Mac Reserch For Corporate Asset Finance Mac 2017 Research Paper

5526 words - 23 pages

The Fintech 2.0 Paper:
rebooting
financial services
Why a paper for Fintech 2.0?
This paper for Fintech 2.0 has been created by Santander
InnoVentures, in collaboration with its partners Oliver Wyman and
Anthemis Group.
The purpose of Santander InnoVentures is to help Santander
deliver better services to our customers through innovation, and to
support a new generation of fintech start-ups on their growth
journey. We believe these goals are inextricably intertwined.
Oliver Wyman’s Innovation Platform has been established to
advise both its traditional client base and fast growth fintech firms
on the transformational change that is currently underway in the
financial services industry.
Many fintechs have succeeded but today they are still operating only at
the edges of banking. To help engineer more fundamental
improvements to the banking industry, they must now be invited inside,
to contribute to reinventing our industry’s core infrastructure and
processes. That can succeed only as a collaborative endeavour, with
banks and fintechs working together as partners.
This paper highlights the benefits of collaboration and identifies some of
the opportunities for profitable change in realising Fintech 2.0. We hope
the whole industry – both banks and fintechs – recognise the value of
this approach and join us in this collaborative journey to Fintech 2.0.
2
Mariano Belinky,
Managing Principal, Santander InnoVentures
Emmet Rennick,
Head of Innovation, Oliver Wyman
Andrew Veitch,
Director, Anthemis
3
4
6
8
1. Fintech 2.0
2. Applications for the Internet of Things
2.1. Cutting costs in trade finance
2.2. Improving valuation accuracy of real assets
in leasing and asset financing 10
3. Being smarter with smart data 12
4. Embedding distributed ledger technology 14
5. Creating frictionless processes and products 16
5.1. Opportunities to reduce friction in the mortgage process 16
5.2. Frictionless saving and investment 18
6. Conclusion: achieving Fintech 2.0 together 19
Contents
4
Over the last decade, however, a new source of innovation in financial
services has emerged from financial technology start-ups (“fintechs”) and
technology companies (“techos”). These new firms have been quicker than
banks to take advantage of advances in digital technology, developing
banking products that are more user-friendly, cost less to deliver and are
optimised for digital channels.
This relative success is unsurprising. These new players are less burdened by
the demands of regulatory compliance which banks are subject to. They are
unencumbered by complex and costly to maintain legacy systems. They
can focus on creating single-purpose solutions, designed to offer an
improved experience within just one product or service. They are more in
tune with the peer-to-peer (P2P) culture engendered by the explosion of
social media. And they are smaller organisations, designed for the purpose
of innovation.
Capital has flowed into the fintech sector: $23.5 billion1 of venture capital
investment in 2013/14. Of this investment, 27% has been in consumer
lending, 23% in payments and 16% in business lending. Fintechs have
two unique selling points: better use of data and frictionless customer
experience. But to date these have been limited to relatively simple
propositions such as e-wallets and P2P lending.
The impact of fintechs to date
After a slow start, fintechs are now capturing a growing market share
in these areas. Yet their overall effect on the banking market has been
minor. Banks have not crumbled in the face of this new competition. We
characterise this first phase of fintech as Fintech 1.0.
Yet the conditions for significant change are present: policy shifts towards
open data and APIs2, the emergence of enhanced technologies such as
cloud computing, changing customer dynamics and intense pressure to cut
costs in banking.
We believe that by extending the use of data and frictionless processes
Fintechs can and will expand well beyond the confines of payments and
consumer credit. It will move deeper into middle and back office processes
providing new, richer propositions for end customers.
Fintech 2.0 is just around the corner. It will deliver fundamental changes
to the infrastructure and processes at the core of the financial services
industry. In this report we consider some important banking innovations
based on the “Internet of Things” (IoT), smart data, distributed ledgers and
frictionless processes beyond payments and consumer credit.
1. Fintech 2.0
Banks can boast of some important innovations. ATMs, credit cards, securitisation,
swaps and mobile banking are now taken for granted, but each was ground-breaking
when first launched.
1 Source: Oliver Wyman analysis.
2 Application Programming Interfaces.
5
Fintech 2.0 will cause a major disruption of the banking market,
as digital technology has in other markets, such as travel and
entertainment. Pre-digital business models and processes will be
rendered obsolete, and billions of dollars of value will shift to “new
model” suppliers.
