The Ripples of Core Banking

The Ripples of Core Banking

Andra Sonea, Anthemis Fellow ’17

2 The Ripples of Core Banking

Table of Contents

Executive Summary .............................................................................................................................. 3
I. Introduction ................................................................................................................................... 4
II. A framework for existing retail banks ............................................................................................ 5
III. What is a Core Banking System? ................................................................................................... 7
IV. The ripples of Core Banking .......................................................................................................... 9
A. Upstream Effects ............................................................................................................................................................... 9
1. Core banking systems are product-focused while the digital world is customer-focused ................ 9
2. The core banking systems in the UK are many decades old ......................................................................... 10
3. Rich extensible transactions become the norm ................................................................................................. 10
4. It is not one system but many .................................................................................................................................... 11
B. Downstream Effects ...................................................................................................................................................... 12
1. Heavily regulated domains ......................................................................................................................................... 12
2. The back office operates on long time horizons ................................................................................................ 13
3. The final aggregate figures of each domain vary widely for the same business dimension .......... 13
4. The timeframe for the relevant data to reach the decision makers is inadequate ............................ 14
V. Planning for the future ................................................................................................................ 15
A. What is the future vision? ........................................................................................................................................... 15
B. From vertical proprietary towers to multi-players and building blocks ............................................... 16
1. The personal computer industry 1980 -1995 ..................................................................................................... 17
2. Telecommunications ..................................................................................................................................................... 18
C. The new building blocks of banking ...................................................................................................................... 19
1. The next banking channel – 3rd party Fintech apps ......................................................................................... 19
2. Core banking services .................................................................................................................................................... 21
3. Capital Management ..................................................................................................................................................... 21
4. Who puts the deal together? ...................................................................................................................................... 22
VI. Conclusion ................................................................................................................................. 23

The Ripples of Core Banking 3

Executive Summary

This paper is written as a perspective on the way current retail banking architecture impacts the
emergence or adoption of innovative solutions. It emphasises the crucial role that core banking
systems have in this architecture, and the effects they project throughout the existing business and
technical model of the banks.

Following a brief introduction in chapter one, the second chapter describes a simplified retail banking
architecture to establish a common framework that is used for the rest of the paper. The third chapter
gives a definition of core banking systems, with a focus on a unified model for thinking about retail
banking products. The fourth chapter discusses in detail the upstream and downstream effects of
using numerous old, product- and brand- specific core banking systems. The upstream/downstream
orientation is a choice made in this paper to represent the banking architecture, but the reader may
find other representations. Here, the upstream effects appear in the customer experience. Customer
channels, and the systems supporting them, sit at the top of core banking systems. The downward
effects are manifested in the financial and risk management domains. Which are considered to sit
underneath core banking.

The fifth chapter reviews the limitations discussed in previous chapters and how they impact various
business capabilities. By looking at the telecommunication industry, the paper argues that the retail
banking industry should not continue to build and design as if the assumptions from 50 years ago
regarding what a retail bank is, still hold. Instead, the industry should look at the way financial needs
manifest today and what would be the best way to satisfy them. By looking at the personal computer
industry, the paper argues that the retail banking industry might go through a very similar
transformation from vertical, integrated, fully-owned towers of functionality to horizontal, specialised
industries which deliver services through collaboration and partnerships (see Figure 7).

The paper ends by describing what the suggested building blocks and new horizontal industries might
be, and concludes that just a small number of strategic moves and combinations of technical and
business ideas could lead to a very different landscape of the financial services industry.


I. Introduction

Visions and predictions of the future rely on a solid understanding of the present. In the automotive
industry, for example, until recently all cars required petrol/diesel to function. When Tesla debuted, it
was described as a “normal” car that worked on electricity and not on petrol. The advent of self-
driving cars represents another departure from the norm. An electric, self-driving car may appear to
be different from the norm in just two key ways, but these changes have been enabled by countless
unnoticed innovation points along the way. The propagation of a larger number of cars with these
features could lead to many possible future scenarios for entire industries, affecting the lives of
millions.

Similarly, people see a bank as a place that stores money, lends money, and facilitates payments. The
perception of what a bank is and does comes from the direct interaction with the institution through
its branches, ATMs, websites and mobile applications. As in the case of cars, the fundamental
changes in the world of banking will come from things which are “inside”, and which would allow
the delivery of the required services in fundamentally different ways.

This paper highlights the ways retail banking architecture is evolving around traditional core banking
systems, and creates ripple effects in and outside of banking. The paper then explores possible change
scenarios for the industry by looking at transformation shifts in personal computers and the
telecommunications industry. The final part of the paper looks at possible building blocks, which will
appear first alongside the classic incumbents and in time could completely transform the way financial
services are delivered1.

1 While this paper refers to the financial services industry in general, in reality the industry varies considerably
from country to country. History, economic development, and regulation have a huge role to play in how the
retail banking industry is shaped. The examples in this paper come mainly from the author’s experience working
with UK banks.


II. A framework for existing retail banks

This article focuses on retail banking only, and for discussion purposes, it proposes a simplified
banking model in order to review specific critical components.

