Executive summary
The last decade Retail Banks have seen margins come under pressure, yet the evidence shows those banks who invested most in technology and revenue diversification, have succeeded in maintaining their profitability. Payments service margins have come under particularly acute pressure, due to both regulatory changes and new digital payment platform competitors. As a consequence, banks are searching for ways to innovate and create new value from payments, to give their customers reasons to keep using their services. This paper looks at the potential of combining merchant offers, derived from the banks Business customer base, and incorporating them within payment services to the bank’s Retail customer base.
Essentially, the bank would act as platforms matching offers and services from merchants, to the needs of the banks retail customers. The success of such a platform is contingent on the ability of the bank ensure that the offers delivered are relevant to the retail customer receiving them. This requires an understanding both of the customers “personal attributes” (e.g financial status, personality type, interests) and their “context attributes” (e.g location, life stage, aspirations). Matching the right offer, to the right customer, at the right time, requires both “personalisation” and “contextualisation”.
Yet, financial data alone is insufficient to achieve this. Based on financial records alone, it’s hard to predict irregular large one-off purchases, it’s hard to identify a customer’s changing psychological mood, indeed it’s hard to spot anything before it’s established as a pattern with some financial consequences. Typically, signals of customer “intent” only show up in financial records after the customer has started making changes. Given the dominance of the Tech Giants in matching “Offers” to “Customers” and their ever richer repositories of customer data, banks who rely on financial data alone are unlikely to achieve “best-of-breed” today, let alone a competitive advantage tomorrow.
Fortunately for the banks, we stand at a point in time (2021 and beyond) where new regulations are transforming the personal data landscape. The EU Data Governance regulations published in November 2020, the forthcoming EU Data Act 2021 and UK Data Act 2021 all look set to unlock the customer-consented mobility of personal data between organisation who hold data about them. Essentially, akin cross-sectorial form of Open Banking, with some important differences. This paper argues that taking advantage of these new regulations will be critical for those banks who succeed in evolving to a new two-sided business model, creating new revenue streams by building their bank-as-a-platform.
Business Context
Banks have faced an erosion of their return on equity over the last decade, with ROE of banks falling from 15.5% in the pre-crisis days of 2005 to 8.6% in 2016 (Source: McKinsey 2017). Yet an analysis by the ECB in 2018 (Source: Anderson et al 2018) showed that the picture is far from uniform, with the best performing banks bucking the historic trend and maintaining or growing their profitability. The two factors cited which marked out these best performing banks were 1) Investment in technology and 2) income diversification beyond interest earning activities. These are likely to be the factors which determine which banks thrive and fade as digitisation matures.
Within this context the banks payment businesses margins have come under acute pressure. These have faced regulatory pressure on their debit and credit card fees and are experiencing increasing competition from digital platforms such as Apple Pay and PayPal. With the implementation of PSD2 maturing this pressure is likely to increase as TPP’s become more established in the market, combining core payment capabilities with a range of value-add services.
This presents the banks with a challenge to persuade their customers to use the banks payment services, rather than cash or services from the increasing number of digital competitors. With already thin margins, the response to this question focuses on what additional value can be created and offered to those customers. Here a lesson may be learnt from the earlier generation of internet platforms and methods of digital innovation.
Fundamentally, the transition to digital disrupts three areas of competitive advantage, with specific innovations comprising some mix of the three:
- Process efficiency
- Insight
- Network effects
The first, Process efficiency, manifests as improved customer experience and a lower cost base. To date this is the area where most innovations, both from the challenger and traditional banks has focused.
The second area is Insight, which is the ability to use data to make predictions, be they ones of actuarial risk or of customer needs. Innovation in this area is leading banks to better support customer journeys and also address untapped markets e.g Aire offering credit score for those with thin credit files.
The third area, Network effects, has only been exploited in a very limited way to date by the banks. Yet if we look at the pure digital players who emerged over the past two decades, we see that the most successful businesses are primarily underpinned by network effects. These have often operated through 2-sided markets (Google, Amazon, eBay, Uber et al), which have resulted in “lock-in effects” that make their competitive position virtually unassailable. In this context, it is worth exploring the opportunities banks have to create new two-sided markets and develop similar commercial dynamics.
