1. finance
2. bank

2014 年 11 月 14 日
中国：金融服务
证券研究报告
互联网金融 1：巨头之争硝烟起；中型银行面临边缘化风险（摘要）
中国互联网巨头挺进金融领域
在互联网巨头中阿里巴巴拥有最大潜力
中国互联网三巨头：阿里巴巴集团、百度和腾讯已经
利用它们庞大的客户基础和市场主导地位进入了线上
金融服务领域。由于它们的线上支付工具在获得零售
和中小企业客户及数据采集方面发挥了关键作用，我
们预计它们会瞄准线下金融业务，服务于消费者和中
国的中小企业，后者从中国传统金融企业获得资金的
成本往往很高。事实上，阿里巴巴集团和腾讯已经获
得了银行执照：它们与中国现有金融企业之间的竞技
场已经铺就。
在中国的互联网三巨头中，我们认为阿里巴巴在发展
金融业务方面比百度和腾讯更具优势，因为支付宝是
阿里巴巴获得客户和采取数据的工具、公司拥有强大
的电子商务生态系统、有能力处理大数据和进行风险
管理，同时还拥有广阔的金融平台。
互联网金融规模虽小但增长迅速
我们认同目前尚属互联网金融发展的早期阶段，而且
其规模置于中国银行系统背景之下显得较为有限。此
外，这些新晋竞争者在资本金、资金以及尽职调查等
问题上面临挑战。但是我们预计以下四大推动因素将
帮助互联网金融从低基数水平快速增长：电子/移动商
务、支付、客户和数据以及金融市场化。我们预计
2024 年互联网金融企业所发放的信贷规模为人民币
6.8 万亿元，在剔除债券/股票之后的总社会融资存量
中仍仅占 2%；但是互联网金融企业利润将增至 400 亿
美元（年均复合增长率为 41%），相当于我们估算
2024 年银行整体盈利的 8%。
互联网对于中国金融企业的威胁
在银行服务的七大元素中，中国互联网三巨头在其中四
个：即交易、支付、数据采集和监管方面较银行拥有越
发明显的优势。
银行仍在存款资金/资本金基础以及尽职调查和不良贷款
解决方案上拥有相对优势。
7 key elements for financial services
对于中国金融企业的影响
我们评估了中国现有金融企业将如何应对这一新兴威
胁，并将通过系列报告探讨这一现象，本文即是开篇
之作。我们的初步分析显示，平安集团、招商银行和
工商银行这三家大型金融企业将在这场保卫战中处于
最有利的地位，因为它们拥有强劲的 IT 能力而且注重
互联网金融发展战略。
而面临着最严峻边缘化风险的（尽管是就中长期而
言）是那些中型银行，比如交通银行、中信银行、浦
发银行、华夏银行和光大银行，因为它们的零售业务
实力相对薄弱，而且侧重于发展中小企业业务，我们
认为后者将是互联网巨头与金融巨头相争的下一主战
场。
Consumers
1
Online/offline
transactions
2
Online/offline
payment
3
Data
SMEs
Corporate
Retailers
4 On-site DD
check
5 Deposit
funding
6
Capital
7
Regulation
资料来源：高华证券研究
*全文翻译随后提供
马宁 执业证书编号: S1420510120014
+86(10)6627-3063 ning.ma@ghsl.cn 北京高华证券有限责任公司
吴双 执业证书编号: S1420514080001
+86(10)6627-3487 jessica.wu@ghsl.cn 北京高华证券有限责任公司
李南, CFA 执业证书编号: S1420513110001
+86(10)6627-3021 nan.li@ghsl.cn 北京高华证券有限责任公司
北京高华证券有限责任公司
北京高华证券有限责任公司及其关联机构与其研究报告所分析的企业存在业
务关系，并且继续寻求发展这些关系。因此，投资者应当考虑到本公司可能
存在可能影响本报告客观性的利益冲突，不应视本报告为作出投资决策的唯
一因素。 有关分析师的申明和其他重要信息，见信息披露附录，或请与您的
投资代表联系。
投资研究
2014 年 11 月 14 日
中国：金融服务
Contents
Overview: Emergence of internet finance to reshape China’s lending markets
3
The stage is set for Titans to clash: Internet finance to come of age in the next decade
8
We see four key drivers of internet finance in China
8
Internet finance giants’ profit: US$40bn by 2024, equal to around 8% of banks’ profits
12
The first battleground: payment as client/data acquisition tool; now moving to offline
15
Online payment develops rapidly – large by transaction number, but small by value
15
The move to offline
15
NFC payment function could provide banks a way to repel BAT, if well executed
18
The second battleground: consumer and SME banking — huge but still untested for BAT
20
Mining their advantages could allow BAT to threaten banks in consumer/SME banking products
20
BAT’s internet finance strategy: Alibaba leads in internet finance
24
Alibaba leads in internet finance
24
Tencent still to monetize its retail customers
30
Baidu: potential in financial searches and WMP distribution; O2O worth watching
33
Impact on financials: Marginalization a risk for midcap banks; Ping An, CMB, ICBC best placed
37
Assessing internet finance strategies of key financial institutions
39
Ping An Group: comprehensive internet finance strategy, top rank IT and integrated platforms
39
CMB: strong in IT service for SMEs, NFC trial, consumer/credit card brand and IT capability
43
ICBC: strong retail/SME franchise and IT capability; data mining and marketing needs to improve
44
Minsheng Bank: reasonably strong SME/IT capability; trial in direct banking and O2O services
44
Industrial Bank: potential in developing internet WMP platform, retail/SME franchise weak
45
Bank of Beijing: cooperation with Xiaomi in NFC; value-added marketing services at an early stage
45
CNCB: actively developing mobile code payment and POS loan; strategy unproven
45
SPDB: early mover in NFC with China Mobile but user experience remains a key issue
46
Disclosure Appendix
48
Prices in this report are based on the market close of November 12, 2014
Gao Hua Securities acknowledges the role of Piyush Mubayi of Goldman Sachs in the preparation of this product.
_____________________________________________________________________________________________________________
Related reports
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Tighter payment rules gives banks time to develop own capability, March 17, 2014
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全球投资研究
2
2014 年 11 月 14 日
中国：金融服务
Overview: Emergence of internet finance to reshape China’s lending markets
Internet finance in China has been developing rapidly over the past three years:
China’s three internet giants — Alibaba Group, Baidu, Tencent (which we dub “BAT”) — as well as JD.com have all been using their
success in e-commerce to build their online payment capabilities. They have all now begun to offer a wide range of financing capabilities:
consumer credit, SME loans, and small-scale wealth management tools such as Alibaba’s T+0 money market funds (MMFs) that links to
Alipay. (Note: Alibaba in this report refers to Alibaba Group and its affiliate Ant Financial Services Group.)
There are many new forms of internet finance emerging in China, such as:

Over 1,400 new peer to peer (P2P) lending firms that have been set up over the past three years to link directly between borrowers
and personal lenders for small ticket loans. P2P providers are typically internet service platforms to allow personal lenders to search
for borrowers on-line.

Crowd funding — that is, entrepreneurs post their projects or company descriptions to crowd funding websites in order to attract
broad investors;

Other kinds of internet finance business models such as third party payment for e-commerce/m-commerce, bank/financial products
search and price comparison websites, and web-based wealth management platforms, etc.
The move into financing by these internet players raises three key questions:

What is the growth potential of internet finance in China?

What are the potential threats to the traditional bricks and mortar banks, insurers, and brokers?