If a bank is imagined as a vertical, integrated model of delivering financial services, on one end are
channels used by individuals and companies to interact with their bank, and at the other end are
specialised systems producing “aggregated figures” related to specific domain logic (e.g. Financial
Accounting, Treasury, Risk, etc.). Some of these “aggregated figures” are public, some are only for the
regulators so they can exercise their role at market level, and some are for the bank executives so they
can run the bank and take decisions.

Figure 1: A simplified framework for retail banking architecture

Interacting with customers vs. interacting with the regulators are two very different aspects of
banking, and bankers from each of these domains don’t speak the same language, rarely if ever meet,
and don’t consider each other “proper” bankers.

At the top of the vertical towers, customer channels represent the “visible face of banking”. This is
what most people view as banking – branches, online banking, mobile app, etc. Few Fintech solutions
even go beyond this visible level of banking. Instead, they typically focus on reducing friction and
improving the customer experience without going too deeply below this level.


Below the core banking systems there are towers or silos, each of which evolved in near-total isolation,
producing figures according to the rules defined by the regulators. The paper refers to this layer as
“deep back office”.

In between these layers, and inside the layers themselves, are thousands of systems. Any global bank
has an Application Catalogue listing between 2,000 and 4,000 applications. These will vary in
importance and level of complexity, but the sheer number coupled with the increasing number of ways
of hosting and integrating them brings a “complicatedness” almost impossible to manage or improve.
Out of these applications only about 5-10% of them serve the bank’s digital capability directly. The
rest are largely unseen and remain untouched by Fintech innovators.

This simplified framework for thinking about retail banks as vertically integrated, fully-owned towers
is applicable to all large banks in the UK. At the market level, there are four or five such large towers.
The internal configuration of each tower represents the evolution of banking from branches to mobile,
the history of a bank’s acquisitions, and the level of its global expansion. In a puzzling move, many of
the challenger banks in the UK have replicated this layered architecture thinking that this is how a
bank should be. These young banks are currently sheltered from the problems that incumbent banks
face because they do not have a long systems history behind them and they have not yet faced
mergers, acquisitions, global expansion, or the appearance of new channels.


III. What is a Core Banking System?

There is no universal industry definition for what a core banking system (CBS) is and does. For many,
core banking systems are simply the back office, limiting the understanding of how deep the banking
architecture runs.

Current core banking systems were either built in-house or purchased are product-centric systems
(e.g. current account, savings, credit card, loans, mortgages, etc.), and hold a trusted near real-time log
of the transactions occurring for all customer-product relationships. There are many other important
features, however the defining trait of the core banking systems is being the trusted source for the
product transaction log.

Figure 2. Customer, product, and transactions relationships

When engaging with the implications of core banking systems architecture the following features
should be kept in mind:

• Each bank typically has dedicated core banking systems from different generations, for each
type of product and brand e.g. Nationwide Mortgages, RBS Savings, etc. (See Figure 2)
• Most UK core banking systems are between 20-45 years old.
• A core banking system not only receives transactions from external systems but also
generates product-specific transactions according to the financial mathematics of the
product (e.g. instalments for loans, interests for saving accounts, overdraft fees for current
accounts, etc.)
• Irrespective of the type of financial product, retail banking products have three main
dimensions:
o Timeframe (e.g. 25 years for a mortgage and 6 months for a savings account)
o Interest Rate (e.g. 2.5% for a mortgage or 0.05% for a savings account)
o Amount (e.g. interest applied to the remaining mortgage amount or interest applied to
the balance of funds held in the savings account)
There are many other dimensions, which define a retail product, but the Timeframe, Interest
Rate, and Amount axes immediately categorise a product. For example, compare Figure 3,
where the grey box defines most saving accounts, with Figure 4, where the grey box describes
most mortgages.
• Each financial product has a defined mathematical formula and there are rarely innovations
that create “hybrid” products. Even new products typically only focus on changing the values
of these variables or combining an existing product with another characteristic (e.g. eligibility
for over 65-year-olds, online product only, etc.) This is largely due to products being managed
in strictly separated systems.


Figure 3. Saving accounts represented on the axes time, interest, amount

Figure 4. Mortgages represented on the axes time, interest, amount.


IV. The ripples of Core Banking

Two key types of effects on the banking architecture and capabilities result from the current core
banking systems2:

• Upstream Effects, visible in the levels above CBS, and mostly occurring at the interface
between banks and customers
• Downstream Effects, visible in back office applications and within the application of new
regulatory changes

A. Upstream Effects

Many limitations brought by core banking systems are believed be fixable in the UX, however most of
them stem from the labyrinthine systems architecture underneath. The most important problems are
rarely fixable in the UX only.

1. Core banking systems are product-focused while the digital world is customer-focused

There are a number of implications emerging from the product-centric nature of core banking
systems. The most visible and well-known implication is the siloed structure of banks in both
business and technology. Most of these silos are in fact product towers: every bank has product heads
(e.g. for Credit Cards or Savings) and P&Ls for products or sub-groups of products, but rarely is a
director holistically responsible for a category of customers (apart from high-net-net worth/private
banking, which often have dedicated systems too).

