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  • user 9:51 pm on March 13, 2017 Permalink | Reply
    Tags: banks, business model, challenger banks, , ,   

    Finding a Business Model for Challenger Banks 

    are a fascinating bunch. As varied as they are — MonzoAtomTandemStarling and other UK market newcomers — they have one thing in common: obsession with amazing customer experience, customer-centric propositions and fee transparency.

    I love these amazing propositions as much as anyone — however, I had a chance to work on a project with one of the UK challenger recently which included deep diving on a for one of the considered products in the bank’s pipeline.

    The project (along with Stephen Lemon’s quote — even though I don’t think he was addressing the challenger banks at all) got me thinking about what comes next after the amazing customer experience and value propositions? Will the challengers be able to sustain these experiences under financing and profitability pressures?

    Consider the following example — Monzo is trying to make itself useful for traveling card holders as it informs on its blog:

    “At Mondo [sic], we love to travel and hate to play games with our banks while we are away. You’ll be pleased to hear we don’t charge any fees for using your card abroad, neither at points of sale nor at ATMs. ?…We pass the MasterCard exchange rate directly onto you”1

    Or another one — Atom Bank has recently (February 2017) announced the best fixed term saving accounts proposition in the market which “annihilates” the rest of the competition as reported by This Is Money:

    Put-upon British savers have been thrown a lifeline with the surprise launch of a one-year account paying 2 per cent today…Beating the current top-paying one-year bond by 0.4 percentage points, Atom Bank has sent ripples through the savings market and provided an account which currently beats inflation.2

    We see similar amazing customer value deals emerge across challengers. What’s next for the challengers then from a business model perspective?

    Case In Point: A Failed ‘Challenger’ Bank in CEE

    A graphic example of business model failure: Zuno is (or rather was) an all-digital bank that was launched in Central Europe (Slovakia and Czech Republic) back in 2010 as a project of Raiffeisen Bank International.

    On one hand, I admit that the comparison to current UK challengers is a bit stretched ( or preposterous?).

    After all, these are different markets and admittedly Zuno was not up to par in level of innovation and customer centric approach as its UK peers are (in the end, Zuno was an outpost of an incumbent bank).

    Some of Zuno’s assets: mobile application, premium credit and debit cards (source: http://www.zuno.sk)

    Before disregarding my comparison, consider the many similarities between Zuno and its UK counterparts:

    • “Less bank, more life” was to be Zuno’s main tagline; reflecting its desired appeal to a young, dynamic and active population
    • Main propositions at launch were “customer transparency, online finance management, free current accounts and favourable saving rates”
    • Purely digital distribution (web & mobile) with no bank branches
    • 266,000 KYC-ed clients in Czech Republic and Slovakia200 employees as of March 2016
    • Approximately 800 million euros in deposits and 80 million in loans

    Ultimately, Zuno did not achieve profitability and in total lost approximately 130 million euros over its lifetime. Eventually, Zuno was shut down:, its banking license voluntarily revoked and its customer assets transferred to other banks within the Raiffeisen Group.

    What is the main takeaway from Zuno’s failure? It is not rooted in a market maturity issue or misalignment of the value proposition (in fact, the 266,000 accounts in Zuno’s markets would translate to somewhere around 1.1 million accounts in the United Kingdom).

    The failure was purely on the business model side and inability to monetize its customer base on the credit side. As Zuno’s CEO at the time pointed out, the only mistake [they made] was that the bank had not started building its credit product portfolio from the get-go, which, in turn, led to their inability to generate revenues in a low interest rate environment.6

    Simply put, the business model grounding of the bank’s market operation was amiss.

    Challenger Banks Are In Customer/Fund Acquisition Phase

    I would wager all challengers are in a net loss-generating phase of their existence. They make big positioning and product bets to scale their customer and deposit bases which will be monetized in the mid- to long-term timeframe.

    On one hand, this is nothing unfamiliar in the startup universum. Snap, for example, has recently reported in its IPO filing losses of $514.6 million in 2016 and “may never achieve or maintain profitability”.