What might the impact be on China’s macro economy?
Germinating from our GS China Internet Finance Seminar, held in in Shenzhen in April, and developed in close collaboration with our internet
and macro teams, this report marks the first in a series we plan to publish on this new platform.
We believe internet financing has the potential to reshape the dynamics of China’s lending markets over time. We expect internet financing
business to grow rapidly in China off a low base and drive greater competition with banks in payments, and in consumer, and SME banking
areas. We expect internet finance players gradually to take some market share and wrestle some profitable consumer and SME banking
segments from banks.
We believe that, at least for the moment, they lack the funding, the capital and the requisite interpersonal relationships with customers (to
conduct due diligence) to take market share quickly. Over the longer-term, we think they may pose increasing long-term marginalization risk
for mid-cap banks that do not have strong franchises and IT/internet banking strategies.
全球投资研究
3
2014 年 11 月 14 日
中国：金融服务
Internet finance set to boom on four key drivers
We expect internet players will accelerate their development of payment, consumer credit and SME banking products. We forecast consumer
and SME loans/payment-related business of internet giants (essentially BAT and JD.com) could generate US$29bn/US$11bn net profits by
2024, or up to c. 6% /2% of total bank profits then, driven by four factors:
•
The rapid growth of e-commerce and mobile commerce activities in China, thanks to increasing penetration of mobile/internet
use, improving logistics for online shopping, and expansion by e-commerce giants and emerging new e-commerce providers in new
areas such as autos, health care, etc.
•
Internet companies’ financial innovation as a catalyst for financial service “deregulation”. The current tight regulation
around banks and insurers provides many growth opportunities for internet finance players to serve un-satisfied demand. For
instance, we think consumer banking (i.e. credit cards, high yield subprime consumer loans) and SME banking are under penetrated
in China, offering segments that internet finance players can serve.
The government is generally supportive of financial innovation, and has imposed few regulatory constraints on internet
finance providers so far. China’s government encourages financial innovation to serve SMEs and consumer banking, offering a
favorable regulatory environment. For instance, the banking regulators recently approved for Tencent and Alibaba Group to be the
major shareholders and sponsors of two new private banks. On the other hand traditional banks and insurers still face strict
regulations such as credit quota, the 75% loan/deposit ratio cap for housing loans and capital requirement that could hinder their
competitiveness and curtail their willingness to serve the consumer and SME segments.
•
Internet players have great incentive and capability to collect and analyze data related to transactions, behavior and payments to
enable them to improve risk management and promote targeted markets to potential users. In contrast, although banks have lots of
transaction data in credit and banking cards, we think they have not analyzed or utilized this data effectively to conduct targeted
marketing or detailed credit analysis.
•
Internet players’ relatively closed ecosystem allows them to include their own online payment business such as Alipay, Tenpay to
close the transaction loop to lock in customers and transaction data. In 2013, third party payment functions accounted for 76%
internet shopping transactions (with the remainder conducted via bank cards), vs. 15% in the US.
Online payment allow internet players to gather clients and data; moving offline
In the absence of Chinese banks’ ability to provide suitable solutions to satisfy online shoppers’ requirements for security, convenience and
trust, online payment tools, such as Alipay and Tenpay, were first developed to facilitate e-commerce transactions in 2004. Now, ten years
later, internet players’ payment services have come to dominate e-commerce and mobile-commerce transactions — with users numbering
over 900mn and 300mn, respectively, by early 2014.
With critical mass, Alipay and Tenpay are now developing off-line payment solutions. For example, Alipay has recently moved to enable
payment for restaurants, taxis, etc. We believe these off-line payment scenarios will be critical for BAT to further develop online-to-off-line
(O2O) business — allowing them to acquire off-line clients (including SMEs), compile transaction data, and create off-line relatively closed
ecosystem business models. This in turn should enable them to build a foundation to expand their consumer and SME banking.
In contrast, banks and China Unionpay (the banking card association) have traditionally been strong in off-line payment scenarios, and have
enjoyed high growth in these channels over the past decade (bankcard usage as a percentage of retail sales rose to 47% in 2013 from 5% in
全球投资研究
4
2014 年 11 月 14 日
中国：金融服务
2002). However, they have not developed comparative datamining capabilities to position them to effectively target new products at the right
customers.
We believe banks will need to increase investment and more focus their efforts to develop their banking card and new payment technologies.
Moves are underway, however. For example, Unionpay and many banks are pushing NFC mobile payment, likely using the iPhone 6 (as in
the US), and currently in conjunction with Xiaomi, Huawei and others. If executed well, this could provide a way for banks to defend their
traditional dominance of off-line payments. However, we believe NFC’s effectiveness remains to be established in China, as there is little
incentive for offline merchants to use NFC and it has not deeply penetrated consumers consciousness, even though NFC has many
advantages over the bar-code payment system employed by the internet giants. NFC as a system has greater speed and safety, as well as
offline merchant payment scenarios and regulatory support.
Consumer and SME banking the next battleground; huge but untested for internet players
Alibaba Group and JD.com already offer SME loans to their merchants and/or suppliers, as well as consumer loans to their clients for online
purchases. We expect BAT and JD will accelerate their efforts in offering consumer banking, credit cards and SME banking online, to
leverage their enormous retail and SME client base, their strong datamining capability (especially online transactions), and their established
e-commerce/m-commerce ecosystems.
We believe that compared with banks, BAT have increasing advantages in four of seven key banking services:

Transactions —capturing online economic transactions, and increasingly pushing into off-line transactions;

Payment — using online and off-line payment services to capture payment data

Data — using their ecosystem and big data technics to gather and analyze clients’ entity and identity data including locations, age,
family size, etc, as well as consumers’ multi-dimensional behavior data such as purchase behaviors, and transaction data.
Essentially they have the ability to analyze who their clients are, their online and off-line behavior, and what they shop for, and
whether they have ability and willingness to repay loans.

Regulatory advantages — so far internet players are subject to limited regulation regarding their financial innovations, whereas
banks face still strict regulations for loan quotas, L/D ratios, and capital and anti-money laundering requirements.
However, banks retain their traditional strengths: cheap deposit funding, on-site due diligence based on personal contacts, their broad
physical network which is critical for risk assessment of more complicated and larger transactions such as mortgage and SME loans, and
enormous capital positions to support the business.
In light of these fundamentals, we believe internet players’ consumer and SME banking will grow very rapidly off a low base, but it will take
many years for internet players to wrangle significant market shares from traditional financial service players — predominantly due to their
comparatively limited capital and funding. We forecast internet finance total credit growth (incl. P2P) to reach Rmb8.8tn annually in
2024E, equivalent to 2.8% of TSF (total social financing; excl. bonds and equities), as banks also grow their loan balances.
全球投资研究
5
2014 年 11 月 14 日
中国：金融服务
Alibaba leads in internet finance among peers
We have analyzed the key strengths, weakness and strategies of the three internet giants’ internet finance business, and believe:

Alibaba is the leading player, given its strong e-commerce franchise and closed ecosystem, Alipay’s pre-eminent position in online
payment, strong data mining and risk management capability, strong product development capabilities, and a comprehensive
repertoire of internet finance platforms such as Alipay, Yu’e’bao, Zhaocaibao, etc.
•
Tencent has advantages in gathering retail customers through WeChat, as well as the potential to develop O2O payments and
financial service for consumers and SMEs in the longer run. Tencent is able to collect a variety of consumer behavior data, but it will
take time to build up a platform to capture e-commerce transactions and a wide range of payment scenarios. In terms of its further
consumer/SME banking potential, we believe Tencent’s O2O initiatives, cooperation with JD.com, and its new banking subsidiary’s
strategy are the three areas to watch for.
•
Baidu is relatively weak in e-commerce transaction/payment functions, but its strong data mining capability and searching traffic
could help it build wealth management platforms and/or generate revenue from financial-service related searches.
That said, we believe BAT are likely to face challenges if and when they expand into finance services — notably complying with
complicated financial regulations in payment, anti-money laundering, customer education, and face-to-face interviews. These may
become more challenging if regulators impose tighter compliance standards (for example, third-party payment volume caps, face-to-face
interview in physical places).
Impact on financials: Risk of marginalizing mid-cap banks; Ping An, CMB, ICBC best placed
Although still very early days in the ascent of internet finance and therefore difficult to predict how the challenge from BAT can be met, we
believe three large-cap financials are best placed to defend their positions due to their strong IT capability and internet finance strategic
focus: Ping An Group, China Merchants Bank and ICBC.
Those most at risk of marginalization, albeit in the longer-term, are mid-cap banks — specifically BoCom, Citic Bank, Shanghai Pudong
Development Bank, Huaxia and China Everbright Bank — on relative weakness in their current retail banking franchise and their focus on
SME business, which we see as the next big battleground for internet finance initiatives.
全球投资研究
6
2014 年 11 月 14 日
中国：金融服务
Exhibit 1: H-/A-share listed China banks valuation comp table: we believe BoCom, CNCB, SPDB, Huaxia, CEB face long-term marginalization risks
Rating
12-Nov
Mkt Cap
Price
(US$ bn)
P/B (X)
2014E
2015E
Adj. P/B
(X)
2014E
P/E (X)
P/PPOP (X)
2014E
2015E
2014E
2015E
Div yield (%)
2014E
2015E
EPS growth (%)
2014E
2015E
ROE (%)
2014E
2015E
H-shares (HKD)
ICBC (H)
1398.HK
Buy
5.05
229
0.96
0.84
1.03
5.0
4.6
3.4
3.1
7.1
7.6
7.0
7.1
20.6
BOC (H)
3988.HK
Neutral
3.84
138
0.82
0.74
0.89
5.0
4.7
3.2
3.0
7.0
7.5
7.8
7.1
17.3
16.6
CCB (H)
0939.HK
Buy
5.72
184
0.92
0.81
0.95
4.9
4.6
3.2
2.9
7.0
7.4
7.9
5.2
18.8
17.5
19.9
19.3
ABC (H)
1288.HK
Buy*
3.56
149
0.93
0.82
0.93
4.8
4.4
3.1
2.9
7.3
8.0
14.3
10.2
20.8
BoCom (H)
3328.HK
Neutral
5.95
57
0.74
0.67
0.81
5.3
5.0
3.2
3.1
5.8
6.7
5.7
5.1
14.3
13.8
CMB (H)
3968.HK
Buy
14.78
48
0.96
0.83
1.01
5.1
4.8
3.3
3.0
4.4
4.9
11.8
5.6
20.2
18.4
CNCB (H)
0998.HK
Neutral
5.32
32
0.75
0.66
0.88
4.5
4.4
2.7
2.4
5.5
5.7
10.4
3.6
16.4
15.1
Minsheng (H)
1988.HK
Neutral
7.99
35
0.92
0.79
1.03
4.6
4.5
2.9
2.7
5.5
5.3
10.7
1.0
21.1
18.3
CQRCB
3618.HK
Neutral
4.39
5
0.77
0.69
0.88
4.8
4.6
2.5
2.2
6.1
6.4
11.3
4.4
17.1
15.9
BOCQ
1963.HK
Neutral
5.51
2
0.75
0.66
0.84
4.3
4.0
2.2
1.9
5.8
6.2
17.6
7.3
18.8
0.85
0.75
0.93
4.8
4.6
3.0
2.7
H-share average
6.1
6.6
10.5
5.6
18.5
17.6
17.2
FEH
3360.HK
Buy
7.16
3
1.22
1.07
7.8
6.1
4.6
3.7
3.9
4.9
25.6
26.2
15.8
17.5
Cinda
1359.HK
Buy*
3.92
18
1.29
1.13
9.5
7.6
5.8
5.1
2.6
3.3
3.7
25.3
14.3
15.8
A-shares (RMB)
ICBC (A)
601398.SS
Buy
3.76
216
0.90
0.79
0.97
4.7
4.4
3.2
2.9
7.5
8.0
7.0
7.1
20.6
BOC (A)
601988.SS
Neutral
3.08
140
0.83
0.75
0.90
5.1
4.7
3.3
3.0
6.9
7.4
7.8
7.1
17.3
16.6
CCB (A)
601939.SS
Buy
4.31
176
0.88
0.78
0.91
4.7
4.4
3.0
2.8
7.3
7.8
7.9
5.2
18.8
17.5
19.9
19.3
ABC (A)
601288.SS
Buy*
2.65
141
0.88
0.77
0.88
4.5
4.1
2.9
2.7
7.7
8.5
14.3
10.2
20.8
BoCom (A)
601328.SS
Neutral
4.65
56
0.74
0.67
0.80
5.2
5.0
3.2
3.0
5.9
6.7
5.7
5.1
14.3
13.8
CMB (A)
600036.SS
Buy
10.99
45
0.90
0.78
0.95
4.8
4.5
3.1
2.9
4.7
5.2
11.8
5.6
20.2
18.4
CNCB (A)
601998.SS
Sell
5.22
40
0.93
0.82
1.10
5.6
5.4
3.3
3.0
4.4
4.6
10.4
3.6
16.4
15.1
Minsheng (A)
600016.SS
Sell
6.81
38
0.99
0.86
1.11
5.0
4.9
3.2
2.9
5.1
4.9
10.7
1.0
21.1
18.3
SPDB
600000.SS
Neutral
11.05
34
0.86
0.75
1.01
4.5
4.2
2.8
2.6
6.3
6.6
12.9
5.3
20.6
18.9
Industrial
601166.SS
Neutral
11.02
29
0.89
0.76
1.10
4.5
4.2
2.7
2.4
4.6
4.9
14.4
6.9
21.6
19.6
Hua Xia
600015.SS
Sell
9.09
13
0.82
0.73
1.05
4.9
5.0
3.1
2.8
5.1
5.0
6.3
-2.4
17.9
15.4
BONB
002142.SZ
Neutral
11.61
5
1.12
0.97
1.21
6.2
6.0
3.9
3.7
3.0
2.9
10.7
3.3
19.4
17.2
BOBJ
601169.SS
Neutral
8.48
15
1.00
0.88
1.18
5.9
5.6
3.8
3.5
4.3
4.5
13.2
5.2
18.2
16.8
BONJ
CEB
601009.SS
Sell
11.26
5
1.10
0.99
1.26
6.8
6.6
4.6
4.2
4.4
4.6
8.8
3.5
17.2
15.9
601818.SS
Sell
3.09
23
0.82
0.72
0.99
5.1
4.9
3.2
2.8
4.3
4.5
3.8
6.0
17.0
15.8
0.92
0.80
1.04
5.3
5.0
3.3
3.0
5.2
5.5
10.2
5.3
18.6
17.1
Big banks average
0.87
0.77
0.91
4.7
4.4
3.1
2.9
7.3
7.9
9.3
7.4
19.4
18.3
Shareholding banks average
City Bank Average
0.88
0.77
1.05
5.1
4.9
3.1
2.8
4.7
4.9
10.4
4.9
18.3
16.7
1.07
0.95
1.22
6.3
6.1
4.1
3.8
3.9
4.0
10.9
4.0
18.3
16.6
A-share average
* denotes the stock is on our regional Conviction List.
资料来源： Datastream, Gao Hua Securities Research
全球投资研究
7
2014 年 11 月 14 日
中国：金融服务
The stage is set for Titans to clash: Internet finance to come of age in the next decade
Internet finance in China has been developing rapidly in China, evidenced by the leadership of Alipay/Tenpay in online shopping payment
marketing, the boom in internet money market funds (c. Rmb1tn increase in AUM in the past year), thousands of P2P lending websites, and
BAT’s push in O2O payment, etc.
We expect internet players will accelerate development of their consumer credit and SME banking capabilities, building on their success in
gaining a lead over banks in the online payment scenarios. We forecast consumer and SME loans/payment-related business of internet
giants (essentially BAT and JD.com) could generate US$29bn/US$11bn net profits by 2024, or up to c. 6%/2% of bank profits. We estimate
their overall loan book could grow to Rmb6.8 tn in 2024, representing 2% of total social financing, excluding bonds and equities in China.
We see four key drivers of internet finance in China
(1) Rapid growth in e-commerce and mobile commerce activities in China, thanks to increasing numbers of internet and smartphone
users, improving logistics for online shopping, and a plethora of e-commerce providers. For example, Alibaba Group’s Tmall and Taobao
market places’ Gross Merchandise Value (GMV) reached Rmb1.5tn in 2013, 3% of GDP and 14% of retail sales. Moreover, China’s ecommerce penetration ratio and smart phone penetration ratio growing at the fastest clip among major economies and quickly catching up
with the US (Exhibits 2-6).
Exhibit 2: Alibaba Group’s Tmall and Taobao market places’ GMV on a steady upward curve
The GMV of Tmall and Taobao retail market place vs. nominal GDP and total retail sales
As % of nominal GDP
As % of total retail sales
30%
25%
20%
15%
10%
5%
2018E
2017E
2016E
2015E
2014E
2013
2012
0%
资料来源： Company data, Wind, Goldman Sachs Investment Research
全球投资研究
8
2014 年 11 月 14 日
中国：金融服务
Exhibit 3: According to Euromonitor, E-commerce as % of GDP in China rose
to 1.02% in FY13 vs. 1.24% in US, and will catch up rapidly
Ecommerce as a % of nominal GDP
2.5%
2.0%
United States
Western Europe
Japan
Brazil
India
China
Exhibit 4: According to Euromonitor, e-commerce as % of retail sales in
China rose to 5.5% vs. 7.7% in US in FY13 and will catch up rapidly
14%
Ecommerce as a % of total retail (online + offline)
12%
10%
United States
Western Europe
Japan
Brazil
India
China
8%
1.5%
6%
1.0%
4%
0.5%
2%
2018E
2017E
2016E
2015E
2013
2014E
2012
2011
2010
2009
2008
2007
2006
2005
2004
2003
2002
2001
1999
2018E
2017E
2016E
2015E
2013
2014E
2012
2011
2010
2009
2008
2007
2006
2005
2004
2003
2002
2001
2000
1999
2000
0%
0.0%
Note: The e-commerce data refers to B2C retail value only excl. sales tax based on Euromonitor of
which e-commerce definition differs from Alibaba retail GMV (B2C and C2C). Hence China’s Ecommerce value based on Euromonitor is smaller than Alibaba’s retail GMV.
Note: The e-commerce data refers to B2C retail value only excl. sales tax based on Euromonitor of
which e-commerce definition differs from Alibaba’s retail GMV(B2C and C2C). Hence China’s Ecommerce value based on Euromonitor is smaller than Alibaba’s retail GMV,
资料来源： Euromonitor, Wind, Goldman Sachs Investment Research
资料来源： Euromonitor, Wind, Goldman Sachs Investment Research
Exhibit 5: China’s smartphone subscription as % of population (aged 15 to
64) is improving rapidly and catching up with developed countries
Exhibit 6: A similar trend is occurring in China’s smartphone subscription as
% of total handsets
North America
Japan
Brazil
India
China
80%
120%
North America
Western Europe
Japan
Brazil
India
China
100%
70%
60%
80%
50%
60%
40%
30%
40%
20%
20%
10%
全球投资研究
2016E
2015E
2014E
2013
2012
2011
2010
2016E
2015E
2014E
2013
2012
2011
2010
2009
资料来源： Gartner, Global Mobile, World Bank, and Goldman Sachs Investment Research
2009
0%
0%
资料来源： Gartner, Global Mobile, World Bank, and Goldman Sachs Investment Research
9
2014 年 11 月 14 日
中国：金融服务
(2) Internet players’ financial innovations as a catalyst or a driving force for financial service “deregulation”, as the tight
regulations on banks and insurers and the interest rate and loan quota regulations provide many growth opportunities for internet finance
to serve un-satisfied demand.
In our view banks have weaker incentive to lend to consumers and SMEs than to big SOEs because of China’s loan quota policy, implicit
government guarantees of SOEs, the 75% L/D ratio cap and an undeveloped credit investigation system for smaller borrowers. As a
result, many SMEs have a cost of funding of 16% or more, considerably higher than large corporates of 5%-6%, and many SMEs and
consumers have limited access to bank loans or corporate bonds (Exhibits 7-9). Therefore, we believe the underpenetrated market for
smaller borrowers provides internet players with growth potential in these areas.
In contrast, government is supportive of financial innovation in the internet sphere, and has imposed limited regulatory limits
to internet finance providers so far. China’s government has encouraged financial innovations to serve SMEs and consumer banking.
For instance, the banking regulators recently approved for Tencent and Alibaba Group to be major shareholders and sponsors of two
new private banks.
Exhibit 7: SMEs have much higher funding costs than large corporates, partly
due to their limited access to traditional bank loans/corporate bond markets
Exhibit 8: SMEs loans accounted for only 31% of bank loans in 2013
Funding cost by borrower type
18.6%
20%
18%
16%
14%
12%
10%
8%
6%
4%
2%
0%
SME loans as % of total loans
2012
31.0%
31%
2013
15.6%
30.5%
30%
30.0%
5.9%
29.5%
29%
4.7%
29.0%
28.5%
1Y Informal
lending in
Guangzhou
Proxy for
subprime
SME/consumers
Chailease
CCB corp loan AAA Corp 1Y
China(secured
yield
SMEs)
Proxy for
secured SMEs
Proxy for
big corps
2012
2013
Proxy for
big corps
Source: PBOC, company data, Wind, Goldman Sachs Investment Research, Gao Hua Securities Research
全球投资研究
2011
Source: PBOC, company data, Wind, Goldman Sachs Investment Research, Gao Hua Securities Research
10
2014 年 11 月 14 日
中国：金融服务
(3) Internet players have strong incentives and capability to collect and analyze transaction, behavior and payment data to
enable them to improve risk management and target potential users for certain markets. In contrast, although banks have a plethora of
transaction data in credit and banking cards, we believe they have so far not analyzed or utilized this data effectively to do targeted marketing
or credit analysis.
(4) BAT and JD.com have a more closed ecosystem to execute both transactions and payment and capture multi-dimensional data for
credit assessment. In China, third-party payment tools (mainly Alipay, Tenpay, etc.) made up of 76% of online shopping volume in 2013, vs.
only 15% in the US, where e-commerce payment is dominated by US banks (Exhibit 10).
The closed ecosystem includes both e-commerce transactions and payment, enabling internet players to know the identity of the customer,
whether payment has been made, whether the transaction is completed, and whether the vendor has received payment. The information
gathered in closed systems on transaction and fund flow can help internet players perform credit analysis, and ascertain whether the
suppliers or customers need working capital. Banks typically are strong in capturing such data for offline commerce transactions and payment.
Exhibit 9: Consumer leverage has been much lower than corporate leverage
in China, suggesting big growth potential for consumer banking in China
(as % of GDP)
270
243
240
252
Exhibit 10: Bankcard share in online shopping in China is much smaller than
US, suggesting internet players have more closed ecosystem to complete
transaction and payment functions
Total debts
as % of GDP
Internet shopping payment volume's share by payment
tools in 2013 estimated by GS
229
208
210
195 194
24%
181
180
161 156
155 154 153 153
155
135 138
112
120
Third-party
76%
Govt.
Leverage
15%
Consumer
loans
US
2015E
2014E
2013
2012
2011
Bankcard
85%
LGFV
leverage(loa
n, bond)
2010
2008
2007
2006
2005
2004
资料来源： PBOC, Wind, Gao Hua Securities Research
Corporate
leverage
125 129 142
24 25 22 23 27 24 23
13 15 15 16
12
11
9
23
27 25 24 24 24
0 7 24 25 26 32 28 30 28 29
22
22
16 19 19 20 23 25 26
4 6 9 12 12 12 11 12 12
2000
0
107
2003
30
103
2002
60
109
2001
90
169 179
114 106 98 98 96 97
2009
150
149
China
资料来源： iResearch, company data, Goldman Sachs Investment Research, Gao Hua Securities
Research
全球投资研究
11
2014 年 11 月 14 日
中国：金融服务
Internet finance giants’ profit: US$40bn by 2024, equal to around 8% of banks’ profits
We project the consumer and SME loan balance of internet giants (essentially BAT and JD.com) to rise to Rmb6.8tn by 2024E, generating
76% CAGR in the coming decade from its start-up loan base of c.Rmb7bn in 2013. Even still, this will represent only 2% of total social
financing (excl. bonds and equities) in 2024E, as we expect banks’ and other financial institutions will also grow their credit products at a
2014E-2024E CAGR of 12%.
Our projection of 76% CAGR over 10 years off a low base takes into consideration:
•
BAT need time to build up their capital base if they aim to grow their offline SME and consumer loans. According to the China
Banking Regulator (CBRC), banking financial institutions’ capital base was c. Rmb11tn in August 2014, multiple times larger than
the capital of BAT’s financial companies. (e.g. the Rmb1.2bn registered capital of Small and Micro Financial Services Company,
Alibaba’s financial business; the Rmb3bn registered capital of WeBank invested by Tencent; and the Rmb200mn registered capital
of Baidu’s micro lending firms)
•
It may take time for internet players to develop solid risk management models in the off-line business. Currently Alibaba’s initial
success in online SME loans (e.g. Alibaba’s Rmb15 bn SME loan portfolio has an NPL ration of around 1%) is built around selected
Taobao shops for which Alibaba has information about sales and cash flow. In addition, Alibaba is able to control the activities of a
Taobao shop in the case of a loan default, providing an incentive for vendors to maintain payments.
As the internet giants move into offline channels to compete with traditional banks, we believe their inherent information advantage over
banks will be diluted, and therefore their expansion will be less rapid that in their online business models.