In the digital (non-banking) world, individuals are targeted and served based on a company’s
knowledge of them from interactions and information available from their digital traces. Although
some uses of customer data may constitute abuse, much of digital marketing or the digital
propositions themselves are chiefly structured around “personas” built from the traces people leave in
their digital lives. Similarly, in a digital world financial propositions should use a more refined needs-
profiling approach to respond with more tailored products. Also, despite the huge change in
technology available on the market, most banks have not yet built an architecture layer which would
enable them to analyse transactions from their customers’ perspectives. Existing data warehouses are
rigid and expensive, and rarely allow ad-hoc blending of new, relevant, or unstructured data sources.
Even if hosted by the same bank, customer transactions are scattered across core banking systems,
immediately archived and never analysed again to understand customers’ needs. The product-centric
view of the world imposed through core banking to date has limited the development of a customer-
centric view in incumbent banks.

Effects:
• It is costly and ineffective to mix data across these product silos in order to build a
customer view. As a consequence, the exercise of understanding niche customer needs and
behaviour through targeted data analysis is difficult and often not done. Considered a
“marketing task”, this is often relegated to a marketing business unit, which in turn is
technologically under-resourced and without the data and tools to do the work.

2 The upstream/downstream orientation reflects a choice of representing banking architecture with the
customer channels on top of core banking (upstream) and the back office shown underneath (downstream) (see
Figure 1).


• Reacting to customer needs real time is de-facto impossible, e.g. the type of
reactions/support/notifications seen in the Finovate demos.

2. The core banking systems in the UK are many decades old

For many retail banking incumbents, the age of the core banking system is relatively unimportant.
Hardware and relevant security are continuously upgraded. The software, however, reflects design
decisions made decades ago, taking into consideration technology limitations of the time, and past
trade-offs made to adjust to new contexts.

Of the many important changes that have happened, the appearance of mobile and online banking
channels have had the most significant impact because for the first time the entire product portfolio
was brought together for individual customers to access directly. This full digital image of the
customer had not been required for older channels such as branch or telephony chiefly because
banking systems were accessed by bank’s employees and not digitally by the customers themselves. It
is important to understand that all the systems surrounding CBS, which enable this digital image to be
created, currently enable the presentation layers but not yet the analytical layers.

Understanding how systems evolved from enabling transactions in the branch, then at ATM, online
and on mobile, helps one understand the architecture of the incumbent banks and see that they were
not designed for the 24/7, always-on mobile customer, but rather only for infrequent interactions.
Core banking systems were designed for batch scheduled overnight interactions, while customer
transactions happened during regular opening hours for shops and banks. Nowadays, customers do
banking 24/7 and banks have to handle unscheduled volume peaks, which were inconceivable until
recently.

Effects:
• The banking world continues running its core banking systems, with the technology
limitations which existed 25-45 years ago, when its core systems were created. While these
limitations no longer exist, banking doesn’t benefit nearly enough from technology advancements
targeted at removing previous limitations.
• Fintech propositions which depend on collaboration and integration with incumbent banks
expect to “shake hands” with compatible technology inside their larger counterparts. This is
rarely the case and this is often the reason most Fintech collaborations fail.

3. Rich extensible transactions become the norm

Years ago, when many of the core banking systems in use today were designed, the information
preserved at transaction level was not very rich and there was no need for more than a few fields to
identify a transaction.

Nowadays, there are an incredibly large number of payment options, and one can capture a rich range
of variables for each transaction, information which may be relevant to understand customer
behaviour or be necessary for customer applications for money management (expenses categorisation,
savings, offers). While this information is produced, at the moment it cannot be stored as a full
transaction in the core banking systems and it is usually split, stored separately, and fuzzy-matched
afterward.

It is reasonable to assume that the information captured at the transaction level will grow with new
dimensions, though it’s difficult to know now what these will be. The next generation of core banking
systems will have to enable rich extensible transactions in order to enable richer customer
propositions on top of them.


Effects:
• Most compelling Fintech propositions that directly target consumers rely on rich contextual
information about transactions. Core banking systems and the surrounding systems around them
can rarely provide this rich information in the timeframe required. This is valid for both in-house
generated and 3rd party digital propositions, and it is one of the main reasons why there aren’t
richer features in banking digital propositions yet.
4. It is not one system but many

Each bank has a number of core banking systems, multiplied by brands and types of products. See
Figure 2. In addition, each core banking system is surrounded by many applications covering
functionality which for technical reasons could not be developed in the existing core banking systems.

So long as the current core banking systems architecture remains in place, banks will need to create
structures that simulate a customer view for the purpose of serving it in UX. This “stitching” is
expensive, may not last, and does not enable many typical UX functionalities given a lack of a real,
meaningful customer view. It is usually just a presentation layer without the underlying intelligence,
which could make the difference in customer experience. Some rightfully call this approach “putting
lipstick on a pig”.

