Super Apps in Financial Services - Business Models and Opportunities
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81
SECTOR BRIEFING
DBS Asian Insights
DBS Group Research • September 2019
Super Apps in
Financial Services
Business Models and Opportunities
DBS Asian Insights SECTOR BRIEFING 81 02 Super Apps in Financial Services Business Models and Opportunities Sachin MITTAL sachinmittal@dbs.com LIM Rui Wen ruiwenlim@dbs.com Produced by: Asian Insights Office • DBS Group Research go.dbs.com/research @dbsinsights asianinsights@dbs.com Wen Nan Tan Editor Martin Tacchi Art Director
DBS Asian Insights
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04 Executive Summary
07 What are SuperApps?
Features of a Game Changing SuperApp
Potential Disruptors in Asia
Proliferation of SuperApps
Regulatory Risks of SuperApps
12 SuperApps: Implications on Financial Services
Virtual Banks
Robo-advisors
Insurance
34 Ride-sharers in the Insurance Space
Grab
Go-Jek
Didi
36 Looking Ahead: The Future for Traditional
Players
An Integrated Model: A Possible Road to Profitability
42 References
DBS Asian Insights
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04
Executive Summary
The SuperApp phenomena began in China with Alibaba and Tencent positioning themselves
at the heart of China’s internet infrastructure. These Apps allow users to access several features
that would only be available through multiple apps and cross-sell to their large customer base.
Key feature of a SuperApp
Large user base with Superior data analytics Agility in working with
frequent engagement other players
Source: DBS Bank
Ride-sharers’ search for profit in banking and
insurance via SuperApps
Despite strong potential for growth in the ride-sharing industry, major ride-sharers are
struggling to generate profits. Embracing a SuperApp approach is potentially the silver lining
to ride-sharers’ woes. Some inherent features of ride-sharers may qualify them to become
SuperApps in the future. Based on our proprietary framework, we attempt to identify which
popular apps are positioned well to qualify as SuperApps in their respective countries.
Potential SuperApps in Asia
Source: DBS BankDBS Asian Insights
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In this report we explore whether popular Apps will take advantage of the sweet-spot they
are currently in, to emerge as SuperApps and what will be their impact in the banking and
insurance sectors?
How would the contest to become SuperApps
impact banking?
Popular Apps around the globe are exploring the possibility of venturing into financial services,
often starting off with digital wallets and payments. Success in mobile payments is a big factor
in determining the quality of consumer data while regulations is the other key variant. The
larger the percentage of unbanked population in the country, the bigger the opportunity.
That said, in markets with smaller unbanked population and more regulatory restrictions,
there are opportunities for incumbents to capture market share from others if they collaborate
with SuperApps to target their customers. New entrants looking to penetrate markets such
as Singapore and Hong Kong should also look at utilizing a more integrated banking model
which ventures beyond the traditional deposit taking and credit model, to successfully battle
well-established incumbents.
Indonesia, Philippines & Vietnam present huge potential with 60%-70% of
population being unbanked
Vietnam
Source: DBS Bank
What should traditional banking players do in the face of the threat from SuperApps?
How should the
incumbents respond?
Collaborate Retaliate Co-Exist
Partner with the new entrants Counter offers by the new Cede the niche markets to
if such partnerships expand entrants aggressively and the new entrants to focus on
the addressable market of the seek strategic alliances to digitisation and improving
incumbents expand into the niche market service offering to your current
segments target marketDBS Asian Insights
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How would the contest to become SuperApps
impact insurance?
Much like the banking industry, the insurance industry in Indonesia and the Philippines
present large opportunity with >90% of population not having any insurance in place. The
big challenge for new players is mostly the lack of enough customer data and a distribution
channel accessible to a large chunk of the population. We believe some of the popular
SuperApps resolve these challenges by acting as digital distributors for new or existing insurers.
Indonesia, Thailand and Philippines Insurance Industry present big opportunities
for SuperApps
Source: DBS Bank
What should traditional insurance players do
in the face of the threat from SuperApps?
Popular Apps are unlikely to cause major disruption in the insurance sector, given the inherent
difficulties in setting up insurance operations including risk management, regulatory approvals
etc. Partnering up with the popular Apps for the distribution of products might unlock a
substantial unserved market for the incumbents
How should the
incumbents respond?
Partner
Partnering up with the SuperApps for the distribution of insurance products
might unlock a substantial unserved/underserved market for insurance for
the incumbents.DBS Asian Insights
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What are SuperApps?
A Super Application (SuperApp) essentially allows users to access, on a single platform, separate
features conventionally only available on different applications by building an ecosystem of
seemingly unrelated services. WeChat is one such example which evolved from a simple
messenger application to a SuperApp with functionalities across social media, banking, online
shopping, food and grocery delivery, taxi hailing, healthcare, etc. Other examples include
Alipay, PingAn and Go-Jek.
SuperApps create an ecosystem surrounding its target audience, unearthing opportunities to
cross-sell services and improve customer stickiness within the platform. They are often fairly
difficult to create, requiring first a large mobile customer base and the need to aggregate a
set of compelling and frequently used services.
Tencent’s WeChat platform is one of the best known examples of a SuperApp
Content E-Commerce
WeChat Super-App
Transport Financial Services
Food Delivery
Source: Tencent, DBS BankDBS Asian Insights
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Features of a Game Changing SuperApp
Large user base with Superior data analytics Agility in working with
frequent engagement Customer Data Platforms other players
A Large user base attracts provide a well-integrated 360 Openness for partnerships
partners easily while frequency degree of each customer, and development of APIs to
of usage, makes the app top- which was not possible few support easy on-boarding of
of-the-mind years ago partners and minimise time-to-
market of new services
Source: DBS Bank
1. Large user base with frequent engagement
SuperApps require a large base of customers that interact with the platform frequently
to collect troves of customer data to support the marketing of other services, attract
partners to its platform and amass sufficient demand for new services. SuperApps
also have to be well integrated with the lives of the customers and have to be
platforms that customers visit and use on a regular basis.