In terms of their profits, we project internet player could earn 28% ROE and NPAT of Rmb180 bn (US$29bn) from credit products
or c.6% of banks’ overall profits in 2024E), as they will mainly focus on the areas with the most promising and profitable bank
business — consumers and SMEs.

Separately, we forecast BAT payment businesses could earn net profits of Rmb66bn (or US$10.7bn), with a 24% CAGR in the next
decade, driven by robust internet shopping and their push into O2O payment.
In terms of banking sector profitability projection, we project banks’ ROA to decline from 1.35% in FY13 to 0.82% in 2024, given:
全球投资研究

A fall in the net margin from an average 2.68% in FY13 to 2.01% in 2024E, due to the increasing competition and interest rate
deregulation.

Average credit costs to normalize to 1% in 2024 from 0.64% in FY13.

Credit growth to slow to c. 10% in FY2024E from 17.9% yoy in FY13.
12
2014 年 11 月 14 日
中国：金融服务
Exhibit 11: We project that the credit products underwritten by internet
giants/P2P players could account for 2%/0.9% of TSF balances excl. bonds
and equities in 2024E
Rmb bn
Credit as % of TSF excl. bonds/equities
P2P
2.4%
Exhibit 12: We project that the internet credit products of BAT and JD could
earn profits equivalent to c.6% of bank sector’ profit in 2024E
Internet giants (mainly BAT, JD)
Profit of Internet giants' credit products
200
180
As % of bank profits (RHS)
8%
158
2.0%
137
150
6%
116
1.6%
100
1.2%
4%
84
53
0.8%
50
2%
27
0.4%
5
2
1
0
12
0%
2024E
2023E
2022E
2021E
2020E
2019E
2018E
2017E
2016E
2015E
2013
2024E
2023E
2022E
2021E
2020E
2019E
2018E
2017E
2016E
2015E
2014E
2013
2014E
0
0.0%
资料来源： PBOC, company data, Gao Hua Securities Research
资料来源： CBRC, company data, Gao Hua Securities Research
Exhibit 13: We project of BAT and JD Transaction Payment Value(TPV) could
grow to 4.5% of bankcard payment volume in 2024E
Exhibit 14: We project of BAT and JD payment profits c reach Rmb66bn in
2024E
Internet giants' payment volume
Relative to bankcard payment (RHS)
Rmb bn
80,000
5%
70,000
Internet giants' paymenet NPAT
Rmb bn
70
50%
yoy (RHS)
60
4%
60,000
50,000
3%
40
30%
2%
30
20%
40,000
30,000
40%
50
20
全球投资研究
2024E
2023E
2022E
2021E
2020E
2019E
2018E
2017E
2016E
2024E
2023E
2022E
2021E
2020E
2019E
2018E
2017E
2016E
2015E
2014E
2013
资料来源： PBOC, company data, Gao Hua Securities Research
0%
0
2015E
0%
0
10%
10
2014E
1%
10,000
2013
20,000
资料来源： PBOC, company data, Gao Hua Securities Research
13
2014 年 11 月 14 日
中国：金融服务
Exhibit 15: Our detailed long-term projection of banks, internet giants’ (predominantly BAT, JD) credit products and payments
RMB, bn
2012
81,673
2013
96,313
2014E
110,612
2015E
125,461
2016E
142,303
2017E
159,272
2018E
178,264
2019E
199,520
2020E
223,311
2021E
249,940
2022E
279,743
2023E
311,702
2024E
345,753
2025E
381,795
1.120718
17.9%
14.9%
13.4%
11.9%
11.9%
11.9%
11.9%
11.9%
11.9%
11.4%
10.9%
10.4%
9.9%
100,500
113,348
130,265
147,752
165,370
185,089
207,160
231,862
259,510
290,455
323,637
358,992
396,414
435,755
2.75%
2.68%
2.59%
2.50%
2.41%
2.36%
2.31%
2.26%
2.21%
2.16%
2.11%
2.06%
2.01%
1.96%
19.83%
21.2%
22.2%
23.2%
23.2%
23.2%
23.2%
23.2%
23.2%
23.2%
23.2%
23.2%
23.2%
23.2%
38.8%
0.64%
38.8%
38.8%
38.8%
38.8%
38.8%
38.8%
38.8%
38.8%
38.8%
38.8%
38.8%
38.8%
Credit cost
39.4%
0.61%
Profit
1,239
1,418
0.65%
1,565
0.73%
1,692
0.78%
1,789
0.83%
1,911
0.88%
2,036
0.93%
2,164
0.98%
2,294
1.00%
2,459
1.00%
2,655
1.00%
2,849
1.00%
3,041
1.00%
3,226
TSF excl bonds and equity
yoy growth
Bank P/L
Bank earnings assets est.
NIM
Non-NII income as % of revenue
CIR
ROAE
19%
19%
18%
17%
16%
16%
15%
14%
13%
13%
12%
12%
12%
ROAA
1.35%
1.31%
1.24%
1.17%
1.11%
1.06%
1.01%
0.95%
0.91%
0.88%
0.85%
0.82%
0.79%
2,335
Internet credit products
P2P
6
27
yoy growth
as % of TSF excl bonds, equities
Internet giants (mainly BAT, JD)
yoy growth
2
as % of TSF excl bonds, equities
Margin
0.0%
7
0.0%
11%
Cost-income ratio
83
233
465
698
816
954
1,116
1,304
1,519
1,760
2,032
210%
180%
100%
50%
17%
17%
17%
17%
16%
16%
15%
15%
0.1%
0.2%
0.4%
0.6%
0.6%
0.6%
0.7%
0.7%
0.8%
0.8%
0.9%
0.9%
23
230%
73
210%
211
190%
550
161%
1,215
121%
2,199
81%
3,321
51%
4,450
34%
5,206
17%
5,935
14%
6,766
14%
7,713
14%
0.0%
11%
0.1%
11%
0.1%
11%
0.3%
10%
0.7%
10%
1.1%
9%
1.5%
9%
1.8%
8%
1.9%
8%
1.9%
7%
2.0%
7%
2.0%
7%
46%
46%
46%
46%
44%
42%
40%
38%
36%
35%
35%
34%
34%
Credit cost
0.8%
0.8%
0.9%
0.9%
1.0%
1.0%
1.0%
1.0%
1.0%
1.0%
1.0%
1.0%
1.0%
Profit
yoy growth
0
1
237%
2
211%
5
174%
12
162%
27
127%
53
92%
84
60%
116
38%
137
19%
158
15%
180
14%
206
14%
Capital needed
2
as % of bank profit
0.0%
ROE
21
55
121
220
332
445
521
593
677
771
0.0%
0.1%
7
0.3%
0.6%
1.3%
2.4%
3.7%
4.7%
5.2%
5.5%
5.9%
6.4%
23%
35%
32%
32%
31%
31%
31%
30%
28%
28%
28%
28%
Payment
Bankcard transaction payment
yoy growth
Internet giants
yoy growth
346,212
423,360
495,331
569,631
646,531
730,580
818,250
908,257
1,008,165
1,119,064
1,242,161
1,378,798
1,530,466
22%
17%
15%
14%
13%
12%
11%
11%
11%
11%
11%
11%
1,698,817
11%
4,971
6,967
40%
9,641
38%
13,175
37%
17,568
33%
22,396
27%
27,096
21%
32,727
21%
39,465
21%
47,523
20%
57,148
20%
68,637
20%
82,339
20%
10
14
19
25
33
41
49
59
69
82
97
115
135
Tak e rate
0.20%
0.20%
0.19%
0.19%
0.19%
0.19%
0.18%
0.18%
0.18%
0.17%
0.17%
0.17%
0.16%
Cost-income ratio
30.0%
29.5%
29.0%
28.5%
28.0%
27.5%
27.2%
26.9%
26.6%
26.3%
26.0%
25.7%
25.4%
5
8
39%
10
37%
14
35%
19
32%
23
26%
28
20%
33
19%
40
19%
47
19%
56
19%
66
18%
79
18%
Payment fees and idle funds' interest income
Internet giants' payment NPAT
yoy growth
Note: The P/L data of internet giants’ credit products and their payment in 2012 and 2013 are our estimates.
资料来源： Company data, PBOC, CBRC, Gao Hua Securities Research
全球投资研究
14
2014 年 11 月 14 日
中国：金融服务
The first battleground: payment as client/data acquisition tool; now moving to offline
Online payment develops rapidly – large by transaction number, but small by value
Payment has been the first battleground — a primary tool to gather clients, transactions and data; after success in online, BAT is moving offline and into O2O. Internet players like Alipay have been rapidly developing their payment business, and taking market share from
banks/China Unionpay. They have dominated the PC and mobile consumption payment market — taking 76% of volume by value in 2013.
Particularly, we note Alipay in 2013 has almost drawn level with bankcard consumption payment in terms of transaction units (albeit a fraction
by value). Moreover, it gained 21% market share in third-party Transaction Payment Volume, second behind Unionpay’s subsidiary
ChinaUnionpay Merchants Service (ChinaUMS) (Exhibits 16-17).
Exhibit 16: Alipay’s number of transactions rose rapidly to 98% of bankcard
consumption payments, although its TPV was only a tenth (Rmb3.6tn vs. 32tn
in 2013)
Exhibit 17: Third-party players’ TPV was much smaller than banks’ due to
their small-ticket size. Alipay’s share in the third-party payment (internet +
offline) was 21% vs. 40% of Unionpay’s subsidiary ChinaUMS in 2013
TPV in Rmb tn, and market share breakdown in third-party payment
(bn units)
# of Alipay transaction
14
# of bankcard consumption transaction
Tenpay
8%
Alipay
21%
12
China PNR
6%
99bill
6%
10
Banks
1,344
8
6
4
Third
party
players
17
Tong Lian
payment
4%
ChinaUMS
40%
Others
10%
Sandpay
3%
Yeepay
2%
2
0
2009
2010
2011
2012
资料来源： PBOC, Company data
2013
资料来源： iResearch
The move to offline
The payment battle between banks/Unionpay and the internet giants has become fiercer since BAT started to develop mobile payment
solutions for offline business — so called O2O (online to offline) business, challenging banks’ offline payment leadership. We believe
全球投资研究
15
2014 年 11 月 14 日
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payment is a high ROE busin
ness for BAT given their scale and limited credit risks involved as payment does not involve any lending business,
generating service fee income
e with little capital.
Moreover, we believe BAT w
will increasingly leverage their payment functions to gather clients, transaction and payment data both
within and outside their group
ps, and both online and off-line:

Payment also prov
vides user traffic and client information between consumers and corp
porates (B2C) and among customers
(B2B and C2C), and
d acts as a channel of financial product distribution. Widely-used payment to
ools like Alipay and Tenpay can
attract lots of consum
mers to merchants and be used to execute various B2C/B2B/C2C transactiions. Moreover, the majority of
frequent interactionss between internet financial service providers and customers occur in paym
ment services, such as small ticket
purchase, money tra
ansfers among friends, settlement etc.

Payment can help
p BAT collect a variety of data to help run credit risk management. It captures shopping, fund flow,
identities of parties, merchant sales data, etc, which can be analyzed by internet players to asc
certain precise customer financial
needs and borrowerrs’ credit quality.
p
user traffic for
Exhibit 18: Payment collects a variety of data for internett players and banks to run data mining and risk management. It also provides
B2C/C2C/B2B economic transactions, and acts as a chan
nnel for financial products
资料来源： Gao Hua Securities Research
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We expect both bankcard payment and BAT’s payment methods will continue to grow rapidly. However, we expect BAT’s payments, to
register much higher growth, driven by internet commerce, smartphone penetration, user-friendly experience that is supported a simple,
convenient and intuitive system, and the addition of more payment scenarios in BAT’s ecosystems (Exhibit 19). We also expect Alipay and
Tenpay to further develop their off-line payment scenarios such as Alipay’s recent move to offline merchants such as hospitals and taxis.
We think these off-line payment scenarios are critical to BAT to further develop their O2O business — by acquiring off-line clients including
SMEs, acquiring transaction data, and allowing the off-line business model to be a relatively closed ecosystem. In turn, this should enable
them to build a foundation to develop their consumer and SME banking.
In contrast, banks and China Unionpay are traditionally strong in off-line payment scenarios, and have enjoyed high growth over the past
decade with their merchant penetration ratio rising to 47% in 2013 from 11% in 2008. Their dataming capability, however, is still undeveloped.
Exhibit 19: We see continued increase of penetration of bank cards, but online/mobile payment should have much higher growth than banking cards
Red marked numbers are GS est.
Unit
Bankcard system
Bank card Consumption Volume
RMB bn
2008
2009
2010
2011
2012
2013
2014E
2015E
2016E
2017E
3,947
6,861
10,430
15,212
20,826
31,830
42,334
52,917
63,501
73,661
32%
74%
52%
46%
37%
53%
33%
25%
20%
16%
Mn
1.85
56%
2.41
31%
3.33
38%
4.83
45%
7.12
47%
10.63
49%
14
30%
16
15%
17
10%
19
6%
Mn
1.2
59%
11.3%
1.6
33%
13.7%
2.2
39%
17.6%
3.2
46%
23.4%
4.8
52%
32.8%
7.6
58%
46.9%
9.4
23%
53.0%
11.1
18%
57.6%
12.3
11%
59.2%
13.2
7%
59.2%
yoy
POS machine
-No. of POS
yoy
Merchant penetration
-No. of merchants accepting bankcard payment
yoy
-As % of total merchants
Online payment system
Internet retail shopping
%
128
263
461
785
1,303
1,983
2,761
3,784
4,775
5,637
129%
105%
75%
RMB bn
70%
12
66%
69
52%
274
39%
828
37%
1,616
26%
2,517
18%
3,207
RMB bn
773
490%
1,234
297%
1,709
202%
1,932
95%
2,168
56%
2,259
27%
2,429
60%
38%
13%
12%
4%
8%
RMB bn
yoy
- Mobile shopping
yoy
- PC shopping
yoy
Penetration ratio by various consumption channels
Bank card consumption as % of retail
sales(excl. property/auto/wholesale)
%
Mobile shopping as % of retail sales
PC shopping as % of retail sales
24%
32%
35%
39%
44%
47%
51%
53%
56%
58%
%
0.1%
0.3%
1.2%
3.1%
5.6%
7.9%
9.3%
%
4.2%
5.9%
7.2%
7.3%
7.5%
7.1%
7.0%
资料来源： iResearch, PBOC, Gao Hua Securities Research
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NFC payment function could provide banks a way to repel BAT, if well executed
We believe banks will need to increase investment and more focus their efforts to develop their banking card and new payment
technologies. Moves are underway, however. For example, Unionpay and many banks are pushing NFC mobile payment, potentially using
the iPhone 6 (according to Caixin) and already in conjunction with Xiaomi, Huawei and others. If executed well, this could provide a way for
banks to defend their traditional dominance of payments. NFC is a near-field payment tool with bankcard information stored in cellphones.
Unionpay is leading banks to promote NFC and has upgraded over 3mn POS to NFC-enabled machines. NFC as a system has greater
speed and safety for offline merchant payment scenarios than bar-code payment tools.
However, we believe NFC’s effectiveness remains to be established in China, as there is insufficient incentive for offline merchants to use
NFC and it has not deeply penetrated consumers consciousness, even though NFC has many advantages over the bar-code payment
system employed by the internet giants. For NFC payment to become widely used in the next few years, we believe banks and Unionpay will
need to do the following:

Aggressively promote NFC and install more NFC enabled POS machines in offline merchants.

Simplify or remove the NFC-wallet charge process from customers’ bank accounts to separate NFC wallet accounts. Currently,
customers need to get a special NFC wallet account for small ticket payments, which link to their bank accounts, and need to
transfer money before they use NFC. This greatly impacts on their user experience, and so need to be simplified, in our view.

Collaborate with as many mobile manufacturers and telecom operators as possible.