Effects:
• Creating new products, either bank-owned or triggered by collaboration with 3rd party Fintech
propositions, is a months-long process. It is not enough to create these products in the CBS; they
need to be created in the multitude of applications flourishing around them and mimicking the
behaviour of one consistent, integrated system.
• Integrating the CBS and 3rd party Fintech propositions is very often the breaking point in
adopting innovative propositions because of the unbearable cost and timeframes. Neither the
bank nor the start-up can afford it.
• The cost of maintaining a portfolio of core banking systems and surrounding applications
grows as the digital world makes more requirements for unified views, richer data, and real-time
availability.


B. Downstream Effects

The core banking systems layer represents for many in the Fintech world the entirety of the banking
back office. Given that only a small proportion of applications and costs are concentrated in the “digital
banking” layer above core banking, it is surprising that deeper layers of banking architecture remain
barely touched by Fintech innovation.

Figure 5. Simplified back office architecture of a large bank

Underneath the core banking systems layer there are other heavily-siloed structures, defined by
financial management disciplines and regulators instead of products. This article mentions only the
Financial Accounting, Management Accounting, Treasury, and Risk silos, which are found under the
core banking systems layer of any bank. Even if these domains are quite different in their purpose,
there are many similarities and interactions between them.

1. Heavily regulated domains

Each domain is heavily regulated at the domestic and international level. The regulators of each
domain don’t appear to collaborate much with each other, and even within the same domain there is
little collaboration between regulators. As a consequence, banks face similar but not identical
requirements, which can trigger separate internal projects with separate budgets, deadlines, and
technology stacks.

Effects:
• Each new regulatory requirement for these domains triggers entirely independent
projects even if the requirements address the same issue. After the 2008 crisis, there was a flurry
of regulation on reporting liquidity through all these domains, yet there was little crossover or


cooperation between domains. As a result, costs multiplied with the number of projects while
bringing few benefits to the banks.

2. The back office operates on long time horizons

Each of these domains uses the whole of a bank’s transactional data from the core banking systems.
The time horizon for transaction data used in the normal cycle of operation is one month to one or two
years, much longer than what is typically needed in digital customer applications.

25 or 45 years ago, there weren’t many transactions that would have appeared on a bank statement
apart from cash withdrawals, direct debits for mortgages, loans, credit cards, and purchases in large
department stores. Now, a UK bank statement may detail specific purchases such as coffees consumed,
tube tickets, and multiple small value transactions made in the digital world. The number of electronic
transactions per person has increased dramatically and the bank must keep up, even if as an aggregate
value for these transactions they do not earn more from their same customers.

Core banking systems have always been high volume systems, however, the digital economy led to a
massive increase in transaction volume, and the Internet of Things may lead to exponential growth. As
most core banking systems cannot hold large enough volumes of data in an active state for back office
domains, these domains built their own data “primary sources” made from transactions aggregated
according to their specific criteria. See Figure 5. This led to the “primary data sources” of these
domains not being the core banking systems, but instead dedicated data warehouses. These are
usually expensive, quite rigid, and difficult to reconcile.

Effects:
• In order to operate with the required volume of transactional data, a large number of
expensive data warehouses lives under the core banking systems.
• As new regulation continues to emerge and as these data structures are typically rigid, new data
warehouses continue to be added to bring in the new dimensions required by the new
regulation.
• Until a common data layer emerges that is capable of containing the full transactional volume,
with all required attributes, it is not possible to develop an approach to regulation that
addresses the requirements of multiple regulatory bodies through common initiatives.
While it’s possible to develop such a data layer separately from core banking, this is no longer a
technological limitation as it used to be.
• The current approach for satisfying regulatory requirements through independent projects leads
to hundreds of millions of pounds being extracted from the banks’ budget, without bringing
much tangible value to the customers or the bank. In aggregate, at country level, given the
repetitive nature of these projects in the banks, the amounts spent on ineffective delivery of
regulatory reporting is staggering.

3. The final aggregate figures of each domain vary widely for the same business dimension

Many specialist domain systems use data from the data warehouses underneath CBS as primary data
sources, e.g. general ledgers, legal and management consolidation systems for Accounting, treasury
systems for Treasury, and specialist risk systems for Risk. Each of these specialist systems transforms
the data even more, to a level of abstraction understandable to the relevant domain specialists and
according to the very strict rules provided by the regulators. Very often, though, different domains
evaluate the same dimension of the bank, such as its liquidity, and given the completely siloed
transformations that data goes through, the position indicated by each of these domains can vary
widely. These differences in the results produced by different domains are highly relevant because
bank executives base their decision-making on this output. What steps should one take when the data
recommends contrasting actions?


Effects :
• It is very hard for decision makers when the information provided by different silos is
contradictory. Executives learn to take decisions very much based on experience and less on
numbers.

4. The timeframe for the relevant data to reach the decision makers is inadequate

Given also that primary transaction data used by all these domains goes through multiple layered
transformations before reaching the state of “meaningful figures”, the timeframe for this data
transformation lifecycle varies between 24 hours and one month.

