead of Siri or Google Home. That’s the height of arrogance if you ask me.

  The builders of chatbots shouldn’t be asking themselves, “How do I implement geo-location push alerts this month?” but “When and how do I use the notifications based on location, ensuring the client gets a sense of gratitude for having been notified contextually of a potential gain, instead of just annoyed if they perceive it as mindless marketing?” They should consider how to become that trusted and invaluable advisor that the consumer turns to when needing help with their money.

  AI with this capability is still a few years away. In the meantime, banks could tighten their game in bringing something that has been well within their reach since the advent of PFM in 2009: notification-banking, also known as “Contextual 1.0”. Irrespective of the nuances, the overarching principle of this involves offering the consumer relevant financial information at the right time or place through the form of notifications on their mobile device. As the platforms mature, voice and augmented reality will provide further reach for contextual notifications.

  At its core, being able to provide contextual money advice has one major prerequisite: that the bank has the information to both trigger the notification and provide the right advice. There is a substantial—and in this case, defining—difference between “data” and “information”. Banks do capture consumer’s financial data (and could capture much more of it). Whether they process it in any way to extract meaning, inference and relevancy and turn it into “information” is another matter altogether. An overwhelming majority of banks do not.

  In my Emotional Banking™ method, I spend a lot of time studying why this happens, why banks do not explore the psyche of the consumer enough to understand how paramount the need for financial information is. The reasons are complex and are chiefly rooted in the culture of the organisation. But this also gives rise to practical impediments, such as the fact that most banks today are not equipped to either collect or collate data in a fashion that would allow them to turn it into relevant information that they can serve the consumer through well placed notifications.

  While being notified of an amazing opportunity to save on a favourite item as you pass a shop would be great, today the bank has no idea that item is a favourite—or if you’re passing said shop. While being informed that by forgoing the mythical cup of coffee you’ll be a week closer to your savings goal would be potentially useful, today the bank has no idea you’re about to have that cup, or what your savings goal is. The bank simply can’t advise you in respect to spending less on a certain type of expense or for thinking of retirement by starting direct payments to a private pension plan, because it does
n’t actually know what your current situation or drivers are today.

  Transforming “data” into “information” requires not only storing it, but having an ability to effectively, efficiently and accurately analyses it—with the ability to categorise transactions and behaviour being at the core of financial data analysis—and then having a way to access and transmit that information as close to real-time as possible. Each of these steps is a sine qua non condition to achieving effective notifications that offer relevant information that make a real difference in someone’s financial life in lieu of meaningless, ill-timed tidbits of data.

  Once banks learn how to slice and dice data and realise the promise of Contextual 1.0, real advice will follow shortly thereafter (2.0)—and it will be based on an ability to tap into other IOT-related data sources to infer wider behavioural cues for increasingly meaningful context.

  Timing: Information is not received and consumed the same way at all times, so notifications about finances will have to become sensitive to that factor, in addition to location. Delivering an encouraging message about one’s savings is immensely more efficient when the consumer is particularly receptive and ready to receive it, such as a weekend morning, as opposed as to an inconvenient time in the middle of their commute. Taking into account the consumer’s psychology and style will also be critical in terms of messaging.

  Wider life context: Smart devices hold and are able to access data that goes far beyond mere transactions such as health parameters and emotional clues. In Contextual 2.0 and its AI component, banks will have to understand how to use this data to build addictive relevance in outlining and assisting Money Moments for their consumers.

  Which of the following seems more efficient?

  Figure 1: Examples of smart device engagement.

  Consumers will receive this type of financial companion within the next few years, whether it will be from their banks or, most likely, other technology companies that have developed the capacity to aggregate financial data and make wider, relevant, contextual sense of it. If you want to be part of the Bank 4.0 revolution, you need to start working on the broader data requirements that will power this type of emotionally sensitive and relevant banking.

  Endnotes

  1https://www.juniperresearch.com/press/press-releases/mobile-banking-users-to-reach-2-billion-by-2020.

  4 From Products and Channels to Experiences

  We still have one million people coming to our branches every day, and they need that channel. Some need it to transact, but a lot of them come in for advice and we want them to do that. So, we need a certain footprint of financial centers.

  —Paul Donofrio, CFO at Bank of America

  The new “network” and “distribution” paradigms

  Let’s propose a binary question for the digital age. In 10 years time, who do you think will have a greater chance of survival—a bank wholly dependent on branches for revenue and relationships, or a digital pure play, challenger bank wholly dependent on digital channels?

  If you answered a branch-based bank, I think the facts suggest a different reality1. While branches aren’t going to disappear in the next 10 years, the relative importance of a bank branch for day-to-day banking is most certainly in decline. In December of 2015, Bankrate.com reported that 39 percent of Americans hadn’t visited their bank branch in the last six months, and a report from CACI in 2017 predicted that visits to branches are set to decline by another 40 percent over the next five years. This is a global phenomenon in developed nations.