Banks are aware of these changes and the opportunities they present. Many
have decided they need to participate in this disruptive trend by actively
supporting fintechs – the list includes Citi, Santander, UBS, BBVA, Barclays,
NAB and Capital One, among others. They have launched incubation and
acceleration initiatives, and created investment vehicles to harness, foster
and scale up innovation.
While banks have disadvantages relative to start-ups, they also have
advantages. Being regulated is a burden in many ways, but it creates
consumer confidence. A long history brings legacy systems with it, but it
also builds trusted brands (albeit tested by the global financial crisis) and
provides rich historic data, not to mention a banking licence and a sizable
head start in compliance initiatives. And, of course, banks understand
banking; especially the risks involved, which new entrants often do not.
Collaboration is the key
The strengths and weaknesses of both banks and fintechs mean that
both will often do better by cooperating rather than by competing.
New digital businesses must either grow quickly or die. Banks can offer
fintechs immediate scale and critical mass through access to demand.
While some fintechs are today focused on the race to build standalone
“Unicorns” (a company with a $1 billion valuation), we believe
Fintech 2.0 represents a far broader opportunity to re-engineer the
infrastructure and processes of the global financial services industry, in
which the top 300 banks command a revenue pool worth $3.8 trillion3.
This is the central premise of this report: that, to realise the
opportunity of Fintech 2.0, banks and fintechs will need to collaborate,
each providing the other with what it now lacks, be that data, brand,
distribution or technical and regulatory expertise.
Only by collaborating will the opportunity of Fintech 2.0 be realised.
3 Sources: Forbes, 2015; Oliver Wyman analysis.
6
The number of objects able to record and transmit data to other objects
is continually rising. 50 billion objects are expected to be linked to the
internet by 2020.4 This network of connected devices creates continuous
streams of data which can increase efficiency across a wide range of
business practices.
Many applications already exist: in transport, tracking when a bus
will arrive; in pharmaceuticals, monitoring temperature-sensitive
products; and in insurance, monitoring the driving style of car owners to
preferentially price premiums for safer drivers. As the cost of sensors and
data transmission continues to reduce, we are reaching a tipping point
where commercial use of the IoT will take off.
In financial services, compelling uses have not yet emerged into the
marketplace. But the IoT could have many valuable applications (see
Figure 1), including:
n Product design: Asset financing, for example, could be based
on parameters such as kilometres driven or load carried rather
than simply the period of time for which the asset is leased, as with
traditional models.
n Risk management and pricing: Collateral management is a key element
of risk management. Better data on the quality and condition of collateral
provides more accurate assessment and pricing of risk.
n Understanding customer needs: Tracking a business’s activity could
indicate when it may have additional growth financing needs, for
example, by revealing when leased machinery is working at full capacity.
n Streamlining contractual processes: IoT devices will be able to capture
data and feed it into digital platforms that govern and verify “smart
contracts” (computer protocols that verify or enforce contracts). The
collation of real-time data on these platforms can facilitate efficient
covenant monitoring, automatic disbursement of assets and automatic
release of liens or goods.
2. Applications for the Internet
of Things
The “Internet of Things” (IoT) describes the widespread embedding of sensory and
wireless technology within objects, giving them the ability to transmit data about
themselves: their identity, condition and environment.
4 Source: Cisco.
1 Monitoring & data transmission 2 Data collection & management 4 Valuecreation
Financial product
development
Risk management &
pricing of finance
Identifying additional
business needs
Streamlining
contractual processes
3 Strategicanalytics
kg
Pl
at
fo
rm
to
m
an
ag
e
da
ta
a
nd
d
is
tr
ib
ut
io
n
7
Figure 1: Application of the Internet of Things in Financial Services
8
2.1 Cutting costs in trade finance
Global trade finance is a complex process. A dizzying number of manual checks
must be carried out to verify the legitimacy of a client, its trading partners and the
goods that change hands. Most checks require the physical presence of a person,
and the administrative work conducted by bank middle offices is overwhelmingly
paper-based. The high cost of this process restricts access to trade finance for
smaller businesses and especially those in developing economies whose
credit-worthiness is difficult to establish (see Figure 2A).
We expect the IoT, combined with the distributed ledger and smart
contracts, to dramatically reduce these costs. Specifically, we expect the
IoT to streamline the trade finance process as follows:
n IoT technology will provide banks with real-time access to trade data,
eliminating the need for manual checks and paper documentation such
as bills of lading. For example, GPS data would automatically alert the
issuing bank once a shipment arrives at a port, and sensory technology
would provide information on the condition of delivered objects. The
IoT could give sellers and their banks access to real-time information
they need regarding goods in transit.
n Access to real-time trade details would enable digitised smart contracts
to be verified instantaneously, assuming pre-defined conditions are met.