2. Improvement in data analytics especially Customer Data Platforms (CDP)
Developments in CDP bring together disparate data from customers into a single
environment to provide a well-integrated 360 degree view of each individual
customer. This was not possible few years ago when most companies adopted a
more singular approach, targeting users based on IP addresses, with no additional
information on age, sex or real time needs. While companies had access to a plethora
of data, a true 360-degree view of customers was not available. This was so as first
party data tend to focus only on specific customer needs served by the company.
By offering services across different sectors, corporates can widen their view of the
customer, thereby allowing them to successfully implement a CDP platform and gain
insights into customers therefrom.
3. Agility in working with other players
Openness to form partnerships and willingness to share the platform and its customer
base to other partners are essential features for the creation of Superapps. Availability
of an ecosystem of Application Programming Interfaces (API) to allow communication
between different platforms also remain essential for SuperApps. This would ease theDBS Asian Insights
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process of onboarding new partners, and lessen the time to market of new services.
Openness of new technology players and developments in APIs have been critical for the
success and evolution of SuperApps.
Distinctively, SuperApps that have emerged in China are predominantly mobile wallets. This is
driven by poor penetration of alternative payment mechanisms to cash (such as credit cards),
growing penetration of smartphones and a higher base of younger population. Mobile wallet
is likely to be one of the most frequently used ecosystem-platform by consumers in Asia.
Mobile wallet players also capture customer data about purchases across various sectors and
develop APIs to work with various players.
Key mobile wallet players in Asia
Philippines
Indonesia
Vietnam
China
Malaysia
Thailand
SingaporeDBS Asian Insights
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SuperApp Framework
Parameter Definition Criteria Score
User Base & Engagement
User Base Market reach (Market share or Customer Reach) in >60% 6
the country/region with core operations. 30-60% 4
>30% 2
High Engagement Mobile payments reach (No. of users as a % of >60% 6
customer base or population or estimated no. of 20-60% 4
downloads as a % of target market reach.
5-20% 2
5 3
developments through partnerships/JV etc. 2-5 2
100 3
past 2 years 20-100 2DBS Asian Insights
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SuperApps that leveraged on the myriad of factors to build out their platforms. This, however,
may not be the case elsewhere.
In developed markets like Singapore and Malaysia, there is a high likelihood for SuperApps to
emerge as different players focus on bundling services targeting different customer niches and
needs. For example, local telecom players are developing a utility-services focused ecosystem.
Regulators may also intervene in these markets to ensure that customer data is not held
hostage by a few dominant entities. This is to ensure that benefits of customer data and
analytics are more wide-spread across segments.
The landscape is somewhat different in developing markets as some popular applications
have already begun their transition to SuperApps. Go-Jek has positioned its platform as
an application for “all needs”. The ride sharer presently provides services that caters to
transportation, delivery and logistics and payment needs of customers. Further to which,
it also provides auto-mechanics and cleaning services. Competition for ride sharers from
banking, telecom and other customer-centric sectors remain fairly muted in many developing
markets. Regulatory restrictions on electronic data collection and protection are also in early
developmental stages.
Regulatory Risks of SuperApps
Data Protection & Information Privacy Regulations Anti-trust Regulations
The principles behind Data Protection regulations Anti-trust regulations promotes and enforces
require SuperApps to use data lawfully and market competition in order for consumers to
with transparency to ensure data integrity and enjoy the benefits of competition such as lower
confidentially1 prices and market efficiency2
SuperApps collect large volumes of private data SuperApps intend to become technological
from various participants3 behemoths in order to improve their bottom-line
performance
SuperApps run the risk of being targeted by
governments using Data Protection Regulations SuperApps run the risk of being targeted under
if they use data beyond their defined purpose for anti-trust regulation if they use their dominant
collection market position in one sector to gain market share
in another through unsustainable competitive
The European Union courts have seen over behaviors
200,000 cases under data protection regulations
already and fined over USD 50m4 The roar of politicians towards using anti-trust
regulations against technology companies like
More than 120 countries have data protection Apple, Google, Facebook and etc implies risk for
regulations and at least 30 others have data SuperApps5
protection bills in their legislature along
international agreements for data protection6 Source: DBS BankDBS Asian Insights
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SuperApps: Implications on
Financial Services
Virtual Banks
Popular applications around the globe are now starting to explore the possibility of venturing
into financial services. Often starting off with digital wallets and payments, popular
applications first gain access to valuable customer data, which they later combine with their
digital expertise to offer more lucrative financial solutions to customers.
Some examples of virtual banking entrants in the region include KBank, WeBank and MyBank.
Interestingly, they have also became profitable within 2 years of their launch, which naturally
poses a question on the opportunities for SuperApps in ASEAN.
We see at least four different business models for new entrants depending upon the
regulations and market competition. Based on our findings, we believe the banking sector
in Indonesia, Vietnam and Philippines are big opportunities for SuperApps. This is largely due
to the respective countries’ large unbanked population, ease of regulatory compliance and
availability of data.
Indonesia
Indonesia is home to a large share of the world’s unbanked and underbanked population,
due to difficulties in catering to the services required in a commercially feasible manner.
However, with the advancements in technology and smartphone, new entrants are looking to
capture this market share as costs of servicing these customers have been reduced drastically.
The country also has fairly lax regulatory restrictions in terms of data protection and a
correspondingly relaxed compliance requirement in the banking sector. In our view, this only
translates to potentially milder regulatory restrictions on virtual banks. The country’s low credit
card penetration and high uptake of mobile payments platforms further translate to easy data
access for aspiring SuperApps, making Indonesia’s banking sector rife for disruption.
Vietnam, Philippines and Thailand
Philippines & Vietnam are in a similar league, with large unbanked populations and relative
ease of data collection for SuperApps. Thailand also presents a great opportunity for aspiring
SuperApps.DBS Asian Insights
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Singapore and Hong Kong
In contrast, the banking sectors in Singapore and Hong Kong present relatively small
opportunities for SuperApp disruption given tighter regulatory restrictions, smaller unbanked
populations and well developed payments ecosystems via formal banking channels.