  We’ve seen drops of 30 to 40 percent happening over a few years, and in some of our traditional bank branches around Australia in some areas we see as little as five or ten people [visit] a day, and the economics are very difficult… But what’s happening is the growth in digital interactions is phenomenal. So we’ve gone from zero to 11.5 million transactions a month on a…smartphone.

  —Michael Cameron, CEO Suncorp Bank, The Courier Mail interview, November 2016

  The reality is that by measuring just one simple metric, it’s very easy to tell the future of the bank branch and how its importance is diminishing over time. That metric is the average number of visits per customer per year to a bank branch in your network. If you don’t know how to get that metric and you work in a bank, it’s easy—take the number of products sold, applications lodged or transactions made per customer per branch over the course of a year, but count a maximum of one interaction per day as a “visit”2.

  You’d be surprised3, but the majority of banks I’ve worked with not only don’t give out this number, but they neglect even to measure this internally, relying instead on the number of product applications per branch per year as their core distribution effectiveness KPI. The data, though, is irrefutable. My bet is in every bank in the developed world when measured between 1990 and today you’d see a decline of somewhere between 60–80 percent in respect to that single metric annually. Meaning, that if you expected to see a customer visit your branch 10 times a year back in 1990, today on average they’re visiting less than two or three times per year. I’d also argue that a large percentage of those visits would be false positives, where the bank or compliance requirements mandate a customer visit the branch versus using an alternate channel; for example, where you only allow mortgage applications for new customers through a branch, or where a bank requires you to visit if you want to restore access to internet banking4 after forgetting a password. Recently, Chase required me to visit a branch in the US to do an ID check because I tried to do a wire transfer on my account for the first time in some months.

  These examples I’ve given are all false positives—they certainly do not represent an argument for continued viability of the branch. Why? Because as soon as a neo-bank competitor establishes a benchmark competency for these same capabilities without requiring a visit to a branch, then your bank will eventually be measured against that standard. Keep in mind that none of these examples I’ve given are required by regulation either, but they are in place because of an overly conservative internal compliance process.

  For many banks, however, their distribution platform is their branch network: it’s their access identity; it’s the way they are embedded in the community; it’s where their branding sits; it’s how they measure customer excellence, experience and engagement. When bankers used the terms “network” or “distribution” in the 80s, 90s and 2000s, they knew internally they were talking exclusively about branch network and branch distribution. From a strategic perspective, while that has obviously shifted in most large retail banks today, it’s a very hard habit to kick—all that revenue from the branch. As Michael Cameron alluded to above, if visits per customer to your branch network continues to decline, branch economics for all but the most active branches will fail, as will revenue.

  Now, for those that really get upset when I talk about changes to branch networks, let me state this for the record: I don’t think branches are completely dead, nor are they ALL going away, but by 2025 most branches will become much more difficult to sustain economically as we see alternative approaches to banking gain traction. These alternative approaches will consistently demonstrate branches don’t deliver revenue and relationships at the same scale or cost effectiveness as digital. Once the market starts to regularly compare a neo-bank like Moven or Monzo, a Tech giant like Amazon or Alipay, or a FinTech like Acorns or Betterment with an omni-channel bank with massive real-estate investments side-by-side, branch networks will come under huge pressure to close because of climbing acquisition costs and reducing differentiation. Within a few years stock market analysts will simply ask whether branch networks are a sustainable way of doing the business of banking. Once that happens, it won’t be long before analysts are discounting bank stocks for their excess real estate. Right-sizing branch networks will be forced upon publicly listed banks. Banks reliant on branches will have nowhere to go, they’ll just continue to argue branch relevance while the shrink. In the same way that retailers argued pe
ople still wanted to come to their stores, while retail stores were closing by the thousands.

  The problem for banks is that in this new experience world, network is a function of technologies that deliver capabilities in real-time at scale, that anticipate or predict your needs, that are embedded in your world, that reframe the utility and import of banking in your day-to-day life. This has very real consequences for the future of banks.

  In July 2017, Kakao, a Korean internet platform that has the largest messenger app in the country and runs a service like Uber called Kakao Taxi, launched their own internet-only bank—Kakao Bank. In just five days Kakao had opened more than one million accounts5, attracting over half a billion US dollars in deposits, and they claim they would have been able to open more had their technology not been overwhelmed by the demand.

  This is increasingly the standard the new internet banks are being held to, but Kakao, Tencent, Amazon, Uber and Alipay have advantages over digital pure play and incumbents alike. They can apply network effect from their existing platforms to functions like deposit taking and payments. It’s not just that they have access to millions of customers, but that those customers will use their networks for payments, commerce and other bank-like stuff. When those platforms start to offer banking utility, it’s an obvious evolution of their network utility.

  In 2004, whenever I had to pay my rent, I would go to my bank, queue, withdraw my rent as cash, walk it across the street to my landlord’s bank, take a number and queue, and then eventually deposit the money into his account. Today, I pay my rent using Alipay from Alibaba. I invest using WeChat from Tencent, and I bought a mutual fund from Baidu. The landscape has completely changed.

  —Kapron, A Shanghai resident talking banking in China; Bloomberg Markets6