This would allow a letter of credit to be issued more efficiently than in
today’s trade finance process.
n By providing accurate, real-time data on trade flows, trade relationships
and performance, the IoT can provide information required to
underwrite trade finance. This transparency will make trade finance
available to SMEs that would otherwise find it difficult to obtain
credit approval. Storing this information on a platform will assist
in due diligence of new customers. Such platforms will also help
smaller suppliers of trade finance identify opportunities where they
enjoy a competitive advantage, such as local knowledge or a better
understanding of specific risks.
This is illustrated in Figure 2B.
International trade is expected to grow by 8% per annum until 2020, with
associated trade finance revenues growing to $70 billion.5 This represents
a massive opportunity for both banks and fintech start-ups to partner and
streamline trade finance processes in the ways described. In doing so, they
will achieve more than cut operating costs. Improved data and analysis of
exposures will also reduce losses and, by increasing the scope of potential
clients, increase revenues.
Manual
pre-screening
Letter of credit Manual checks Contracts manually
completed
Shipping
arranged
Paper-based verification
to be completed
Manual KYC and due
diligence is time consuming.
Limited access to data
means many SMEs cannot
access finance.
Lack of transparency
over exact condition
of goods in transit.
Process of manual
checks is costly and
creates a higher
turn-around time.
Unavailability of
authorised signatories
to sign the
paper requests.
Pain points
A: Pre-IoT trade finance
Real time capturing
of trade data
Letter
of credit
Real time
monitoring
Small contract
auto filled
Shipping
arranged
Real time verification
and digital submission
Better underwriting and
credit decisions.
Authorisors can approve
requests remotely.
Better knowledge of the
condition of goods. End
customers can track their
goods improving trust.
Verification of goods
is more reliable and
in real time.
Elimination of
documentation
speeds process
and reduces costs.
Advantages
B: Post-IoT trade finance
One online platform
Multiple platforms
9
Figure 2: Diagram of pre- and post-IoT trade finance highlighting advantages of the IoT
5 Source: SWIFT, 2013.
10
IoT technologies can help banks overcome this problem, allowing them
to monitor the condition, environment and location of collateral assets
without needing to send someone to assess them. They can provide
something close to the accuracy of an in-person assessment at a fraction
of the cost. Such technology could be applied across a wide range of
collateral as illustrated in Figure 3.
Inefficiencies in the global collateral management market are
estimated to cost banks up to $4 billion annually.6 Adopting IoT
technology could significantly reduce this figure as real-time
monitoring technology will improve valuation accuracy and render
more assets eligible for collateral financing.
2.2 Improving valuation accuracy of real assets in
leasing and asset financing
Monitoring and valuing collateral leased or financed by banks is made inefficient by
the cost of getting detailed information about the asset concerned.
11
6 Source: Collateral Management – Unlocking the Potential in Collateral, Accenture and Clearstream, 2011.
Real Estate (mortgage)
Commodities
Fleet vehicle leasing
Flag when vehicles require
maintenance and also allow financers
to have a better understanding of a
vehicle’s present value
Provides information on the current
condition of the house for valuation
and insurance purposes
Monitoring the condition of
commodities during transit allows
financers to know if the condition
of goods delivered meets
contractual specifications
n Hours in operation
n Distance covered
n Engine diagnostics
n Driving behaviour
n Weight of load
n Terrain driven on
n Environmental factors –
pollution, temperature, flooding,
general weather patterns
n Water damage/ damp
n Interior decay
n Local economic trends,
observable, for example, in
local transport usage and
shopping patterns
n Temperature and
moisture level exposure
n Weight
n Vibrations
n Exposure to chemicals
n Location
n Speed of travel
Asset Data Capture Application in financing
Figure 3: Applications of IoT technology in asset financing
12
3. Being smarter with smart data
Digital technology has greatly increased the volume of data available. However, the banks
have found it difficult to use this new data to create value for their customers and themselves.
In contrast, online retailers and social media firms have found ways to create value from data.