That said, there are still opportunities for incumbents to capture market share from others if
they collaborate with SuperApps to target their customers. New entrants looking to penetrate
the Singapore and Hong Kong markets should look at utilizing a more integrated banking
model which ventures beyond the traditional deposit taking and credit model, to successfully
battle well-established incumbents.
Indonesia, Vietnam and Philippines present big opportunities for SuperApps in
ASEAN
Vietnam
Source: DBS Bank
In our assessment of opportunities for SuperApps in ASEAN, we factored in the percentage of
unbanked population in each country (represented by size of the bubble), ease of regulatory
compliance and availability of data to determine which markets in the region are most likely
to be disrupted.
To determine ease of regulatory compliance, we factored in the availability of data protection
regulations in the market, complexity of compliance with existing banking regulations, potential
regulatory complexity for virtual banks and the size of each country’s shadow economies.
To determine availability of data, we factored in current penetration rate of credit cards,
availability of a unified payments clearance platform that supports electronic fund transfers
on mobile platforms (eg. transfers to mobile numbers, email IDs, etc), penetration of mobile
payments platforms and the availability of SME data for aspiring SuperApps.
Low penetration of credit cards presents a great opportunity for mobile payments platforms
to flourish. On the other hand, the lack of a unified payment platform makes it difficult for
existing operators to effectively address customers’ need for mobile platforms.DBS Asian Insights
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Grab seeks to build, buy or partner to create its own SuperApp
Build
Buy
Partner
Source: DBS Bank
Business Models of Virtual Banks
We have identified four notable virtual banking business models in retail banking which are
functions of regulations and competition in their countries.
Business Overview Deposit taking Lending and Revenue Generation
Model Financing
Digital Functions like a traditional commercial Deposits are Data from the Net Interest income
Commercial bank, taking deposits from customers primarily acquired primary service through interest
Bank and providing financing solutions. from customers. of the entity (eg: rate spread on
Entity behind the bank is well-known, Customers at payment service financing products
paving way for easier attraction of Kakao Bank can provider, social and deposits,
deposits. open an account media platform) Limited focus on
in 7 minutes vs. is used to assess service fees and
Kakao Bank is owned by- Kakao Corp 20-30 at traditional credit worthiness commissions unlike
(10% stake) and Korea Investment banks. The bank and repayment traditional banks.
Holdings (58% stake). Korea had c. 17% of capability. Kakao Bank
Investment Holdings brings banking the country’s Kakao Bank managed to turn
expertise while Kakao Corp operates population as its uses data from profitable within
Kakao Talk and Kakao Pay, the most customers by 1Q19 Kakao pay and just 18-months of
popular messenger app and a digital (18 months since government record operation.
wallet in South Korea. launch). to provide loan
approvals within a
minute.DBS Asian Insights
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Business Overview Deposit taking Lending and Revenue Generation
Model Financing
Digital Functions primarily as an online Customer deposits Loans are Two sources - Net
Distributor distributor of finance products on are focused on to a underwritten by Interest income and
Bank behalf of traditional banks. Collection lesser degree either traditional banks commission fees
of deposits and on-balance sheet due to regulatory leveraging their from traditional
financing is focused on to a lesser restrictions or lack balance sheets. banks. WeBank
degree. WeBank in China, backed of public trust. On balance sheet became profitable
by Tencent, focuses on disbursing Retail deposits at financing is focused within two years
personal loans via WeChat with c. 80% WeBank accounted on to a much lesser of its launch.
of the loans underwritten by 50-60 for just 7% of its degree. WeBank Net income from
financial institutions in the locality liabilities in 2017 primarily works commissions was
of the borrower. WeBank had over due to regulatory as the platform c. 34% of the total
60m customers as of 2017 (~4% of restrictions on providing credit income.
China’s population) and managed to transaction volume assessment, loan
get well ahead of major Chinese city and deposit for disbursement and
commercial banks in terms of the retail virtual banks. collection on behalf
loan portfolio, within just two years of of the lender.
operations.
Digital Focuses primarily on the provision of Customer deposits Loans are financed Mainly net interest
Alternative financing solutions, with loan funding are focused on to a through alternative income. MyBank
financed largely derived through alternative lesser degree either financing channels, turned profitable
Bank financing means other than customer due to regulatory including interbank within 1.5 years of
deposits. MyBank in China, backed by restrictions or lack borrowings and launch. MyBank
Alibaba, funds c. 60% of loans through of public trust. securitization. generated a net
in the interbank market.MyBank Retail deposits at Interbank funding interest margin
already caters to over 6m SMEs in MyBank accounted sources accounted (on total assets) of
China, representing over half the 11m for just 34% of its for c. 60% of 4.7% vs. 5.4% for
SMEs in China. liabilities in 2017 MyBank’s total WeBank.
due to regulatory liabilities in 2017.
restrictions.
Digital bank Functions similar to the commercial Deposits are Uses technology Net Interest
plus software banking model. The bank further acquired from and data analytics income through
provider extends its offerings by running customers. Any to provide loans to interest rate spread
marketplace or by offering white- funding shortfall customers. between loans and
labeled banking products. Starling is financed deposits, Earns
Bank in the UK, functions as a mobile- through interbank commissions, service
only commercial bank and operates borrowings. fees or revenue
a marketplace offering a range of shares for product
products like accounting software and sales offered via the
Wealth management products. marketplace or on
the white-labeled
banking products.
Source: DBS BankDBS Asian Insights
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1. Digital Commercial Bank
Operating like any traditional commercial bank, a virtual bank rakes in customer deposits
and uses them to provide loans to customers, profiting from the net interest spread.
Kakao Bank in South Korea is an example of a virtual bank operating under this model.