    For various reasons I don’t think the challenger banks will be able to afford such liberty with their bottom-line results. The question then remains — how will challengers banks generate enough money to satisfy venture capital expectations, cover their operating costs and create meaningful profit?

    Early Monetization Is Materializing

    In the short term, the evidence of this can be seen with one of the earliest market entrants to the neo-bank space, Berlin-based N26. The now fully licensed bank has moved on from its previous modus operandi with Wirecard and free of charge service offering.

    N26 is now starting to monetise on new users on card issuing, ATM withdrawals and introduction of first paid products such as premium current account with an insurance bundled in.

    As we also know N26 has introduced its partnership strategy which will presumably generate incremental revenues for the bank as well. N26 now distributes the likes of Transferwise and vaamo, a German -advisor — “N26 is using vaamo’s API to offer clients N26 Invest, a co-branded solution that lets users select from three investment strategies depending on their risk tolerance.”4

    Current N26 pricing (source: N26.com):

    However, I would argue that monetization efforts as seen with N26 are only the very first step in a long way to profitability for the neo-banks.

    Let’s take a step back and see what lessons are there to be learned on profitability and revenue streams from traditional players in the banking market.

    Taking a Step Back: 6 Lessons on Profitability from Incumbents

    Note: Profitability of retail banks is a complex and complicated area of study — full academic studies and white papers by consulting firms are devoted solely to discussing its intricacies. For purposes of this article, I will try to keep it simple and put forward a couple of highlights I personally find important in context of implications for the challenger banks.

    1. How Do Retail Banks Actually Make Money? (a.k.a the boring part)

    Retail banks have two primary sources of income: interest income; and fees and commissions income.

    Interest income is primarily earned by a bank lending money to customers and charging interest on the amount lent. A bank earns interest income by lending money to customers at higher rates of interest than it costs the bank to borrow funds from depositors and/or wholesale markets.

    Fees and commissions income: banks earn fees and commissions income by charging customers fees for services and receiving commissions from, and participating in profit-sharing agreements with, other product providers. Examples of fees and commissions include fees for use of an overdraft, fees for packaged accounts, and income from the ATM (cash machine) network.7

    2. Product Point of View (and Importance of Mortgages in the UK market)

    An interesting insight on a UK retail bank product profitability comes from Credit Suisse research. Unsurprisingly, the most profitable products can be found exclusively on the credit side of retail products:

    “Among the banks we have studied, we find that mortgages are the most profitable lending product (average ‘clean’ RoE of 28%), followed by credit cards (26%); with SME lending (12%) and consumer credit (7%).”5

    In fact, Credit Suisse attributes such a weight to a successful mortgage offering that it is singled out as one of the three key profitability drivers for UK-based retail bank.

    From the challenger’s perspective, it is interesting to note that the most profitable retail product is at the same time one the most complicated to distribute digitally (Oliver Wyman):

    3. Importance of Interest Income

    It turns out that interest income — i.e. charging interest on outstanding liabilities — is an extremely important revenue stream for the incumbents.

    What’s more, share of interest income has increased significantly — from 65% in 2008 to around 75% in 2013 according to Credit Suisse research. Beyond cyclical trends, ‘there has been a more structural shift in the industry’s ability to generate peripheral revenues beyond pure interest-related income.’5

    AT Kearney reports that ‘Different regulations, such as free current accounts, lending fee limitations, and caps on interchange fees, have impacted (and will continue to impact) banks’ ability to generate fee-based revenues.’ According to CMA, AT Kearney also reported that the share of net interest income in UK retail banks’ total income was the highest in Europe at 82%.

    Another point of view besides the regulatory limitations is that traditional banks are simply not good enough at generating ‘innovative’ revenue streams from context and customer relevant 3rd party service offerings, new types of partnerships and beyond banking offerings — which might where the challengers could shine.

    4. Importance of SME Businesses

    Perhaps unsurprisingly, it turns out SME business is extremely important for the large UK incumbents.

    In fact, revenues from personal current accounts for the eight largest banks totalled £7.44 billion in 2014, while SME revenues for the seven largest banks totalled £7.1 billion in 2014.