Effect:
• In the digital era when so much happens real time, the typical retail bank is very slow to
understand its own position. This becomes even more critical in times of financial crisis when
the markets in which the bank participates move wildly. Not only do the numbers
recommend the bank take contradictory actions, but the bank truly has no way of knowing what
happens in real time. The timeframe to get the numbers is at least 24 hours and typically one
month. It is like having messages delivered through Chappe Brothers telegraph while the rest of
the world uses a phone.


V. Planning for the future

Despite billions of pounds of investment into Fintech companies, it is unlikely that many will have
their technology adopted or acquired by large banks until core banking services fit for the digital
economy are in place.

Many bank executives believe it is possible to operate old core technology ad infinitum because
different delivery models can coexist under the so-called “bi-modal” delivery model. In theory, a bank
could have a delivery model focused on stability, safety, and accuracy for its legacy infrastructure
while working in an agile way for its digital propositions. The bi-modal approach is no longer
sustainable. These two worlds are not separate, but they deeply integrate.

The few core banking systems replacement projects which went ahead (e.g. NAB Australia3, Deutsche
Bank4, Mizuho5) lasted many years and cost billions. While these early attempts are admirable, buying
an off -the-shelf core banking system and going through replacement projects product by product, and
brand by brand is not effective either.

A. What is the future vision?

The table below summarises some of capabilities of banking architecture and its current limitations as
presented in the previous chapter. The focus should be however how these limitations can be
overcome and what the future platforms and building blocks should aim for.

Table 2. Comparison of the current and needed states of banking architecture capabilities

Feature Current manifestation Future vision
1 Integration of banks and 3rd
party Fintech propositions
Costly. Takes a long time. Usually
abandoned. PSDII/Open Banking
solutions adopted by banks
typically will not solve this
problem.
Seamless integration.
2 Product innovation New products vary only on known
dimensions/ attributes and within
the defined categories. Bringing
such products live takes months
and is very costly.
Ability to create new (hybrid)
products fast, at a low execution and
running cost. Products could
originate in the bank or through 3rd
party niche providers.
3 Product personalisation Not possible currently. In a digital economy, based on
experience with other domains,
people expect banks to respond to
their individual financial needs.
4 Real-time digital interaction Limited functionality in incumbent Persistence of banking transactions,

3 Foo, Fran. "CSC Questions CBA Core Banking Upgrade." The Australian, 7 July 2011. Web. 9 Apr. 2017.
<http://www.theaustralian.com.au/business/technology/csc-questions-cba-core-banking-upgrade/news-
story/3641617bd3640a35a570928d65d65402>.

4 Team, Editorial. "Deutsche Bank Moves First Customers to New Core Platform." Finextra, 11 July 2012. Web. 09
Apr. 2017. <https://www.finextra.com/newsarticle/23885/deutsche-bank-moves-first-customers-to-new-core-
platform>.

5 Andreasyan, Tanya. "Mizuho Bank Gears up for New Core Banking System Go-live" Banking Technology. N.p., 16
Nov. 2016. Web. 09 Apr. 2017. <http://www.bankingtech.com/644262/mizuho-bank-gears-up-for-new-core-
banking-system-go-live/>.


with the customer (instant
nudges to save, contextual
interaction, instant PFM,
etc.)
bank applications. Compelling
demos in the neo-banks but they
are limited by data availability from
the incumbent with whom they
integrate.
in the full richness of the context
captured. Ability to analyse the
transactions for the whole portfolio
of products of the customer so the
bank can initiate relevant
notifications and offers.
5 Customer analytics Usually not done. Sometimes done
on aggregated values and with
delays lasting days or months.
Analytics on multi-product
transactions down to customer level.
Ad-hoc or planned blending with
structured and unstructured sources
of data from inside or outside the
bank. Self-service analytics to
relevant functions in the bank,
appropriate to their work and
authorisation.
6 Holding large volumes of
data in an active (not-
archived state) and without
aggregation or duplication
in static data warehouses
Incumbent banks hold multiple
versions of data, typically in
aggregated and/or archived states.
All these limitations (cost of large
information management
infrastructure, integration,
regulatory compliance approach)
need the same first step to happen
for a noticeable improvement and
cost reduction.

As part of new core banking design,
cloud-based information
management platforms should be
created to host transactional data for
all clients and products, allowing
also for one source of data for the
business decision domains (e.g.
accounting, treasury, risk).

This would enable the development
of a multi-regulatory approach to
delivering the solutions required for
regulatory compliance across all
these domains and individual
regulatory requirements.
7 One common source of
truth for banking reporting
and decision systems
(Financial and Management
Accounting; Treasury, Risk,
etc.)
Incumbent banks have separate
silos for these domains. Their
respective data sources are
irreconcilable.
8 Multi-regulatory execution
and operation approach
Each new regulatory project is
defined and budgeted individually,
leading to duplications of
development costs for interfaces,
data warehouses, and regulatory
reporting software.
9 Near real-time decision
making figures available for
executives
Decision support figures available
within 24 hours at the earliest and
usually after days or even months.
By reducing the number of data
layers from source to reporting,
most of the domain relevant figures
will result from algorithms
applicable to the same data source,
allowing the executives to make
decisions on more accurate and
recent data.