The bank is backed by Korea Investment Holding, a leading financial services provider
and Kakao Corporation, a media and technology company in South Korea, famous
for its “Kakao Talk” messenger and social media app, used by c. 85% of the South
Korean population7.
Launched in 2017, Kakao Bank, the second virtual bank in South Korea, managed to
attract over 2mn customers in a fortnight, securing KRW1tn (US$930mn) in savings and
providing KRW770bn (US$701mn) in loans8. Kakao Bank caters to over 17% of the
South Korean population and presently has over KRW 14.9tn in deposits9 (US$12.6bn).
To put this into context, MyBank in China managed to accumulate only US$3.6bn in
deposits over a longer two-year time frame10. Kakao Bank managed to turn profitable
within just 18-months of operation, turning in a profit of KRW 6.6bn (US$5.6mn) in 1Q19.
A large part of the success of Kakao Bank can be attributed to two key reasons.
i. Kakao Bank was backed by well-known, established players in
the country
Korea Investment Holdings and Kakao Corporation was instrumental in
bringing public trust.
ii. Access to customer data and high-tech nature of the bank
Backing of Kakao Corporation provided the back with access to extensive
social media and payments data of customers, which Kakao Bank could
then use for credit assessments and the bank’s operations. The bank
reduced the time taken to on-board customers to just 7 minutes vs. 20-30
at traditional banks11.
2. Digital Distributor Bank
Under this model (made famous by WeBank in China), the virtual bank primarily
functions as a distributor of financial products on behalf of traditional financial
institutions. The bank is typically backed by a player with strong technological
capabilities and access to customer data. The virtual bank also operates as a
commercial bank but a substantial proportion of their lending is underwritten byDBS Asian Insights
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traditional financial institutions. On top of net interest margins, the virtual bank
earns commissions and servicing fees for the services it provides to traditional banks.
Regulatory restrictions in China impose restrictions on fund transfers to other banks
and daily transaction limits of deposit accounts that have not undergone on-site
verification at a physical bank branch. This makes it difficult for virtual banks in China
to rake in customer deposits to finance their loan portfolios.
WeBank, backed by Tencent in China, primarily focuses on the disposition of personal
financing solutions via its WeChat social media platform. c. 80% of the bank’s
loans are underwritten by c. 50-60 financial institutions12 that are in the locality
of the borrower, with WeBank primarily working as the platform providing credit
assessment, loan disbursement and collection on behalf of the lender.
WeBank managed to generate a profit within two years of its launch and registered
a net profit of US$209mn in 2017 (RMB 1.5bn). Net income from handling fees and
commissions for the facilitation of loans on behalf of other lenders accounted for c.
34% of the bank’s total revenue. This model works well in markets where securing
retail deposit is difficult due to the lack of trust or regulatory barriers. The model,
however, limits the upside potential of new entrants in the long run
3. Digital Alternative financed Bank
Similar to the distributor banking model, the alternative financing model is typically
practiced in regulatory environments where restrictions surrounding the collection
of deposits make it difficult for virtual banks to raise funding. Under the alternative
financing model, the bank may turn to sources of funding like interbank borrowings
or securitization of assets to finance its operations. Profitability of this model tends
to be lower comparative to other models, as the cost of funding is typically higher.
MyBank in China operates under this model, with c. 60% of its liabilities comprising of
inter-bank borrowings. The bank, with the backing of the e-commerce giant Alibaba,
concentrates on the provision of loans to SMEs, who are typically underserved in the
Chinese market. With limited access to retail deposits, the bank funds a large portion
of its loans through interbank borrowings and the issuance of asset backed securities.
Retail deposits accounted for just 34% of MyBank’s total liabilities13. Relatively higher
rates on SME borrowings may have prompted MyBank to opt for more expensive
interbank funding sources. MyBank generated a net interest margin (on total assets)
of 4.7% vs. 5.4% for WeBank.
4. Digital bank plus software provider
Further to operating like traditional commercial banks, these banks also offer theirDBS Asian Insights
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platforms to other service providers. Platform banks may operate marketplaces,
paving way for other service providers to leverage the bank’s customer base and offer
other integrated services or white-labeled banking products. It essentially allows non-
banking users to leverage on the bank’s banking expertise, license and technology.
Apart from generating net interest income, platform banks also enjoy commissions,
service fees or revenue shares for product sales offered via the marketplace or sale of
white-labeled banking products.
One such example is Starling bank in the UK. Starling bank, launched in 2014,
is a mobile-only virtual bank in the UK with over 460,000 retail and 30,000 SME
customer accounts. The bank offers a range of accounts including chequing and
savings accounts for retail customers and business accounts for partnerships and
sole-proprietorships. The bank also maintains the “Starling Marketplace”, providing
a range of solutions including wealth management products for retail customers
and accounting software and tax advisory solutions for SMEs. Starling bank plans
to further extend the marketplace with the inclusion of insurance and financing
solutions for customers.
Fidor Bank in Germany, a virtual bank launched in 2009, on top of operating a
marketplace, focuses on extending its services by offering a Banking-as-a-Service
product. The product allows non-banking players to roll-out banking products,
utilizing the banking platform of Fidor bank. Fidor bank provides its banking
expertise, banking license in the EU, technology and regulatory compliance allowing
non-banking players to launch banking products such as current accounts, bank
cards, payment platforms and credit products under the branding of the non-
banking player.
Lending Capabilities of Virtual Banks
In general, many SuperApps have easy-to-navigate user interface with positive reviews
for their user experience (UX). Putting credit underwriting capabilities aside, SuperApp
aspirants should seek to re-shape the lending scene in two key ways:
1. Expand target segment to underbanked SMEs and unbanked retail customers
2. Attract existing banked customers by offering higher speed and convenience, on top
of the SuperApp’s other lifestyle functionalities
We think an incumbent should be better off by leveraging on its existing database with
faster and more convenient loan processing to defend its existing customer base.DBS Asian Insights
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Expand target segment to underbanked SMEs and Attract banked customers with higher speed,
unbanked retail customers convenience and personalised services
Unbanked retail customers and underbanked SMEs New entrants would seek to re-shape current retail lending
would be the key focus of new entrants. through faster loan processing and fully-digitised applications
New entrants who possess transactional data on unbanked For these customers, banks are ahead as banks possess
customers and SMEs can better evaluate the credit worthiness more data of these customers. Licensed new entrants can
of these customers vs banks who typically possess no data of also access the risk data through credit bureaus but that may
these customers. not be as quick and comprehensive.