    Unsurprisingly still, banking SMEs is much more lucrative on a per customer basis compared to a retail current account customer.

    5 Importance of Costs

    Naturally costs are a big part of the profitability equation.

    Consider the following — according to Oliver Wyman, 30% of all costs of a typical retail bank in the UK is consumed by its branch network. An additional 20% is eaten up by IT; a huge chunk of it certainly going towards maintaining legacy systems.

    Oliwer Wyman:

    In addition, it is estimated that on average, 5–6% of their revenue base is given up by the big retails banks as an effect of impairments.

    I believe challengers have a great opportunity to alleviate the short to mid-term pressure on their bottom-line and competitive positioning if they are smart about their cost base, deployment of resources and investing into the right and processes.

    6 Importance of Scale and Funding Structure

    The following two points are courtesy of Credit Suisse research:

    Scale alone is not enough, but is a necessary attribute — Although not enough on its own to determine profitability, our analysis suggests that without scale it is very challenging for a stand-alone business to be in the top quartile of sector profitability.

    Funding structure…is one of the most important differentiators. We see a clear positive bias [in regards to UK retail banking profitability]  towards a higher proportion of current accounts/low interest bearing deposits.5

    (My) Observations for Challengers

    1. Have a clear strategy that enables customer (and customer deposits) onboarding and retention in the short to mid term timeframe, particularly on low interest bearing products. Keep in mind that scale itself is not enough at all times.
    2. At the same, have a clear mid- to long-term strategy on the credit side of your products. This pertains especially to those offerings which are at the time being difficult to deliver via digital and particularly mobile channels such as mortgages; as these products are at the very core of profitability of retail banking.
    3. Start thinking about how to tap into the lucrative SME market with SME propositions or profit-generating partnerships; especially…

    Finish reading at Medium. Got a perspective? Please join the debate!

    Sources

    Monzo Blog, https://monzo.com/blog/2016/07/06/how-to-travel-with-mondo/

    A one-year savings account at 2%: Atom Bank blows away rivals with new inflation-beating rates, http://www.thisismoney.co.uk/money/saving/article-4252282/Atom-launches-new-one-year-fixed-rate-savings-paying-2.html

    ‘Very questionable models’: The cofounder of a startup addresses the elephant in the room, http://uk.businessinsider.com/currency-clouds-stephen-lemon-questions-fintech-business-models-2016-6

    vaamo Partners with N26 (Formerly Number26) http://finovate.com/vaamo-partners-n26/

    5 Credit Suisse UK banking Seminar — 2015 Update, https://doc.research-and-analytics.csfb.com/docView?language=ENG&source=ulg&format=PDF&document_id=1050375611&serialid=D3fAivrz0KjVObVAhNsc5e1OnBva50uGToQzZoM6ekA%3D

    6 Celý príbeh Zuna: Klienti ho chceli, investori nie https://www.etrend.sk/trend-archiv/rok-2016/cislo-41/zuno-banka-konci-klienti-ju-chceli-investori-nie.html

    7 Competition & Markets Authority, Retail banking market investigation — Retail banking financial performance, August 2015, https://www.gov.uk/cma-cases/review-of-banking-for-small-and-medium-sized-businesses-smes-in-the-uk

    8 Oliwer Wyman, Perspectives on the UK Retail Market, November 2012, http://www.oliverwyman.com/our-expertise/insights/2012/nov/perspectives-on-the-uk-retail-banking-market.html#.VbIMPPlViko


    [linkedinbadge URL=”https://www.linkedin.com/in/tomasvysny/” connections=”off” mode=”icon” liname=”Tomas Vysny”] is Co Founder at The Booster Labs

     
  • user 9:39 am on March 12, 2017 Permalink | Reply
    Tags: , banks, , , Downloads,   

    Citi Mobile App Downloads Doubled in 2016 

    Group also wants to join the ranks of the &;e-&; of U.S. The bank&;s app userbase soared in , Bank Innovation has learned. According to a company spokeswoman, &8220;last year alone, North America mobile app customers have grown by 50%, and mobile app have &; we saw over 3.25 million downloads in 2016,&8221; she [&;]
    Bank Innovation