B. From vertical proprietary towers to multi-players and building blocks

For years, many believed that fundamental changes in the industry must come from banks because
they are the only institutions with all the mechanisms and tools to enable an entity to operate in the
financial services market. Nowadays however, it looks like the most important changes will likely
come from outside of the traditional banking world.

Many ask if the existing challenger banks represent the long-expected innovations in retail and SMB
banking. While most of these new banks have compelling UX and CX propositions, most also have
almost identically replicated the incumbent banks’ architecture. This may not be obvious, as indeed


their architecture is leaner. However, this streamlined architecture is due simply to the fact that unlike
their larger peers, younger banks do not have a history of mergers and acquisitions, global expansion,
and incremental additions of customer service channels. Given a long enough period of time and
similar challenges, the architecture of the new banks will look similar, and more importantly will
manifest the same problems.

Building a bank with full functionality is exceptionally hard and complex. In addition, getting funding
for innovative solutions that attempt to solve broad problems in a scalable and sustainable way with
current technologies is a challenge. Finding models address an entire industry problem may be too big
for any single challenger bank to attempt to solve.

What may happen in the near future and lead to an optimal solution in aggregate is the fragmentation
of the current retail banking vertical towers model. New building blocks of functionality, which
before were delivered solely by banks, will appear alongside incumbent banking. Through
partnerships between them, they will form a new financial services model alongside the
traditional banking one. In time, these building blocks may lead to the development of entire
horizontal industries. See figure 6.

Examining other industries which have gone through similar transformations offers a glimpse into
how things may evolve in banking. This paper focuses on two examples:
- The personal computer industry, which saw the fracture of proprietary vertical towers that
were meant to dominate their respective industries.
- The telecoms industry and the fundamental changes of the business and technical model of
the industry.

1. The personal computer industry 1980 -1995

In just 15 years, the personal computer industry transformed from large, dominant, fully-owned
verticals to a set of new horizontal industries with many competing players.

In his book “Only the Paranoid Survive” published in 1997, Andrew Grove, ex-Intel CEO described IBM,
DEC, Sperry Univac, and Wang, the main players of personal computer industry in 1985, as being
“strong, vital and growing”6. Each of these companies at the time was a vertical proprietary block
competing against other vertical proprietary blocks. Each produced all the components that went into
a personal computer from hardware to operating systems and software. They also sold these
computers directly. The first sell was incredibly competitive given that enterprises would be locked
into a proprietary technology standard in perpetuity. This model of a few proprietary vertical towers
locking their customers in a long-term relationship is very similar to the current state of UK banking.
See Figure 6.

What changed the structure of the industry was not a few other small players creating their own
personal computers, but rather the appearance of very good microprocessors as the first building
block that could be developed and improved outside of the personal computer industry. The
economics of mass production kicked in and more importantly horizontal industries appeared,
excelling in creating, not only better microprocessors but also better operating systems, application
software or distribution channels.

6 Grove, Andrew S. – Only the Paranoid Survive, Exmouth: Profile Books, 1997, page 45


Figure 6. Transformation of personal computer industry7

The financial services industry is now on the cusp of a very similar transformation. Similar to the
computer industry in the 1980’s, one of the things holds back changes is a lack of knowledge about
“how a bank works”. The body of knowledge about banking increases in the Fintech world as banking
professionals form their own companies in response to problems they encountered while working
with or for incumbent banks. In time, people will likely figure out what is the equivalent of the
microprocessor or the operating system for a bank and they will start building it. However, the
banking industry is very different from personal computers in that some of these new banking
“building blocks” are designed to serve millions of customers simultaneously and have technical
characteristics which are expensive and take time to develop. Creating these building blocks from
scratch requires significant investment, commitment, and determination. As in the case of computer
manufacturers developing the best microprocessors of their generation, one will need a high calibre
team to be able to create the architecture building blocks, which can stand-alone not only technically
but as businesses as well.

2. Telecommunications

David Isenberg’s articles “Rise of the Stupid Network”8 and “The Dawn of Stupid Network”9 should be
mandatory reading for anyone with an interest in financial services. Isenberg’s words were
revolutionary for the telecoms industry, though many did not initially agree with what he described.
Isenberg claimed that “assumptions are shortcuts to useful efficiency, provided that they are not
violated” and then went on to describe how the assumptions of what telecoms companies are do no
longer hold.

7 Grove, Andrew S. – Only the Paranoid Survive, Exmouth: Profile Books, 1997, page 44

8 Isenberg, David. “The rise of the Stupid Network.” Computer Telephony, August 1997, pg 16-26. Web
09 Apr. 2017. <http://www.hyperorg.com/misc/stupidnet.html>

9 Isenberg, David. "The Dawn of the Stupid Network." ACM Networker 2.1, Pp. 24-31, 01 Feb. 1998. Web. 09 Apr.
2017. <http://www.isen.com/papers/Dawnstupid.html>.