For unbanked and underbanked customers, tech players Offer an integrated personalised statement on banking and
have a clear competitive edge over the banks in assessing non-banking transactions
lending capability.
Disruption to the existing banks would be high as the
Disruption to the existing banks would be low as the new entrants would be targeting the same set of customers
new entrants would be targeting a new set of customers
Faster loan processing and user-friendly platforms help
MYBank leveraged transactional data from Alibaba HDFC win market share
platform to build a loan portfolio c. US$ 130bn in 3 years
HDFC bank in India digitized its credit approval process to
MYBank leverages data from Alibaba’s e-commerce platform minimise human interventions and reduce the time take to
to provide credit solutions to SMEs operating on Alibaba’s grant credit approvals and disbursement in 10 seconds in
e-commerce platform. MYBank caters to 6m SMEs, roughly from May 2015 onwards compared to the industry standard
half of all SMEs in China. MYBank offers competitive interest of several days. The bank digitized most of its documentation
rates ranging from 6-16% vs. 20-40% charged by traditional requirements and linked its systems with the Aadhaar
players. MYBank approves close to 60% of loan requests identification system. 10-second loans accounted for nearly
and boasts a default rate of c. 1% much lower than that one-third of the total loans by 2018 with delinquency rates
of traditional players. MyBank, for example, uses network on-par with loans disbursed physically.
analysis of transactions, through data gathered from the
AliPay and other sources, to evaluate if an entrepreneur HDFC has gained 3.1% market share of retail banking
separates personal funds from business funds, one of the key revenue over the past five years.
elements that drive credit worthiness of SMEs.
Convenience and personalised services
Grab has started sending out personalised monthly
transaction statements to users, which captures non-banking
transactions such as Grab rides, GrabFood orders and
Grabpay transactions. Virtual banking operator Monzo in the
UK categorises a user’s expenditure into segments such as
clothes, groceries, entertainment and transport and has most
recently partnered with fintech startup Flux to deliver digital
receipts into its banking app across various merchantsDBS Asian Insights
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Assessing Creditworthiness Using Transaction and Risk Data
An important component of the lending business is the individuals that these virtual banks are
lending to. The amount of loans that can be disbursed to a borrower is often determined by
the individual’s credit worthiness.
Traditional banks have been relying on inhouse historical data to assess borrowers’ credit risk.
For individuals, these data include salary, cash holdings, debt repayment history amongst
others. For corporates, financial profile, debt, valuation of collateral, industry outlook are also
taken in to consideration.
However, one might argue that risk data available accumulated are often retrospective – only
pointing towards existing and historical financial conditions of a borrower. Unfortunately,
these data points do not provide any useful insights towards the future financial standing of
individuals and corporates.
This is set to change with the proliferation of virtual banks due to the availability of transaction
data, which tend to be more forward looking. Technology giants typically have access to
transaction data derived through e-wallets, e-commerce operations, etc. In certain cases, non-
financial data on demographics, live locations and contacts details are also captured at the
point of loan disbursement.
For example, a borrower’s locations or “check-ins” are being monitored and can be used to
determine if an under banked worker has been reporting for work on time (and hence having
the financial means to repay the loan that he has taken up). Said borrower’s communication
and contact details can also be used to map credit risk – a borrower can be deemed to be
more credit unworthy or bears higher default risk if the individual has been communicating
frequently with other credit facilities.
Balancing forward looking transactional data with historical risk data
Transaction Data, coupled Collected only
with advanced analytics allows over the last few
tech giants to better assess years and does not
the repayment ability of their cover the change in
customer base behavior during
an economic
downturn
Points only towards Risk Data, points towards the
the existing financial existing financial conditions of
conditions of the the borrower
borrower
Source: DBS BankDBS Asian Insights
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That said, the volume of transaction data available is relatively sparse due to the relative
“newness” of virtual banks. Furthermore, transaction data alone is not sufficient for credit
assessment – the absence of financial data disallows technology giants to model the repayment
ability of the borrowers. Coupled with the fact that transaction data has only been collected
over the last five to six years, where the world was experiencing healthy economic growth, it
is hard to ascertain borrower behaviour during an economic downturn.
An example of a technology giant that successfully harnessed the power of transaction and
risk data is Tencent’s WeBank. Beyond transaction data, WeBank’s distributor banking model
allows it to access risk data of borrowers, enabling it to make sound and holistic decisions
for disbursing loans to its customers. Beyond risk analytics, data collected can also be used in
credit pricing decisions, effectively shortening the lending process significantly.
The distributor banking model
allows WeBank to access risk
data of customers that were
previously not covered by banks
or credit bureaus
WITHOUT
taking on the risk of default on
those customers, as loans are
usually disbursed by traditional
financial institutions.
Source: DBS Bank
Regulatory considerations in Hong Kong and Singapore
The emergence of various fintech companies around the world has redefined what it means
to be a bank. In the past, traditional banks associated themselves as the intermediary to
payments systems, deposits and lending, all while offering credit cards and other banking
and capital markets solutions. With the proliferation of the internet, banking transactions
are moving online. This inevitably puts into question the need for a physical branch network.
China has been a forerunner in the virtual banking space, having issued five licenses since
2014. This allowed digital banks to provide loans to small businesses and consumers, but with
strict limitations on accepting deposits.