7 Source: Oliver Wyman analysis.
Some of the ways in which online retailers create value from data:
n Customer transaction behaviour is used to inform product
suggestions, increasing sales and customer loyalty.
n Viewing and listening behaviour is monitored to give appropriate advice
about new products and services, or to serve third-party advertisements.
n Real-time or contextual satisfaction surveying is used to flag
when a customer is dissatisfied and to inform appropriate actions
to retain them.
n Location data is used for security and fraud checks or to offer
suggestions, advertisements and offers that depend on the
customer’s location.
Despite substantial investment in data management, financial institutions
lag behind firms in other industries. It is not unusual for large banks to
spend upwards of $500 million7 on programmes to address the challenges
related to data, yet it is widely acknowledged that these investments have
not been translated to increased profits. Banks are not nearly creative or
enterprising enough in their attempts to use data to offer better products
or cut operating costs.
The sheer variety of problems which data can address calls for specialised
capabilities which banks often lack. Banks could take advantage of the
specialised expertise at fintech companies by engaging these firms to
perform the required work or by acquiring them. Partnerships between banks
and fintechs would create a powerful combination of information, supplied
by the bank, and innovative analytical tools, supplied by the fintech. The kind
of problems that might be addressed are illustrated in figure 4.
Identifying problems that can be solved by data is the first step to
its smarter use. Assuming banks make their data readily accessible
to those who need it, specialised teams can be assigned to problems
such as these and create algorithms that uncover trends, patterns and
anomalies. Then banks will be able to extract value from their ever-
increasing supply of data.
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“Right time and
channel to contact”
A blend of transactional, locational, communications and social media data can indicate times when customers
are likely to be available. This has applications in marketing, customer engagement and collections.
Fraud and market
manipulation
Some fintechs, such as Red Owl Analytics and Pentaho have developed software that helps banks to visually track
who has influenced content in their data networks. This allows banks to “connect the dots” across a wide variety of
data sources such as transactions, communications, physical access and digital data, and flags any unusual patterns
between them. Understanding patterns that might constitute fraudulent behaviour and combining this with post-
incident analysis helps banks to uncover fraud. Similarly, “know your customer” (KYC) checks could be helped by
verifying the link between income and spending habits, location and stated occupation.
SME Credit
By utilising customer spending behaviour and supplier performance data, banks could help SMEs manage their
cashflow and credit line requirements. Access to regular trade data, via the Internet of Things and point-of-sale
systems, could help banks with credit scoring for growth capital and working capital needs. This would allow them to
pre-empt SME financing requests so that they can provide real-time credit to match their clients’ needs.
Budgeting
Historical account data can give banks a granular view of customer spending and income patterns. By coupling these
observed patterns with customer saving goals and aspiration, banks could offer budgeting advice. This would also
help consumers and business clients understand the long-term budgeting implications of potential decisions. Fitechs
such as Personetic and Geezo now use banks’ data and external sources to provide a more holistic and personal
experience to customers.
Figure 4: Applications of smart data
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Clearing
House
Centralised Ledger Distributed Ledger
In contrast to today’s transaction networks, distributed ledgers
eliminate the need for central authorities to certify ownership and clear
transactions. Distributed ledgers can be open, verifying anonymous actors
in the network, or they can be closed and require actors in the network
to be already identified. The best known existing use for the distributed
ledger is the cryptocurrency Bitcoin.
Distributed ledger technology has several attractive features:
n Transactions can be made to be irrevocable, and clearing and
settlement can be programmed to be near-instantaneous,
allowing distributed ledger operators to increase the accuracy of
trade data and reduce settlement risk.
n Systems operate on a peer-to-peer basis and transactions are
near-certain to be correctly executed, allowing distributed ledger
operators to eliminate supervision and IT infrastructure, and their
associated costs.
n Each transaction in the ledger is openly verified by a community
of networked users rather than by a central authority, making
the distributed ledger tamper-resistant; and each transaction is
automatically administered in such a way as to render the transaction
history difficult to reverse.
n Almost any intangible document or asset can be expressed in code
which can be programmed into or referenced by a distributed ledger.
n A publicly accessible historical record of all transactions is created,
enabling effective monitoring and auditing by participants,
supervisors and regulators.
Commercial banks, central banks, stock exchanges and major
technology providers, such as IBM and Samsung, are all exploring the
potential uses of distributed ledgers. Fintechs, such as Ripple, Ethereum,
Eris Industries10 and HyperLedger, are also developing new ways to
exchange data and assets enabled by the technology. It is only a matter
of time before distributed ledgers become a trusted alternative for
managing large volumes of transactions.