In a very similar way, the assumptions of what a retail bank is no longer hold, and the industry should
not continue to design and build as if the assumptions still hold.

Classic retail bank propositions were:

- A very expensive infrastructure was required in order to be a player in financial services e.g.
branches, secure data centres, etc.
- The retail bank revenue streams come solely from interest, fees, and charges for the
specific financial products and their associated events.
- Retail banking products are standardised and cannot be personalised, e.g. banks offer two
saving accounts and three types of mortgages
- There are few competitors in the market and the offering is so similar and switching so
difficult that there is a low risk of losing customers once they had signed with a bank.
- The bank owns the channels through which the customer can interact with the bank and
they also determine the rules of interaction.
- The number of transactions per person was quite low and limited to direct debits, larger
amount payments, salary, etc.

These rules either don’t stand anymore or they are on the brink of being broken:

- New players enter various segments of the value chain, which before were entirely the
domain of banks. They can do this at costs which are no longer prohibitive. An app costs much
less than a branch. Infrastructure-as-a-service is now a commodity. Large volume, event
processing is now the bread and butter of many digital propositions in other industries.
- Real-time tools for managing one’s finances would allow people to pre-empt charges or fees
being imposed mostly out of negligence and thus retail banks can lose an important revenue
stream. Cheaper and faster alternative methods for international transfers have emerged
leading to another revenue stream reduction. Most importantly though, as is the case with
other industries, data has value. Banks’ new revenue streams could emerge from acting on
customer insight obtained through meaningful data blending and real-time data analytics.
- The digital world creates the expectation of hyper-personalisation. People’s portfolio of apps
on their phone is a selection of services that satisfies one individual‘s needs. Retail bankers
cannot continue operating as if they can continue with “take it or leave it” approach to their
product offering and still be successful.
- Since mobile applications have become more and more prevalent, customers have become
more and more in control of their interactions with service providers. The bank was built for
a world where the branch was open from nine to five, five days per week. People would stay in
a queue and their requests were addressed sequentially and slowly. Communication between
systems was typically batched and scheduled. These days, customers do banking 24/7 and the
architecture of the bank has barely kept up with this change.
- The volume of transactions has increased significantly with the expansion of NFC and various
mobile payments methods. Depending on how IoT will evolve, it’s expected that this “new
world” can generate micro-payments, which can flow into retail banking as well. The current
architecture is simply not scalable to this degree.

Isenberg’s lens, applied above, underscores the limitations and issues addressed in the first chapters of
this paper. Below is a description of the building blocks which will possibly emerge.

C. The new building blocks of banking

1. The next banking channel – 3rd
party Fintech apps


Specialised financial services applications have already appeared to serve specific customer segments
(students, self-employed, migrants, etc.) or offer a smoother experience for international transfers or
trade finance. A quick review of global Fintech conferences reveals that most Fintech propositions
target the customer experience and a range of digital services that enable it, e.g. identification,
authentication, communication, etc. Most these services and apps cannot exist in isolation. At this
stage, they depend on integration with incumbent banks, and this is where most of them fail.

As other new building blocks emerge underneath this layer, these types of applications will be more
successful given that many of them address niche needs that no bank would have the capacity to
address. The explosion of 3rd-party banking apps would be consistent with the trend of hyper-
personalisation that transcends traditional industry barriers. It is still unclear where the balance will
fall between privacy – the desire not to be monitored by a “Big Brother” type bank – and the need to be
served seamlessly. Such balances are personal in the same way that risk appetite is personal.
Eventually, there will probably be multiple models of engagement, varying from no data sharing to
completely turning over personal financial decisions to automated algorithms.

While most of the Fintech community supports this vision of the future, very few look at why only a
small proportion of these manage to integrate with incumbent financial services institutions.

Figure 6 shows how the industry may change from vertical towers to horizontal industries where new
propositions are brought to life through the partnership between various building blocks belonging to
different horizontal industries.

Figure 7: Retail Banking Industry. Vertical tower functionality will be delivered through combinations of building
blocks, which can develop in horizontal industry segments.


2. Core banking services

As discussed in Chapter II, core banking systems are a very specific type of banking application. Over
time, many other applications flourished around them to accommodate the evolution of customer
channel requirements, communication methods, or regulation. Core banking systems have now
extended into an entire layer of applications instead of a single system.

When thinking about designing core banking services for the digital age this presents a number of key
challenges. Replacing the core banking system with a newer version of the same is no longer a viable
solution. Instead, the industry should look for a different kind of platform that covers a somehow
larger area of the banking architecture than current core banking systems strictly do. Such platforms
will also reduce the high barriers to entry for Fintech players trying to bring new customer
propositions to life. (see Chapter III. C.1).
What should this platform look like in order to run resiliently and at low-cost, and to enable the
emergence of relevant and highly personalised customer offerings as well as multi-regulatory low-cost
compliance?