In 2014, Korea gave an initial approval for its first two virtual banks. More recently, the Hong
Kong Monetary Authority (HKMA) and Monetary Authority of Singapore (MAS) both set up
various guidelines and frameworks for virtual banks in 2018 and 2019 respectively.DBS Asian Insights
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While critics are of the view that Hong Kong’s licensing criteria is somewhat restrictive, we
believe there are some common considerations for Hong Kong and Singapore regulators.
Foremost, both regulators are keen on financial inclusion, and a potential benefit for virtual
banks would be its ability to help promote the cause. This is so as virtual banks generally target
the unmet or undeserved needs of retail and SMEs segment.
Secondly, virtual banks would need to strike a balance between building market share and
delivering a reasonable return on assets and equity. This stems from concerns on predatory
tactics which may affect the stability of the banking sector. In Singapore’s case, MAS has
stated explicitly that it will not allow any bank, digital or not, to engage in value-destructive
competition to gain market share.
Based on the above, it may be an appropriate conclusion to draw that regulators in Asia
are primarily focused on the financial stability of the systems, and hence systematic risk and
impact on incumbents caused by new players.
Considerations Hong Kong Singapore
Definition A virtual bank is defined as a bank which N/A
primarily delivers retail banking services
through the internet or other forms of
electronic channels instead of physical
branches.
Scope Both financial firms (including existing In addition to any digital banks that the Singapore banking
banks in Hong Kong) and non-financial groups may establish under the existing internet banking
firms (including technology companies) framework introduced in 2000, new digital banking licences
may apply to own and operate a virtual are extended to non-bank players.
bank in Hong Kong.
No. of licenses 8 licenses have already been issued. A maximum of 5 licenses with two full-service commercial
More applications for licenses are under banking licenses and three wholesale banking licenses.
consideration.
Ownership Should be locally incorporated. Digital full bank licenses are available only to companies
headquartered in Singapore and controlled by
An entity with >50% ownership should Singaporeans.
be a bank or a financial institution
(if not, the bank should be held by Wholesale banking licenses are open to both local and
an intermediate holding company foreign companies.
incorporated in Hong Kong).
Operational None. Not expected to maintain physical Digital banks will commence as restricted digital full banks
restrictions branches and should not impose any and be subject to various deposit caps, business restrictions
minimum account balance requirement and a lower minimum paid-up capital in its initial one to
or low-balance fees on customers. two years; no prescribed time period in which restricted
digital full bank must graduate to digital full bank.
No access to automated teller machines or cash deposit
machines network though allowed to offer cashback services
through electronic funds transfer at point of sale (EFTPOS)
terminals at retail merchants.DBS Asian Insights
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Considerations Hong Kong Singapore
Deposit taking None Restricted stage for digital full banks: Aggregate deposit
restrictions cap of S$50m with an individual deposit cap of S$75,000.
Deposits can only be secured from business partners, staff
and related parties.
Wholesale banks: Can accept fixed deposits upwards of
S$250,000 from individuals. Free to open and maintain
business deposit accounts for SMEs and corporates.
Product None Restricted digital full bank: At entry point, can offer only
restrictions simple, banking operations in not more than 2 overseas
market. Upon progression, no business restrictions after
meeting MAS’ criteria.
Wholesale banks: Can only serve SMEs and other non-retail
segments.
Capital and Minimum capital requirement for Initial paid-up capital for restricted digital full bank: S$15m
liquidity licensed banks: HK$300m.
requirements Paid-up capital for digital full bank: S$1.5bn.
Virtual banks must maintain adequate
capital commensurate with the nature Both restricted and digital full bank are subject to similar
of their operations and the banking risks capital requirements as local banks. Restricted full bank
they are undertaking. needs to maintain liquidity of 16% of minimum liquid
assets, thereafter, subject to similar liquidity requirements as
local bank.
Source: DBS Bank
Robo-advisors
Historically, new entrants draw liquid investments away from banks due to temporary
loopholes or lack of regulations. In 1980s and 1990s, US and UK brokers took advantage of
liberalisation of financial regulations by sweeping client money into funds.
Fast forward to today, SuperApp aspirants have several options when looking into launching
investment products. This range from offering money market products that resemble
traditional retail deposit accounts (Eg. Yue Bao) or Robo-advisory services.
Robo-advisory services is a great fit for many customers with simple investment needs, especially
so for the underbanked and unbanked population of ASEAN. However, its value proposition,
which is based on low-cost and transparency, limits the providers’ ability to generate fees.
Furthermore, low entry barriers have resulted in many start-ups entering the space, driving up
the acquisition cost per client. These challenges are particularly pronounced in ASEAN, each
with its own set of regulations while being a fraction of the size of the European or US market.DBS Asian Insights
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Examples of Robo-advisors in Singapore
Robo advisor Assets Min. balance Fees
StashAway 19+ ETFs including government, None 0.2 to 0.8%
corporate bonds, US Equities, Small- depending
cap Growth index funds, Consumer on amount
Staple Equities, Asia ex-Japan
Equities, gold, etc.
Smartly 20+ ETFs in equities, government S$50 0.5 to 1%
and corporate bonds, commodities, depending
real estate and cash on amount
AutoWealth More than 8,000 stocks and 600 S$3,000 0.5% per
government bonds from US, Europe, year + US$18
APAC and Emerging Markets. per year
Source: Moneysmart.sg
Profitability of Robo-advisors
According to Morningstar14, Robo-advisors spend c. US$300 on a gross basis acquiring each
client account. It can take as long as a decade in some instances for Robo-advisors to recover
the cost through fees, considering the 0.2% to 0.5% fees charged.
Three things significantly weigh on the profitability of robo-advisors:
1. High client acquisition costs
2. Ongoing costs of servicing clients
3. Low revenue yield on client assets
Gaining visibility among customers and converting potential leads to customer accounts
remains one of the hardest and most expensive tasks for emerging Robo-advisors.