The enablement of 3rd Party services
Large traditional banks usually encompass both Retail and Business banking arms. These tend to be historically separate outgrowths of the bank and operated as separate lines of business. Fundamentally, they serve different communities, but those communities in turn serve each other. Many businesses serve retail customers and in doing so one of the biggest challenges they face is making the right customer aware at the right time of how the services they provide can be of help.
Retail businesses address this customer engagement challenge through advertising and CRM. Typically, this accounts for round 20% of their overall cost base and they are keen to find more effective ways of deploying this spend. In the area of digital advertising, which now accounts for 72% of all advertising spend this efficiency can be improved by personalisation and contextualisation. The former shaping the content to appeal to the recipient, while the latter ensures the content is delivered in a context in which it is relevant to the recipient. Yet the data to do this is hard for a merchant to access and the tools to contextualise are not yet widely available. This creates the following types of problem for the retailers:
- Wasted inventory: Most spend misses its target either due to wrong targeting or right target wrong time.
- No visibility of the competition: Since retailers can only see the spend with them it’s hard to judge churn risk or their share of wallet.
- High value purchases: often sporadic purchases and so internal retailer data is often not predictive of repeat purchases e.g second hand cars.
- No persistent touch point: The number of apps regularly used is small and retailers struggle to make theirs one of them. This makes it hard to re-engage customers when they become disengaged.
Despite these problems, the scale of expenditure on advertising and marketing is huge. In the UK the average salary is £24,000 p.a, whereas the total expenditure on each individual person is equivalent to about one month of their income. This would represent a meaningful sum of money to the individual if they could directly receive some part of it. In many ways’ todays situation is reminiscent of a market failure. What’s needed is an entity, that both sides trust, who can access extensive customer data and who with the right value proposition can gain the customers consent to use that data. If the banks stepped forward into this role (which there is growing evidence that they are doing), they could bring the vital assets of consent to access data, trust and inventory, connecting millions of merchant clients to millions of retail clients.
What’s missing from this mix of asset access to a broad enough scope of customer data to optimally personalise and contextually match the right offer to the right client at the right time, to a level better than the solutions offered today by the Tech Giants, such as Google, Facebook and Amazon. Critically, the type and scope of the data held by the Tech Giants enables them to spot forward indicators of customer need, whereas financial data alone too often only offers time lagging indicators. To overcome this barrier to success, banks need to understand and leverage the new and forth coming Data Regulations.
The mobility of cross-sectorial data
Viewing a customer through the “letter box” of a single enterprises data, inevitably misses much that is pertinent to determining the customers needs. For brevity, we won’t attempt to catalogue the insights derivable from customer data cross sectors, but the table below gives some illustrative advantages:
An excellent survey of “behavioural insights” has been compiled by Mark Egan of Stirling University and is available here:
Being able to leverage these insights to create better user experiences and new services is contingent on being able to access the data held by other organisations. The first steps in this direction were taken with GDPR’s right to “data portability”. However, this was focused on data mobility to aid account switching, rather than enabling the reuse of data for the ongoing provision of services. Extensions to achieve this latter objective were identified in the EU’s Data Strategy (Feb 2020) and are being enacted in the published EU Data Governance Regulations (Nov 2020) and proposed EU Data Act (2021). A central objective of these legislative initiatives is to enable:
“…..a novel, ‘European’ way of data governance, by providing a separation in the data economy between data provision, intermediation and use.”
This amounts to a radical reshaping of the personal data landscape, from the organisation who brought you GDPR, now copied globally, this is the logical next step. While in a European context, this flows in part from a desire to extend the Human Rights legislation of the 1950’s into today’s digital society, the same can hardly be said for China’s enactment of analogous legislation. The global appeal of GDPR stems both from its empowerment of citizen rights, and its ability to unlock new data driven innovations to power economic growth. New markets will be created and old market leaders toppled.
Central to the new EU proposals is the role of the “Data Sharing Provider” (aka “Data Facilitators”, “PIMS” et al). These are entities who have a fiducial duty to work on the customer’s (data subjects) behalf, share their data and to help them make informed decisions about its use by third parties. They are prohibited from offering commercial services beyond those needed to enhance the sharing of the data subjects services. A “Data Sharing Provider” could be established by a bank with the appropriate Chinese walls and legal independence or by independent new actors. The Data Sharing Providers will use the powers given to a citizen, under GDPR and the new EU Data Act 2021, to access data held about them by (almost) any organisation and mandate it’s transfer to a 3rd party organisation.