4. Embedding distributed
ledger technology
A distributed ledger is a network that records ownership through a shared registry
(see Figure 5).
Figure 5: Centralised and distributed ledger approaches
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CustodySettlement
Collateral
managemet
and valuation
Life cycle
management
ClearingMatching
Post trade life cycle
Scope for
distributed
ledger
technology
■ Smart contracts can
enable automated
clearing upon
trade completion
■ Real time updates
on security title and
interests updating
■ Allowing access to
multiple users for
robust monitoring
■ Increased transparency
as information
asymmetries
are eliminated
■ Real time updates on
the positions of the
underlying collateral
with consistent
valuation methodologies
■ Securely,
transparently move
securities and assets
in seconds or minutes
■ Enables point-to-point
settlement, lowering
the cost and risk
of transactions
■ Smart contracts can
facilitate robust
custodian services on
decentralised platforms
eliminating intermediaries.
The first major application is being seen in payments, especially across
borders. International payments remain slow and expensive and
significant savings can be made by banks and end-users bypassing
existing international payment networks.
In time, distributed ledgers will support “smart contracts” – computer
protocols that verify or enforce contracts. This will lead to a wide
variety of potential uses in securities, syndicated lending, trade finance,
swaps, derivatives or wherever counterparty risk arises. For example,
smart contracts could automate pay-outs by the counterparties to
swap contracts. Figure 6 examines how securities settlement could be
transformed by distributed ledgers.
Cutting operational costs is not the only benefit in securities trading.
Distributed ledgers can increase investor confidence in products whose
underlying assets are now opaque (such as securitisations) or where
property rights are made uncertain by the role of central authorities.
Our analysis suggests that distributed ledger technology could reduce
banks’ infrastructure costs attributable to cross-border payments,
securities trading and regulatory compliance by between $15-20 billion8
per annum by 2022.
8 Sources: World Bank remittance data; World Federation of Exchanges; Oxera; Financial Times; Oliver Wyman analysis.
Streamlining securities settlement
The post-trade, settlement process can be expensive and slow, commonly taking two days, and sometimes longer, to process through a
number of intermediaries. Distributed ledger technology has the potential to overcome frictions in current post-trade processes, providing an
alternative technology for clearing and settlement.
Figure 6: Scope for distributed ledger technology in the post trade settlement process
16
Banking is no exception. Not only can customers now shop for banking
products online but the products themselves are being digitised. It is now
possible to manage accounts and make payments to third parties without
visiting branches, writing letters or signing and posting cheques. Digitisation
is taking much of the pain out of banking.
This progress, however, has been limited mainly to transaction accounts and
consumer lending. Mortgages and long-term savings products still involve
processes that are expensive, time consuming and a source of customer
dissatisfaction. Removing the “friction” from these products is where the
greatest opportunity now lies.
5. Creating frictionless
processes and products
Digital technology has taken the hassle out of shopping. Customers can now
compare options, choose, pay and often receive the goods, such as an e-book or
airline ticket, on any device with access to the internet. What might have taken hours
of walking or driving around and talking to sales people can be done in minutes or
even seconds without leaving home.
9 Source: Oliver Wyman analysis.
This provides opportunities to digitise the process, removing much of its
current friction. We envisage a simple yet robust home purchase process
based on an improved data environment. See Figure 7 for a description of
the Danish house purchasing process where much of the friction that exists
in other markets has been removed.
5.1 Opportunities to reduce friction in the
mortgage process
With over $25 trillion9 in new mortgages issued annually across the globe the
mortgage sector is a very big market. However, most mortgage markets still rely
on a number of intermediaries to manage a predominantly paper-based process.
17
Buyer
Seller
Customer affordability information
Online home search
Lists property
e-signature
from both the
buyer and
seller, to
execute
transaction
Prepares draft
Property Data
Final checks to
release funds
Property Data
Transaction Details
Mortgage providor
Seller’s bank
Electronic Purchase
Agreement
Real Estate
Platform
Electronic Land
Registry
Figure 7: Danish house purchase process
Buying a house in Denmark
n As a house becomes available for sale, a prospectus of the house
is published on a real estate portal. The prospectus provides
the public valuation, ownership, and financing details, energy
rating, environmental issues and technical survey details. This
collateral information will be available to prospective buyers and
to all banks (through the electronic land registry) who can then
immediately assess the value and the condition of the collateral.