Bulk of the seed funding raised in the initial stages of operations is invested in customer
acquisitions. Costs dedicated to customer acquisitions account for a large proportion of
the operating expenses Robo-advisory firms. This large capital outlay delays the path to
profitability. WealthFront is one an example of an established Robo-advisor which has yet to
record profits since its inception in 2008.
Size of client accounts are likely smaller in Singapore than in the US, where two of the largest
Robo-adivsors, Betterment and WealthFront, claimed average account sizes of between
US$20,000 to US$40,000. However, client acquisition expenses are should technically be
lower in Singapore as well given the smaller market size.
Based on a hypothetical assumption below, a Robo-advisor could take at least 3 years toDBS Asian Insights
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recover its average client acquisition cost (CAC). This is three time the ideal time of a year. In
order to be profitable within a year, it is imperative that either the fees charged be at least 1%
of the investment or CAC be significantly lower for each customer.
• Average client account size: S$10,000
• Average lifetime value (LTV) of customer: S$150
(assuming 0.5% of the investment amount over 3-years)
• Average client acquisition cost (CAC): S$150
(at a c. 50% discount to CAC in the US)
Case Study: Yu’e Bao
Yu’e Bao was first set up as a repository for leftover cash that was temporarily stored in Alipay
wallets, and has since surpassed JPMorgan’s US government money market fund in 2Q17 to
become the world’s largest money market fund with $166bn under management. Since then,
Yu’e Bao’s assets under management rose to $240bn in 4Q17.
The success of Yu’e Bao hinged on two factors. By sweeping the money into a fund, Ant
Financial offered returns of up to 6.8% in 2014, higher than the prevailing savings interest
rate (0.35%). Another factor was the ambiguity in regulations which allowed Ant Financial to
avoid the requirement of parking 20% of funds as reserves with the central bank.
After realising Yu’e Bao’s disruptive power, regulator imposed
20% reserve requirement in 2017, subsequently raised to
50% in 2018. Also, there are individual quota requirements
and daily caps in place for Yue’Bao investments crackdowns
Yu’e bao currently offers a return of c. 2.3% by investing in
money-market funds versus 0.35% savings rate
The negative impact on the banking industry is insignificant.
Fund size shrank to 0.5% of total banking deposits in March
2019
Source: DBS BankDBS Asian Insights
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Insurance
Digitalisation of Insurance
Backed by SoftBank’s ambitions, ride-sharers around the world are exploring opportunities in
the traditional insurance services industry. While Softbank itself is not a technology firm, it is
a major investor in technology-based insurance disruptors. Between 2017 and 2018 alone,
SoftBank backed China’s largest online insurer ZhongAn, India’s biggest online insurance seller
Policybazaar, as well as US home insurer Lemonade.
Softbank sees the insurance sector as ripe for disruption and believes in the immense potential
of cross selling between these “insurtechs” and other firms within its portfolio such as Grab,
Didi and Uber. While Softbank and its portfolio of ride-sharers may be the first to venture into
the insurance industry, it is definitely not the last. Other non-SoftBank backed ride-sharers such
as Go-Jek are also making in-roads into insurance through equity investments in “insurtechs”.
Mainstream Adoption
Looming end-to-end digitisation for insurance companies
15% adoption rate -
tipping point of
mainstream adoption
Digital distribution to become
a common functionality among
insurance players by 2020
(adoption in 2016 – 17%)
Mainstream adoption fully-
digital claims processing
likely by 2020 with growing
cross-sector partnerships Automated usage based
(adoption in 2016 – 7%) pricing to reach the tipping
point by late-2019, with
improvements in real-time data
collection and analytics
(adoption in 2016 – 10%)
Adoption rates are based on the % of innovations in the insurtech space. All data is for the Property and casualty segment.
Sources: McKinsey, DBS Bank
To determine which markets in the region are most likely to be disrupted via SuperApps, we
have factored in the percentage of uninsured population in each country (represented by size
of the bubble), concentration of the insurance industry in each country and the availability of
data for SuperApps.DBS Asian Insights
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Indonesia, Thailand and Philippines Insurance Industry rife for disruption by
SuperApps
Source: DBS Bank
In our X-Axis we try to rank the countries based on the concentration of the insurance market
based on the number of firms and their share of the total insurance market (life and general
separately). In Malaysia, life insurance market is highly concentrated with the top 5 insurers,
accounting for c. 80% of Gross Written Premium (GWP). On the other hand, the Indonesian
general insurance market is highly fragmented, with the top 5 insurers only accounting for c.
35% of GWP.
In our opinion, concentrated markets in general are better suited for disruption since they
offer higher profit opportunities allowing exploitation of pricing inefficiencies by new
entrants. Concentrated markets generally offer higher profit making opportunities with listed
incumbents recording higher margins. Although there is a notable exception in Singapore,
where United Overseas Insurance Ltd had a bumper year in 2018.
Concentrated markets typically post better profitability
Country FY18 Average Pre-tax Profit Margin
Indonesia 12%
Singapore 27%
Malaysia 9%
Thailand 7%
Philippines 7%
China 4%
Hong Kong 1%
Source: Reuters, DBS BankDBS Asian Insights
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That said, it should also be noted that market concentration in isolation may not be a good
indication of profit making potential for new entrants. Indonesia is a prime example of the
opposite; where market fragmentation enables future disruption with a largely uninsured
population and the archipelago nature of the country, which prevents incumbents from
establishing strong agent networks.
Similar to our previous analysis on availability of data for the banking sector, we use credit
card penetration and pervasiveness of mobile payments platforms as metrics in our Y-Axis.
Our analysis suggests that the insurance industry in Indonesia, Thailand and the Philippines
are ripe for disruption by SuperApps. They provide better opportunities than developed
economies such as Singapore and Hong Kong due to their respective low barriers to
entry. In addition, ASEAN countries like Indonesia and Philippines are highly prone to
natural disasters, political and economic instability and a high level of sectarian violence.
Coverage for the above are presently not met by the incumbent insurers which could
also provide a niche for SuperApps. Unlike banking, Government-funded social insurance
leaves relatively smaller opportunities in Vietnam.