Develop value-added services to incentivize merchants and consumers, similar to BAT’s CRM service for merchants and
customized merchant recommendation for consumers.
Recently, Apple launched the NFC function in its i-Phone6 in the US. We believe that if China banks and Unionpay can reach an agreement
to cooperate with Apple, their NFC payment can overcome its user-experience weakness, penetrate Apple aficionados and attract other
cellphone manufacturers to follow its NFC model, it will give them a way of defending their position from the BAT challenge.
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Exhibit 20: NFC has advantages in speed, safety, offline use over bar-code payment. But we believe NFC in China still has many weaknesses to overcome,
including its money-charge process, and the absence of consumer awareness or incentive for offline merchants
Bank system' NFC
Code payment led
by Alipay/Tenpay
Payment speed
Internet access
Safety
Money charge
Only one quick touch
No
High
Pre-charge on ATM/UnionPay website. <Rmb 1k+
Three steps
Needed
Unconfirmed, software encryption
No pre-charge needed. Linked to Yu'ebao/credit card, etc.
Offline scenarios
Over 3mn+ NFC POS.
Gradual penetration by applying online license for offline
merchants
900mn+ users/300mn+ active users in early 2014
Potential attractive CRM service
Temporarily halt code payment in offline payment deals
Mobile users
Limited NFC-enabled cellphones. Likely iPhone6
Merchants' incentive No CRM value-added service launched
Regulation
Support
资料来源： iResearch, PBOC, Company data, Gao Hua Securities Research
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The second battleground: consumer and SME banking — huge but still untested for BAT
Mining their advantages could allow BAT to threaten banks in consumer/SME banking products
Alibaba Group and JD.com already offer SME loans to their merchants and/or suppliers, as well as consumer loans to their clients. We
expect the internet giants and JD will accelerate their efforts in offering consumer banking, credit cards and SME banking online, to leverage
their enormous retail and SME client base, their strong datamining capability (especially for online transactions), and their established ecommerce/m-commerce ecosystem, etc.
We believe that compared with banks, BAT have increasing advantages in four of seven key banking services:

Transactions —capturing online economic transactions, and increasingly pushing into off-line transactions; E.g. Alibaba leads the
online B2B/B2C/C2C commerce transactions in China.

Payment — using online and off-line payment services to facilitate online and O2O transactions and capture clients and payment
data. E.g. Alipay active users reached 300mn+ in early 2014. Alipay is now challenging banks’ leadership in the offline payment
market, by developing offline payment scenarios such as hospital, utilities, taxi and other O2O cases as well as its mobile payment
tools such as code payment, etc

Data — using their ecosystem and big data techniques to gather and analyze clients’ entity and identity data including locations,
age, family size, etc, as well as consumers’ multi-dimensional behavior data such as purchase behaviors, and transaction data.
Essentially they have the ability to analyze who their clients are, their online and off-line behavior, and what they shop for, and
whether they have ability and willingness to repay loans.
For instance, Alibaba captures various data about Taobao merchants including their sales trend, client distribution, client feedback,
logistics and fund flows (Exhibit 22). As such, on the back of its datamining, credit analysis, and automatic loan approval and risk
management, Alibaba can offer attractive unsecured credit products to Taobao merchants at c. 15% to 25% yields. These shops can
easily apply online, get the approval/proceeds instantly and pay much lower funding cost than informal lending (25%-40%). In
addition, we believe Alibaba’s SME business could also deliver high ROEs given its good risk control, on the back its c.18-25% loan
yield, fewer manual data entry requirements and good asset quality (NPL ratio only 1.1pp in early 2014).

Regulatory advantages — so far internet players are subject to limited regulation regarding their financial innovations, whereas
banks face still strict regulations for loan quotas, L/D ratios, and capital and anti-money laundering requirements. There are risks
that in the future regulators may need to level the play field between internet finance players and banks.
However, banks retain their traditional strengths:
全球投资研究
•
Cheap deposit funding — as provided by their licenses to undertake deposit taking business. Although internet players can issue
bonds or undertake securitization to attract funding, we think their funding costs could be at least 300bp higher than banks.
•
Enormous capital positions — to support the business.
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2014 年 11 月 14 日
中国：金融服务
•
On-site due diligence (DD) — based on personal contacts and banks’ broad physical networks, which is critical for risk
assessment of more complicated and bigger transactions such as mortgages and SME loans and corporate loans. For example, in
terms of SME loans, typically the due diligence process checks the true operation of the business, such as production and inventory,
and the background of the entrepreneurs and senior management. Personal contacts and conversations between banks and
corporate, their suppliers and customers are critical for the quality of the DD review.
Exhibit 21: Internet players have increasing advantages in transactions, payment, data and regulations, 4 of 7 key elements for financial services
The comparative advantage of internet players from the angle of the 7 key s for successful financial services
7 key elements for financial services
1
2
Client
acquisition
and risk
mgmt.
Consumers
Note
Internet players' increasing
advantage over banks, part 1:
Online/offline
transactions
Online/offline
payment
3
Data
4
On-site DD
check
1. Increasing internet/mobile consumption traffic
SMEs
Entity/Identity
Behaviors
Transactions
Corporates
Retailers
2. Significant advantage in data mining/big data
computing, which is the basis for risk management
and targeted marketing
3. Dominat position in online payment and increasing
penetration of offline payments through OTOs
Personal
contact
Behaviors
NPL resolution
Internet players' increasing
advantage over banks, part 2:
5
Funding
and
regulations
Deposit
funding
6
7
Capital
Regulation
- Banks face strict regulations while internet players
do not
- Internet players may overcome capital/funding
weakness via innovation (securitization, etc.)
- Banks' advantage
over internet players in funding and on-site DD
1. Deposit funding franchise
2. Strong capital
3. Better on-site DD check and NPL resolution
资料来源： Gao Hua Securities Research
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Exhibit 22: Alibaba’s instant online loan for Taobao merchants: business and risk management process
Client application
Loan approval
Online risk model
Database
‐ Historical sales
‐ Current sales
Online
‐ Client feedback
24/7 service
Instant approval
‐ Client distribution
‐ Promotion plan
‐ Taobao score
‐ Logistics
‐ Fund flow
‐ ID/Entity
Data mining
Customized size
Precise pricing
Post loan mgmt.
‐ Update data in real‐
time
‐ Update the input of its risk model
‐ Automatic risk warning
‐ Location data to support debt collection
‐ Use Taobao stores as a pledge
资料来源： Company data, Gao Hua Securities Research
In light of these fundamentals, we believe internet players’ consumer and SME banking will grow very rapidly off a low base, but it will take
many years for internet players to wrangle significant market shares from traditional financial service players — predominantly due to their
comparatively limited capital and funding. Moreover, internet players will still need to strengthen their multi-dimensional behavior database
and risk management tools as the battleground migrates to off-line consumer and SME banking business, as:
全球投资研究

Compared with banks, internet players still have limited financial-related data (salary, fund flow, personal wealth) for consumers and
SMEs, as well as little insight into the offline commerce transaction data that banks usually capture from banking cards and fund
remittance activities;