     
  • user 12:18 am on March 8, 2017 Permalink | Reply
    Tags: , banks, , , , Leans,   

    Chase Leans Strategy to ‘Buy’ from ‘Build’ 

    SAN JOSE, Calif. – The “ or buy” scale is leaning increasingly towards “buy” at JPMorgan , as fintechs become less concerned with disrupting traditional . That’s the upshot Adam Carson, the bank’s head of digital partnerships, during a fireside chat at Bank Innovation 2017. “In my space, which is digital, I think you’ve [&;]
    Bank Innovation

     
  • user 12:19 am on March 7, 2017 Permalink | Reply
    Tags: , , , banks, , ,   

    Kasisto Announces KAI Insights at Bank Innovation 2017 

    wants to make proactivity the norm when it comes to banking. The conversational AI company today announced KAI , a data-driven service that will be integrated into its KAI for Banking platform, during the  event taking place in San Jose, Calif. The integration of KAI Insights into this platform will allow [&;]
    Bank Innovation

     
  • user 12:18 pm on March 6, 2017 Permalink | Reply
    Tags: , banks, , Relaunches   

    Bank Innovation Relaunches 

    Today,  releases its most significant redesign and relaunch since the site initially dropped online in 2009. We hope you love the new Bank Innovation. When we started Bank Innovation, while the crosswinds of the credit crisis were still swirling, we were the lone voice for innovation at . I recall introducing Bank Innovation to [&;]
    Bank Innovation

     
  • user 12:19 pm on March 5, 2017 Permalink | Reply
    Tags: B2B2C, banks, , ,   

    INV Unfiltered: Is B2B2C the Future of Fintech? 

    It’s increasingly hard to keep track of all the new personal finance management apps out there. They face tough competition from established startups and even themselves. Mark Zmarzly, founder of startup Hip Pocket, found a different solution for his newest PFM app, Hip Money. The company is tapping into the existing customer base of [&;]
    Bank Innovation

     
  • user 10:13 pm on March 1, 2017 Permalink | Reply
    Tags: , banks, ,   

    Three Steps to Adopt Artificial Intelligence in Banks and Insurance 

     

    Today, there is incredible interest in anything that is even remotely related to (AI). AI is dominating the conversation on a variety of levels. Philosophers and thinkers are debating the moral implications and risks for human kind of a world where intelligent machines are ubiquitous. In the media, it seems that a new movie or TV series on AI is launched every month. Academic papers on the topic are receiving attention from far beyond the scope of the usual research audience. In the meantime, businesses are facing much more short-term and concrete decisions about what to do with AI, where to invest first and how to measure the return of these investments.

    In this post, I will try to define a framework for how to structure decisions about AI adoption. To do so, I will focus on a sector that for different reasons is an early adopter: Banking and .

    As with any innovation, it is very important that established organizations focus first on selected “easy wins” or incremental change instead of disruptive change. This is a solid approach for several reasons. It gives you the chance to take advantage of some concrete benefits in the short term, which helps mitigate internal resistance, and it provides a view of the innovation’s full potential.

    For these reasons, using AI to increase automation for certain operative tasks is a great way to start.

    The daily operations of Banking and Insurance companies contain a number of repetitive, human error-prone processes that make them a perfect target for initial adoption of AI. Here, you have the added advantage that, even if you decide to start small and with only partial automation, the ROI could be staggering because these are typically high-consumption processes in terms of resources and costs.

    Let’s consider some processes that are common to both industries that fit these requirements. Customer care and e-form extraction (reusing data taken from electronic forms), or banking-specific processes such as mortgage approval (moving data from different documents into a central repository to do calculations) or fraud detection (tracking account activities, communications, connections etc.) are processes that are ripe for automation. In insurance, this includes processes such as claims management, new policy quotes, or the technical due diligence required for a new commercial policy.

    In processes like customer care automation or claims management, you can achieve significant savings even if you limit the scope to partial automation. In addition, the standardization often brings improvements for “soft” metrics like customer satisfaction. Each manager knows how many resources are dedicated to these tasks, so the potential ROI would be easy to calculate. A collateral benefit is that resources and people freed from these activities can be assigned to higher value tasks, such as sales-related activities that focus on growing the top line.