The organisation who flourish in the new data landscape will be those who can work with their customers to enable such data flows. Doing so is not simple, as it touches on so many enterprise functions: Brand positioning, ethics, governance, liability model, technology and service propositions, must all be aligned to a coherent whole and that be articulated to the customer.
While the challenges are not insignificant, the prize is enormous. If you can become a Brand trusted by your customers to receive such data flows, you can unlock the opportunity to become a “meta-brand”. By “meta-brand” we mean a brand trusted by the consumer to process their data and use analytics to derive insights about their future needs, before most other enterprises can do the same. This places the “meta-brand” in a position to “make the market”, matching the customer’s needs to the service provider that can best meet those needs. In essence, meta-brands own the customer relationships and all other brands become utterly commoditised. Far-fetched? Too strongly worded? Amazon.
In truth Banking-as-a-platform, could be Telco-as-a-platform, or some trusted retail brands could execute the same strategy. Historical accident, maybe combined with the strategic ineptitude of the telco’s, has left this huge opportunity at the feet of the financial services sector. The opportunity is to create new compelling propositions and services for a banks customers. The natural Line-of-business within the bank is an extension of the banks “payment services”, but as we have seen its significance lays in the re-invention on banks-as-a-platform far beyond their tradition financial services roots. What would such future business models and propositions look like?
Business models & Use Cases
The strategies described above can be embodied in a range of business models, which are largely shaped by how the money that would have been spent on advertising is shared between the customer, bank and merchant. We illustrate the range of possible business models in the triangular diagram below:
From a Banks perspective each of these three business models may have some attractions. Acting as a contextualised Ad Platform may help customers find the right merchant services and drive engagement with the Bank. Further, delivering merchant offers with unique discounts may be a compelling way to differentiate a bank. Enabling a customer to personally receive a portion of the Ad spend as cash, may prove a compelling motivation to drive customer engagement. It easy to imagine such a proposition being developed to include micro-investments, whereby the money accrued by the customers is diverted into investment instruments to save for their next holiday or some other purpose. In effect this builds a relationship between use of the Banks payment system and something in the customers life which they care passionately about.
For illustrative purposes, we will consider what a proposition might look like that enables a business model positioned fairly centrally in the above triangle. Essentially the bank offers a contextualised “Offer” service to their participating merchants in a “Offer Scheme”. Using the rich data accessed by bank through its “Data Sharing Provider” role, combined with an analytics and contextualisation capability, the bank is able to ensure that only offers which are helpful, and so have a high redemption rate, are passed from the merchant to the banks retail customers. The offers are sent to end-customer digitally and presented as a small number of contextually relevant tiles within their banking app. The offer includes a QR code which is scanned at the PoS at participating merchants. The QR code contains both the “offer number” and the “Bank account number” a record of which is created by the merchant as the “redemption file”. The value of the goods sold contained within the redemption file is then used to calculate the Banks fee for the provision of the “Offer Service”. The bank retains a portion of the fee, with the larger remainder being passed by the Bank to the customers savings/investment account. The benefits for each of the parties are:
The Customer
- Has a new opportunity to earn cash back with their existing card
- Has the option to direct this cash back into micro investments
- Potentially generating > £1000 pa (esp if telco, utilities etc)
The Merchant
- Route to re-engage lost customers
- Targeted way to engage on infrequent high value purchases
- A persistent personal digital touch point to compete with loyalty schemes
The Bank
- Creates a new “Offers” revenue stream
- Give customers more reason to use their card
- Increase merchant loyalty / stickiness
- New opportunity to help customers create investments
All parties significantly benefit and the best-in-class service is only deliverable by an entity who can work with a “Data Sharing Provider” who is deeply trusted by the customer.
Business impact
To gain a perspective on the order of magnitude of possible value creation, we note that Quidco, without any contextual targeting or access to the rich data mentioned above, passes on savings to their average user of £305p.a. If we assume with contextual targeting this rises to a conservative value of £600 p.a and 25% of a banks 10M customers participated, it would create a value pool of £1.5Bn. If the bank retained 1/3 they would increase their revenue by £500m p.a and their average participating customer would gain roughly an extra month’s worth of disposable income.