Their current off-line risk mgmt. model is still in its infancy, and untested for the bigger and more complicated off-lines financial
transactions.
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2014 年 11 月 14 日
中国：金融服务
Exhibit 23: Mapping the internet finance battlegrounds between banks and BAT, and their relative strengths and weakness
colored cells suggest the strengths of the players
Banks
Economic transactions
Some offline utility transaction
Recent push to grow O2O
C2C small-ticket transaction
Recent push to grow O2O
- Dominating player in on-line
payment via Alipay, esp. in smallticket B2B, B2C, C2C payment
- Strong online payment
scenarios and now gradually
migrating to off-line payments
such as hopital, utilities, taxis,
OTOs, etc
- Strong small-ticket C2C payment
- Convenient online payment
with some online scenarios
- Significant number of customers
that link Tenpay to their banking
cards
- Little B2B payment
Some efforts in
Recent push to grow
O2O commerce and code/web
payment
Recent push to grow
O2O commerce and code/web
payment
Recent push to grow
O2O commerce and
code/web payment
Large amount of
entity/ID/financial/
operating/B2B transaction
data but lack behavior data
Sizable multi-dimension data
incl. household entities
identification, behavior, online
transactions data
Big retail customer Wechat/QQ
touch, ID, behavior data like
networking; future O2O data
Strong search data and some
behavior data, but lack
ID/transaction data
Very limited data mining
Strong data mining/big data,
precise marketing/risk
management capability
Strong skills for data mining
Strong skills for data mining
Current products:
- Third-party WMPs
- some consumer loans
- large amounts of SME loans
Future:
Current products:
- Third-party WMPs
- some consumer loans
- SME loans
Future:
Current products:
-Third-party WMPs
-Gateway for financial
products
-Big potential in financial
search advertisement
More bank products post the
launch of its bank
More bank products post the
launch of its bank
- Strong security
- Strong offline scenarios
- Convenient big-ticket online
payment
Future
O2O commerce and NFC
development payment
Data for
consumer/
SME credits
Data source
Utilization
Financial product selling
Baidu
Some online e-commerce with
investment in JD.com
- Weak online payment
scenarios, less convenient
small-ticket online payment
Payment
Tencent
Strong online B2B/B2C/C2C
commerce transactions
Strong B2B transactions,
offline B2C transactions, C2C
large-ticket transaction
Financial investment
Current status
Alibaba
Little precise marketing
- Deposits
- Bank WMPs
- Third-party WMPs
- Credit card
- Consumer loans
- SME/corp loans
Little online e-commerce
C2C small-ticket transaction
- Convenient online payment
- Weak online/offline
payment as a late entrant
- Few payment scenarios
资料来源： Gao Hua Securities Research
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BAT’s internet finance strategy: Alibaba leads in internet finance
We have analyzed the key strengths, weakness and growth strategies of the BATs’ internet finance business, and believe:
•
Alibaba Group (Alibaba, in this report refers to Alibaba Group and its affiliate Ant Financial Services Group) is the leader in internet
finance in terms of transactions, payment, data, risk management, and comprehensive financial platform.
•
Tencent enjoys strong retail customer acquisition, but has yet to monetize this; its O2O push and new banking subsidiary are
critical to watch for its consumer and SME banking business growth.
•
Baidu is relatively weak in e-commerce, but has the potential to monetize financial related searches and WMP distribution platforms.
However, we note the customer franchises and internet finance strategy of these internet firms will be constantly changing, and we will
continue to monitor new trends.
Alibaba leads in internet finance
We believe Alibaba is the leading internet finance player — with strong e-commerce, payment, data mining, risk management and product
development. The majority of its finance businesses is conducted by Ant Financial Services Group (AFSG, formerly Small and Micro Finance
Service Company), of which 37.5% of profit sharing rights are attributed to the listed Alibaba Group. We believe Alibaba’s strengths in internet
finance include five main strengths:
(1) Its strong and relatively closed e-commerce ecosystem provides a solid platform to acquire consumers/SMEs clients, and capture
payment and consumer behavior data.
•
Its retail e-commerce maintains a leadership position in China, and we think it will be difficult for competitors to catch up. The
GMV (Gross Merchandise Value) of its e-commerce platforms reached Rmb1.9tn in FY14. Taobao dominated with over 90%
market share in C2C commerce, while Tmall account for 57% share in B2C in 2013.
•
Large user base: Around 279mn active buyers and 8.5mn active sellers in its China retail market places in FY14.
•
No. 1 player in online e-commerce transactions (90+ % share in C2C, 57% share in B2C and No.1 in B2B) in 2013.
•
Alipay is the leader in online small-ticket payment market (over 300mn active users in early 2014 and Rmb3.6tn TPV in
2013)
•
Alibaba Group is able to capture sizable multi-dimensional data — including: identity, payment, transactional and users’
behavioral data — and has strong data mining skills.
(2) Alipay dominates online payment, and is now moving off-line into areas such as taxis, hospitals, utility bills, etc., to gather even
more off-line commerce, customer traffics and data.
Alipay initially emerged as a payment tool to facilitate online e-commerce transactions. It offers 7 day credit/escrow accounts so that
customers can buy goods and pay the escrow accounts first; Alipay then releases the funds to online shops after clients are satisfied with the
goods delivered. This helps customers shop online without worrying about fraud (e.g. shops walking away without delivering the goods).
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By contrast, banking cards are not frequently used as consumers have concerns about the safety of putting card information online. Moreover,
neither banks nor China Unionpay have really tried to address such concerns or sufficiently promote banking card e-commerce transactions.
With new services now being rolled out, such as paying utility bills, peer to peer payments, and payment services off-line, Alipay is becoming
an even better tool to captures more customers outside Aligroup’s ecosystem.
(3) Alibaba has strong IT, data mining and cloud computing capability to develop online risk assessing, credit scorings, loan
monitoring systems, which we believe could be more advanced than China banks’ systems for consumer and SME banking.
For instance, in its Taobao merchant loan model (Exhibit 24), Ali-Cloud processes over 30 Petabytes available for data mining every day (a
colossal amount). In our view it is vital for the system to be able to assess risk, rank credit and assign loan limits within seconds and
continuously monitor asset quality trends, perform advanced data mining and have cloud computing. This sets a high entry barrier.
Exhibit 24: Alibaba captures operating data, IT system data, CRM data and personal information of SME owners for its risk
management in its online SME loan model
Data in real‐name account
Implication
Payment, money transfer
PBOC database
Yu'ebao assets
Other WMPs
Wealth
Online sales
O2O sales
Revenue
Client feedback
Client service
E‐commerce creditability
Client distribution
Logistics
Judge sales decoration, address
ERP,
IT system
TBC...
Operation, etc.
Risk mgmt.
ID, fund flow, credit card repayment
Pre‐lending DD
Post‐lending update
Debt collection
资料来源： Company data, Various news sources; Gao Hua Securities Research.
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2014 年 11 月 14 日
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(4) Alibaba has built a comprehensive financial platform. By leveraging the traffic and data in transactions and payment, Alibaba is
actively growing wealth management product (WMP) business — such as Ali-WMP platform, asset managers etc.
Its Yu’ebao money market fund has gained 124mn+ investors and over Rmb500bn in AUM within a year, demonstrating how effective Alipay
can be in bringing traffic to its WMP business.
(5) With Alibaba’s bank license, we believe its SME/consumer lending business looks promising in the long-term.
It is unclear to us what the business models Alibaba’s new bank will adopt, and what the future strategy for AFSG will be.
According to Alibaba, it may build an open platform for its financial services, such as selling WMP of other financial institutions, being a
platform for P2P lending, offering mutual funds such Yu’ebao, and similar strategies.
In the mid-to-long term, we believe Alibaba’s bank subsidiary can offer unsecured consumer loans and credit card loans to its enormous
Alipay customer base, or Taobao/Tmall customers.
For SME loans, we believe Alibaba’s bank subsidiary (30% stake owned by AFSG) can continue to offer its SME loans to serve Tmall and
Taobao merchants online, as its current online SME loan model enjoys the following advantages:
•
Under its real-name account ecosystem, a large number of multi-dimensional data including financial,
personal, location, ID are collected by its ecosystem automatically (Exhibit 27).
•
User-friendly experience for applicants: three minutes for a vendor to apply for a loan and a one minute
waiting period for loan approval and issuance. This compares to the detailed and long-drawn out proves
for offline applications for traditional bank loans.
•
Manageable credit cost: 1.1% NPL ratio in early 2014 for unsecured micro loans.
Moreover, we believe Alibaba can expand SME loans to off-line merchants, as Alibaba increasingly moves offline. Its offline
commerce — such as travel, healthcare and other daily-life consumer business are gradually being incorporated in its
ecosystem.
However, we see these challenges in Alibaba’s finance business going forward:
全球投资研究
•
There is much ground for Alibaba to cover to increase its penetration in offline merchants and make its O2O payment widely-used in
offline scenarios.
•
Its online risk model has not been tested for off-line merchants and large borrowers (especially non-Taobao merchants and
consumer credit cards).
•
It will also encounter more NPL collection problems offline than online, as Alibaba finance division does not have many branches,
and has limited measures of sanctioning borrowers for debt defaults (for online shoppers, Alibaba can close their shops);
•
Its rapid credit growth could be limited by the relatively small capital base of AFSG (registered capital of Rmb1.2bn)
•
If it gains sufficient scale and regulators decide to treat it as a financial institution, AFSG might need to meet similar compliance
requirements as banks for payment, anti-money laundering, customer education, face-to-face interviews, etc.
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2014 年 11 月 14 日
中国：金融服务
Exhibit 25: Alibaba is the leading internet finance player with strong e-commerce, payment, data mining, risk mgmt. and product development
Alibaba’ s SWOT analysis in the internet finance space
Strengths
Weaknesses
1. Dominant player in online B2B/B2C/C2C commerce
1. Small capital base of Alibaba Group and its
financial operations, vs. banks’ capital of Rmb11tn in
Aug 2014
2. Alipay as the leader in online small-ticket payment market
in terms of both # of deals and user base
3. Sizable multi-dimensional data incl. ID, payment,
transaction and its ecosystem's behavior data
2. Relatively weak penetration in offline merchants
4. Top-tier data mining, cloud computing skills supported by
Ali-cloud and Hundsun Tech; good risk mgmt. track record
of Taobao loans
5. Various financial license(bank, mutual funds, online/POS
payment)
6. Strong financial product innovation capabilities like ABS,
Yu’ebao, etc.
Opportunities
1. Grow O2O commerce and payment scenarios to penetrate
offline payment and gain more data (e.g. hospital, taxis, etc.)
Potential risks
2. Develop its ecosystem to lock customers and capture
more behavioral and transaction data
1. Challenges in complying with complicated
financial regulations including payment, anti-money
laundering, customer education, face-to-face
interviews, etc.
3. Sell value-added CRM/marketing service to offline
merchants/SMEs; gather more corporate data from investing
into custom clearing corporates, hotel IT players, etc.
2. Failure of risk management model could cause
high NPLs; lack of off-line NPL collection/
restructuring resources
4. Issue online credit cards, consumer/SME loans based on
data mining after the launch of the new bank
5. Distribute financial product via internet channel
资料来源： CBRC, Gao Hua Securities Research.
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Exhibit 26: Alibaba’ s layout of internet finance strategy: the most comprehensive financial service platform with great potentials in consumer/SME banking and
supported by strong e-commerce traffic and Alipay, and further O2O pushes
Ali-WMP(Zhaocaibao)
- Launched 4/14; WMP platform open to various
FIs
- Products include P2P loans backed by bank
acceptance, mutual funds, fixed-income
insurance
- Transaction volume Rmb14bn+ since April 2014
- Alibaba won't provide guarantees
Micro lendings
Mutual fund firms (incl. Yu'ebao)
- Loan balance Rmb14.6bn in 1H14;
Launched in 2010
- Average loan size Rmb37k in 1H14
- 100% credit loans based on Ali's big data
- NPL ratio 1.1pp in early 2014
- Launched one ABS with quota up to
Rmb5bn to securitize its MSE loans
- Subsidiary Tianhong asset managers
- MMF Yu'ebao AUM Rmb574bn,
124mn+ users in 1H14; T+0 online
consumption function linked to Alipay
- Aim to build a platform of broker
WMPs
Ali-bank
Zhongan P&C
- Focus on
consumer/SMEs
- Online deposit and
lending model
- Small deposit and
loan size
- Online P&C
insurer with 21mn
sales in 2M14
co-investor with
Tencent and
PingAn
Healthcare
Citic 21CN
- online drug-sale
Big data
Hundsun Tech
Alipay
- 900mn+ users/300mn+ active users in early 2014
- TPV Rmn3.6tn/internet mkt share 49pp in 2013
- Internet payment, bankcard POS, online prepaid card licenses
- Set up mutual access with WeiboPay
Online
E-commerce
Taobao
Tmall
- 90+% share in
C2C
- No.1 mobile
ecommerce
app in terms of
MAU as of Jan
2014
- 57.4% share
in B2C
- Pioneered
Singles Day
promotion
festival
O2O websites/apps
Traveling
Transportation
Taxi-hailing app Kuaidi Taobao
- Rmb16bn sales, 50%+ - subs 100mn+
traveling
of them from mobile
- daily deals 6mn+ in
- user share
Local info service
Taobao Life
- SNS media
- MAU 157mn in
2Q14
- provide LBS life
info
- support ordering, - 52% mkt share
payment, coupons in
some nearby
Juhuasuan linked to
restaurants,
Taobao
entertainment, etc.
Tango
- Global Video
chat software
- 200+mn subs
Support
Groupons
Meituan
SNS
Sina Weibo
1Q14
Autonavi Map
- c.33pp share in mobile
in 4Q13
- 100mn+ subs
5.6pp as of
Aug 2013
license
- nationwide drugdistribution data
- 50pp+ mkt share
in FI IT
outsourcing
Ali-cloud
- IT service for FIs
- SME IT system
provider/collect
SME data
Note: data for 2013 unles otherwise stated. Red text represent its core business and strength.
资料来源： Company data, iResearch, Analysys, Gao Hua Securities Research
全球投资研究
28
2014 年 11 月 14 日
中国：金融服务
Exhibit 27: Alibaba Group Finance, Payment and SME/consumer lending forecasts
2014 SAPA
GMV (Rmb bn)
% of total Alipay volume
Implied total Alipay volume
SME loan balance (Rmb mn)
% of GMV
FY2015E
2,418
36%
Alibaba Group's profit share
FY2017E
3,719
33%
FY2018E
4,417
32%
FY2019E
5,095
30%
FY2020E
5,731
29%
6,627
8,645
11,106
13,807
16,712
19,768
43,148
1.8%
84,217
2.8%
140,746
3.8%
211,314
4.8%
294,730
5.8%
388,774
6.8%
1,592
2.5%
2,812
2.5%
4,401
2.5%
4,401
2.5%
4,401
2.5%
6,447
34%
0.07%
37.5%
8,504
32%
0.08%
37.5%
10,849
28%
0.08%
37.5%
13,465
24%
0.08%
37.5%
16,323
21%
0.08%
37.5%
2,417.50
3,189
4,068
5,049
6,121
Annnual fee charged by Alibaba Group
% of average balance
Payment
Alipay PBT (payment only)
% yoy change
% of Alipay GMV
% Alibaba Group's share
FY2016E
3,025
35%
4,810
0.07%
-
SME Lending
Loan balance
% yield
% funding cost
% net spread
43,148
18%
7.0%
11%
84,217
18%
7.0%
11%
140,746
17%
6.5%
11%
211,314
16%
6%
10%
294,730
15%
6%
9%
388,774
14%
6%
8%
Net interest income
4,746
9,264
14,778
21,131
26,526
31,102
431
1.0%
842
1.0%
1,407
1.0%
2,113
1.0%
2,947
1.0%
3,888
1.0%
Other operating costs (including business tax)
% of net interest income
2,373
50%
4,632
50%
7,094
48%
9,720
46%
11,671
44%
13,063
42%
Profit before tax
1,942
3,790
6,277
9,298
11,907
14,151
485
25%
947
25%
1,569
25%
2,324
25%
2,977
25%
3,538
25%
1,456
2,842
95%
3%
10.0
4,708
66%
3%
10.0
6,973
48%
3%
10.0
8,930
28%
3%
10.0
10,614
19%
3%
10.0
34%
8,422
33%
13,130
33%
20,103
30%
29,033
27%
39,647
Provision for bad debt
% provision for bad debt
Income tax
% of PBT
Net profit (SME lending)
% yoy growth
% ROA
Leverage ratio (X)
5.0
% ROE
Book value
资料来源： Company data, Goldman Sachs Global Investment Research.
全球投资研究
29
2014 年 11 月 14 日
中国：金融服务
Tencent still to monetize its retail customers
We believe Tencent has advantages of gathering retail customers through WeChat and Tenpay, but has yet to monetize its internet finance
business given still relatively weak e-commerce transaction volumes vs. Alibaba Group. Its O2O push is critical to developing a
consumer/SME banking operation in the longer run, in our view.
(1) Tencent has a large customer base and stickiness via its WeChat and QQ, providing strong traffic support to its WMP distribution
and other O2O applications.
For instance, Wechat helped Tencent distribute a Rmb62bn money market fund from 2.4mn users, becoming the second largest internet
money market fund as of 1H14. Tencent is in the process of developing a mobile WMP platform, which will allow financial institutions to
distribute various products to its grass-root customers.
(2) Tencent has popular C2C small-ticket payment and a large amount of social network and ID data, a solid foundation for its
consumer lending business especially after its WeBank subsidiary becomes operational.