Such a platform would have several essential requirements:
• Have the non-functional performance parameters at least at the same level as existing systems.
• Be a trusted log for customer transaction for any type of retail banking product.
• Have a product engine capable of:
o Defining any type of retail banking product
o Interrogating 3rd party applications on the characteristics of their products, and
mapping them back in the product engine. See Chapter III for the dimensions of retail
financial products.
o Trigger the creation of product specific transactions based on their financial
mathematical formulas (e.g. instalments, interest, etc.)
• Represent one source of data for transactional data for the rest of the organisation.
• Integrate downwards to specialist domain systems consuming transactions.
• Integration upwards across various customer channels
• Integration with payment systems

Currently, large and high-performing core banking systems exist only in banks. However, there are no
reasons why technology companies could not develop such platforms and operate them as a service.

Until now, regulation has focused only on banks because they were executing the full chain of actions
around the delivery of financial services. Eventually, as the functionality delivered by “verticals” will
fragment into building blocks, regulators will begin creating regulation that is specifically applicable to
certain types of functionality, such as transaction processing at scale.

3. Capital Management

Core banking does not represent all of the banking back office. Many think it is the case, because
discussions within the Fintech ecosystem initially centred on the most visible layers and eventually
expanded to include core banking. While this was a significant shift, other important layers are still
being overlooked, though over time these other elements will likely attract attention.

Considering the whole Application Catalogue of a bank and its distribution between the layers, 10% of
applications are in the digital layer and 15-20% are core banking systems and surrounding
applications. Underneath the layer of core banking and that of the data warehouses meant to store


volumes of transactions that cannot be stored in core banking, there are financial and management
accounting, tax, treasury, risk and their associated regulatory reporting solutions, representing more
than 50% of the application portfolio. This proportion is important to keep in mind because it
represents the hidden piece of the iceberg, a part that’s very much ignored by the Fintech revolution.

This part of the back office needs to move towards a more streamlined way of doing things, otherwise
the proportion of costs it represents kills any digital propositions layered on top. Core banking
systems drive the evolution and costs of this layer, which is in turn driven by regulatory forces. See
Chapter V. A. points 6,7,8.

The “deep back office” will change very much as well, once the core banking layer changes. Eventually
banks, some of which will focus on providing back-office services only, will become the capital
providers and will decide with which 3rd parties they will partner, depending on the risk profile of the
product and niche customers served by the respective applications. “Back office only” types of players
are beginning to emerge, with Cross River Bank and CBW Bank from the US emphasizing their
capability to partner in this way with Fintech players. There may be others which position themselves
in a similar way not discovered by the time of writing.

4. Who puts the deal together?

A banking vertical may break into these three large building blocks as described, however the whole
might fracture across other lines as long as other pieces of functionality can be segregated and
optimised when running at scale, as a service to many players.

When the industry changes the operating mode from vertical towers to building blocks, which can
operate as independent businesses, there is a need for another type of player to assemble the building
blocks into a fully-operational proposition. Whether such a player is another type of banking service,
or is a mix of consultants and lawyers, remains to be seen.

These dealmakers will have the ability to negotiate revenue and cost sharing models which did not
exist before a multi-player configuration emerged. They will also be responsible for matching the risk
appetite of capital owners (banks) to the risk proposition of niche customers or new products.

The regulator will be also faced with a new type of agent, who will play an important role in the
market. This poses important questions such as who will regulate this domain, and whether the limits
of their responsibilities and obligations will be regulated.


VI. Conclusion

While the architecture of banking can be left to specialists, the state of retail banking and how it affects
the larger world is of concern to everyone.

Retail banking is wrongly considered a complicated domain, and not a complex one. The banking
industry creates very rapid and important effects on many social systems, and therefore the same
frameworks and ways of thinking used for ecosystems and complex systems should apply to banking.

If banks were akin to buildings and financial crisis peaks akin to earthquakes, then architecturally, the
banks have not been built for earthquakes and this is very dangerous. One would argue that the
structures to take care of the resulting damage exist, but ideally the “buildings” would have the
flexibility required so the earthquakes lead to less damage. The rigidity of the banking towers and the
regulatory protection unique to this industry prevent them from absorbing shocks, and instead send
powerful ripples into other social systems.

One of these ripples is that there will be more and more unbanked in the Western world, including
people and small companies who can make a living but don’t make enough money for the incumbent
banks to accept them as clients. If the incumbent banks do not develop an infrastructure capable of
functioning in real-time and at a reasonable cost for all members of the society, such infrastructure
will necessarily develop alongside the existing banks.

An economy with low interest rates, compounded by the social and political uncertainty brought by
Brexit, cannot absorb the development of new banking propositions as fully-vertical towers. Some
economies of scale need to be achieved for common processes, which the technology of today permits
to be delivered at a fraction of a cost and at better performance parameters. This would be possible
through the development of horizontal platforms serving multiple specialised players. These platforms
are doubtlessly being developed currently, and once they are operational will challenge traditional
technology vendors, which for years lived in symbiosis with the banks they served.

The Ripples of Core Banking

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