n A prospective buyer searches for a house on the real estate
portal and contacts the agent appointed by the seller. In a
parallel process, the buyer engages a mortgage bank and gives
them permission to access their financial records, including
salary details that show that the borrower can afford to service
the mortgage. Combined with the collateral valuation, this
allows the bank to approve a mortgage.
n After contacting the agent and viewing the property (perhaps
online), the buyer agrees a price with the seller. The buyer and
seller electronically sign a standardised Purchase Agreement
using their electronic ID.
n An authorisation is sent to the buyer’s bank to transfer funds to
the seller’s bank. The funds are released to the seller once all final
conditions are met on the agreed closing day.
n Once the funds have been transferred to the seller, the electronic
land registry is updated to reflect the new owner’s details, and
the transaction details are made available as an input to property
pricing in the local area.
18
For example, new technology monitors customers’ spending habits,
allowing them to manage their money better (e.g. Mint, Yodlee,
Blueleaf10). And algorithm-driven tools or “robo-advisors” provide
investment recommendations based on stated investment goals
(e.g. SigFig, FutureAdvisor, Betterment10).
This has helped reduce friction within some saving and investment
activities, but we believe there are further opportunities:
n Personal financial management (PFM) solutions typically help
customers make better decisions about their spending habits but
not about their savings and investments. New applications could
unify investment, savings and current accounts, allocating funds
according to user-defined triggers (e.g. a particular savings goal). This
information could be linked to external data such as merchant offers.
For example, a customer who wanted to buy a new phone could add
the phone to a wish-list as part of their budgeting and savings goals.
n Algorithm-driven investment platforms typically focus on just a few
variables, such as asset diversification and risk tolerance, without
taking account of other important variables, such as the customer’s
current investments, especially where these are not tradable
securities. These platforms will be better able to compete with
traditional financial advisory offerings if they take a comprehensive
view of all the assets a client might invest in or already has, both real
and financial.
n Fintech players could automate several basic PFM services, such as
estate planning (e.g. setting up trusts), life insurance and basic tax
planning. Current robo-advisors can extend their offering up the
wealth spectrum, for example, to include people worth $1 million, who
are now served face-to-face at a cost that is often not commensurate
with the upside.
5.2 Frictionless saving and investment
Many people seek help managing their personal finances and making investment
decisions. This has traditionally been an area dominated by expensive face-to-face
interactions with financial advisors. However, fintech alternatives have now emerged.
10 Anthemis portfolio company.
After origination, mortgages have typically remained on bank balance
sheets or been transferred to investors via securitisations. While investors
are showing an appetite for direct exposure to whole-loan mortgages, the
majority of equity stays in banks.
For institutional investors, whether they are looking for whole loans or
participation via securitisation, gathering and providing the growing amount
of granular information that is becoming available through seamless
real-time reporting will be highly valuable. A mortgage platform providing
regularly updated data on the condition and value of collateral and on the
financial situation of the mortgagee will allow investors to manage their
portfolios with far more precision (see Figure 8). The information available
would include demographics (e.g. age), location, income and affordability
profile, financing type (e.g. mortgage rate, duration, payment profile), risk
profile (e.g. borrower’s credit rating, behavioural information) and detailed
collateral information (e.g. type of property, age of property, condition).
Data and Analytics LayerOriginating Strategy Investor Asset Selection
Rich layer of granular data
and analytics
Front to Back Customer Management
Figure 8: Key features of an end-to-end mortgage platform
19
Conclusion: achieving
Fintech 2.0 together
Fintech 1.0 has brought only minor disruptions to the banking market, mainly
in the areas of payments, credit and personal financial advice. But changes
in customer preferences, advances in technology and growing investment in
fintech set the scene for more radical change.
Fintech 2.0 could mean a “seamless specialisation” across core elements of
the value chain whereby a variety of providers combine to deliver cheaper and
easier-to-use propositions to end customers.
Banks must continue on their journeys of digitisation. But they need not
travel alone. They should be clear about where their market advantages and
institutional strengths lie. Where they fall short they should look to work with
the start-ups who can provide what they need.
The same goes for the new fintechs. They may be entrepreneurial and
ambitious but there is more required to achieve Fintech 2.0. Wisdom, market
expertise, trusted brands and not least a banking licence may also be required.
The message to banks and to fintechs is the same: if you can’t beat them, you
should join them to achieve Fintech 2.0.
Copyright© 2015 Oliver Wyman, Anthemis Group and Santander Innoventures. All rights reserved. This report may not be reproduced or redistributed, in whole or in part, without the written permission
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