    Once the organization has experimented with the initial adoption of AI by focusing on high ROI initiatives linked to incremental improvement, it’s time to focus on the areas that can bring the most strategic value. This is what AI was made to do.

    The MIT Sloan Management Review recently published an article where they try to get at the core of what AI can really provide. They compared AI to the advent of the computer. The authors make the case that, even if the computer brought drastic change to basically everything, the real transformative element was the improvement in calculation.

    For AI, the elements that will bring about real change are scalability and cheap prediction power. Once automation is out of the way, these are the areas where organizations should start focusing.

    Banking and Insurance companies could make a smooth transition to AI-enabled predictions by starting to leverage data made available by the automated processes. For example, a side result of customer care automation is an increased set of analytics about your customer. Frequency of communications, the topics discussed, customer reactions to the marketing message, etc. are quantitative and qualitative data that can help in creating (again through AI and machine learning algorithms) models to predict customer behavior such as propensity to churn or to buy, to promote with peers, etc. Similar benefits can be achieved with processes such as claims management or technical due diligence for new policies.

    Organizations that have gone through the initial steps of adoption will be ready for the third more disruptive step. Let’s go back to the computer example from the MIT article. The majority of people who were in awe of the computer completely ignored or dismissed the larger impact that this speed and precision in calculation would have on us in the future via the  internet, e-commerce and free video phone calls.

    With AI, we are at the same stage of computers in the 70s. The most disruptive effect for organizations will be in the appearance of new business models, especially in the most traditional sectors (just as retail and telecommunications were among the core sectors disrupted by the evolution of computers).

    Going back to our focus on Banking and Insurance, while these organizations are going to be busy going through the first two steps in AI adoption, it is important to not forget about the big changes that are coming. For example: What will autonomous driving do to insurance? What would highly accurate algorithmic predictions of movements in the financial market (for example considering unstructured data like news, social feeds, etc. in addition to stock price fluctuations) do to ? What will perfect weather forecasts do to banks and insurance companies? No matter how advanced a company is in adopting automation or in experimenting with prediction, not paying attention to these next aspects of AI will be a death sentence for any business.

    AI adoption will be about competitive strength first and business sustainability later. As some of the early adopters of this , Banking and Insurance companies must ensure that they have a strategic framework in place to support the full cycle of these changes. If they drive this adoption through smart, incremental and forward-looking tasks they have a good chance of obtaining both short and long term gains.


     
  • user 7:51 am on March 1, 2017 Permalink | Reply
    Tags: , banks, , ,   

    Will the Enterprise Ethereum Alliance Be the New R3 for Banks? 

    is back in vogue with &;well, blockchains, anyway. The Ethereum Alliance (EEA) seeks to provide space for projects based on Ethereum. The group was officially launched today, and its 27-plus membership list includes some big names, like BBVA, Credit Suisse, J.P. Morgan, and Santander. “The initial list of members was inspired by [&;]
    Bank Innovation

     
  • user 12:19 pm on February 28, 2017 Permalink | Reply
    Tags: banks, , , , , , , , , USAA’s   

    Design Lab Will Fuel USAA’s AI, UX Efforts, Exec Says 

    Labs – focus units tasked to tackle specific technologies and ideas – have been growing in popularity among lately. Most established banks already have “innovation labs” – which focus on identifying trends and partnerships – in place, and many test distributed ledger applications in “ labs.” USAA  took a different route: the [&;]
    Bank Innovation

     
  • user 1:06 pm on February 27, 2017 Permalink | Reply
    Tags: banks, , , , , Refugee   

    Breaking Banks: Fintech Helping the Refugee Crisis 

    In this episode of Brett King, Marc Hochstein of American Banker, and Peter Renton, founder of LendIt Academy, talk about the upcoming Digital Identity Webinar, the LendIt Conference at the Javits Center in NYC, and the proposed Charter, and what that can mean for changes in banking in the U.S. Sam [&;]
    Bank Innovation

     
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