Potential entry points to insurance industry
Insurance Services
Product design/ Product pricing Underwriting/ Distribution Policy claims
Development risk management management
Automotive
Potential for
entry Travel
High
Moderate Home
Low
Health
SME
Source: DBS BankDBS Asian Insights
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Insurance Distribution Models
Business Overview Distribution of insurance Underwriting and Claims Profitability and Revenue
Model products processing generation
Digital Functions like a Nature of insurance Risk assessment takes A significant portion of
Insurer traditional insurer products vary with the place via digital means the premium income
in a selected sector insurer’s backers and and leverages partner’s however, has to be
(more common in P&C focus of the insurer. data. Handling of claims shared with ecosystem
and Health). Insurer’s Policies are largely happens online to a partners. For example,
products are usually distributed via digital great degree albeit ZhongAn is yet to
distributed through channels. For example, offline channels are generate profit since its
its ecosystem partners. shipping return also used. For example, launch in 2014. c. 30% of
For example, ZhongAn policies on e-commerce ZhongAn’s policies on ZhongAn’s net premiums
operates with the platforms, flight delays flight cancellations take are shared with its
backing of Alibaba, and event cancellations into account weather ecosystems partners.
Tencent and Ping An on travel platforms data, airline history,
(c. 33% combined are popular policies by airport history etc.
ownership). ZhongAn ZhongAn. Shipping returns policy
caters to six consumer is offered on partner
centric ecosystems with channels.
five major ecosystem
partners.
Insurance These are aggregators They are purely Does not get involved in Revenue from lead
Aggregator of insurance plans and distributors of insurance insurance underwriting generation for the
serves as a marketplace products. Policybazaar and claims processing insurers, advertising
for policies. For example, portal is an exclusive but facilitates the and policy sales. In the
Policybazaar is an online insurance focused registration of claims on case of Policybazaar, c.
platform that aggregates e-commerce website behalf of its clients. 85% of FY18 revenues
insurance plans and with c. 50% market came from policy sales.
serves as a marketplace share in online insurance Policybazaar’s FY18
for policies, offering distribution space In revenue was US$22m
more than 250 insurance India. with US$1.3m loss.
plans from over 50
insurance brands on its
platform.
Orchestrator Generally, these are The orchestrator Insurance policies are Direct revenues from
led Insurance large orchestrators distributes the insurance underwritten and commissions and service
with a loyal customer products on behalf of managed by the insurer’s fees on premiums.
base, who select the insurer and provides partners while the Orchestrators also enjoy
exclusive partners to targeted marketing distributor manages indirect benefits such
join their ecosystems. for insurance policies. the client relationship as improved customer
The orchestrator Insurers benefit from for enquiries and claims stickiness, opportunities
helps in the insurance access to a wider processing. to cross-sell and up-
discovery, while customer base. WeSure sell core products
insurance providers for example, takes etc. WeSure primarily
underwrite and manage 1.5-2 months and 7-8 generates income
the insurance product. iterations to develop a through commission fees.
WeSure by Tencent, has product with partners.
partnered with over 20 c. 50% of customers on
insurance providers to WeSure are likely to
offer insurance policies recommend insurance
covering health, auto, policies to friends who
life, and travel and caters are 2-3x more likely to
to over 20mn customers. purchase the policies
recommended.
Source: DBS BankDBS Asian Insights
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Digital Insurer
Digital insurers function like any typical traditional insurance provider, except its emphasis
on digitalizing its operations. In the current landscape, digital insurers are typically either a
subsidiary of a pre-existing insurance provider or are backed by a strong set of industry partners
with good technical backgrounds, customer data access and expertise in insurance.
Digital insurers maintain an end-to-end digital platform, handling the process from lead
generation and underwriting to claims processing digitally. Risk assessment takes place via
digital means and leverages data shared by the customer with the insurer and any data
gathered from agreements with ecosystem partners.
Like traditional insurers, digital insurers generate revenue through premium and investment
income. However, operational expenses are not necessarily lower in this model as a significant
portion of the insurer’s revenue is shared with its partners facilitating the insurance process.
An example of a Digital Insurer is ZhongAn, the first online-only insurer specializing in Property
and Casualty insurance policies. ZhongAn is also backed by two technology giants and a leading
insurer in China – Alibaba, Tencent and Ping An. The three entities hold c. 33% ownership
stake and assists the company through the provision of technical support, access to customers,
insurance expertise and assistance in co-creating new insurance policies.
In terms of business strategy, ZhongAn mainly focuses on micro-premium and repetitive
insurance policies around six consumer-focused ecosystems (Health, Auto, Travel, Consumer
finance, Lifestyle consumption). ZhongAn’s insurance policies are also well integrated with its
partner ecosystems, which allows for easier distribution. For example, one of ZhongAn’s best-
selling shipping return policies is made available on e-commerce platforms such as Alibaba’s.
Another example of its integration with its partner ecosystems is ZhongAn’s insurance policy for
buyer and sellers to cover return shipping costs. This greatly alleviates Chinese buyers’ concerns
about product quality when they make purchases online.
As a Digital Insurer, ZhongAn has largely digitised its underwriting and claims management
process. Data analytics are used to personalise insurance policies and pricing to customers.
Claims are also largely digitised with certain policies carrying fully-automated claims processing.
For example, customers who purchase ZhongAn’s Flight Delay Policy are reimbursed
automatically into their WeChat Pay accounts if flights are delayed beyond certain amount of
time as specified in the policy.
Despite rapid growth in premiums it has underwritten, ZhongAn still remains unprofitable
as the insurer is still scaling up its platform in a bid to add new ecosystem partners to its
network. Despite acting purely as a digital insurer, ZhongAn shares c. 30% of its net premiums
underwritten with its ecosystem partners for distribution and customer access. This is largely
in-line with c. 40% channel fees paid by Brick and Motor insurance players in China.You can also read