Tencent captures abundant ID data and behavior data like social networking, peer-to-peer small ticket payment, location, gaming by
levering its WeChat and QQ.

We view this as a good basis for the risk management of consumer loans. However, compared with Alibaba, Tencent lacks of
personal wealth and shopping habits data for assessing credit risks;

We believe Tencent’s WeBank subsidiary (30% stake) will likely to leverage Tencent’s strength to focus online retail loans and
deposits. It may also set up some physical branches or VTM so as to develop its large-ticket payment and bank WMP services.
(3) Tencent can build its off-line transactions and payment-customers plus data (needed elements to develop consumer/SME
banking) via its push into O2O
Tencent invested in Jingdong (JD.com), the No.2 B2C e-commerce player, as well as several influential O2O players in order to quickly
expand its O2O business.
It remains to be seen whether Tencent can effectively migrate its 500-600mn WeChat and QQ users to its m-commerce and O2O commerce
applications (e.g. Jindong, WeChat O2O shops and many other O2O applications) (Exhibit 29).
However, Tencent has not monetized its internet finance, given its following weakness and risks as below:
全球投资研究

Tencent has weaker B2C/C2C e-commerce and online payment transaction volume than Alibaba, which may result in insufficient
transaction data and fund flow data for its online risk management, as well as less access to merchants.

Similar to Alibaba, Tencent faces a relatively small capital base and weak offline DD to combat banks’ current advantage in off-line
commercial activities and their branch network.

Tencent could also face challenges if required to meet compliance requirements for payment, anti-money laundering, customer
education, face-to-face interviews, etc. to level the playing field with banks.
30
2014 年 11 月 14 日
中国：金融服务
Exhibit 28: Tencent has advantages in gathering retail customers through WeChat, and the potential to develop O2O payment/financial service for
consumer/SME financial service in the longer run
Tencent’s SWOT analysis in the internet finance space
Strengths
Weaknesses
1. Strong consumer user base and stickiness to mobile
app WeChat/QQ
1. Weaker online B2C/C2C commerce than Alibaba
and involvement in online B2B commerce
2. Capture some online transaction data by investing in
No.2 B2C commerce player JD.com
2. Smaller market share in online payment than
Alipay
3. More O2O merchant penetration via WeChat accounts
and other services than peers
3. Weaker in consumer fund flow data/SME data
than Alibaba
4. Strong small-ticket C2C payment due to WeChat; large
amount of bank cards linking to Tenpay
4. Small capital vs. banks’ capital of Rmb11tn in
Aug 2014
5. Strong database and data-mining skills
6. Bank license and online/POS payment license
Opportunities
1. Grow O2O commerce and mobile payment to penetrate
offline transaction and gain more data
2. Issue online credit cards and consumer/SME loans
based on data mining after the launch of Webank
3. Distribute financial product via its WeChat and on-line
channel
Potential risks
1. Difficulties in complying with complicated
financial regulations including payment, antimoney laundering, customer education, face-toface interviews, etc.
2. Failure of risk mgmt. model could cause high
NPLs; lack of off-line NPL collection/
restructuring resources and expertise
资料来源： CBRC, Gao Hua Securities Research
全球投资研究
31
2014 年 11 月 14 日
中国：金融服务
Exhibit 29: Tencent’s layout of internet finance strategy: leveraging WeChat success/customer base, growing O2O business and payment business, to further
develop retail/SME banking/WMP distribution
WeChat WMP platform
- Sold MMF with AUM Rmb 62bn to 2.4mn users
as a third-party channel in 1H14
- T+0, consumption or money transfer NA
- Likely to introduce other financial products in
future
- Invest in the leading third-party online mutual
fund platform Howbuy
WeChat service accounts
Micro-lending
- Many FIs launched their service account in
WeChat. Most of them only provide basic
services like balances check, product intro so
far.
- CMB WeChat bank is one of the leading
accounts with 4mn+ subscribers in 2013
- Registered capital of
Rmb300mn in 2013
- Would try to improve
client selection
efficiency based on its
data like SNS
WeBank
Zhongan P&C
- Focus on
consumer/SMEs
- Retail deposit and
SME loans
- Most business
online + physical
branch support
- Online P&C
insurer with 21mn
sales in 2M14
co-investor with
Tencent & PingAn
Traveling
Tongcheng+Yilong
Living
Tenpay
- C. 300mn+ subscribers in early 2014
- Online transaction volume Rmn1tn, mkt share 19pp in 2013
- Internet payment/bankcard POS licenses
Online
SNS
WeChat
O2O websites/apps
E-commerce
Jingdong
- active user 47mn,
600mn subs
779mn hours of visit(55% of 18pp share B2C
the sum of Top10) in Dec13 - 323mn orders,
119bn volume
QQ
Local info service
Dazhong Dianping
in 3Q14
- MAU170mn+
- Merchants profile
10mn+
500mn mobile subs/
594mn hours of visit(42% of
Top10) in Dec13
800mn PC subs
Groupons
Dazhong Dianping
- 21pp mkt share
- c6bn sales
Taxi-hailing
Didi App
- subs 100mn+
7.2pp share in online
- daily deals 5mnm, 88% travelling agency mkt
of which were paid by
Tenpay in 1Q14
Leju
online property
agent leader, 3.4
penetration rate of
property sales in
Top40 cities
3-tier players
Gaopeng, QQ
Note: data in 2013 otherwise stated. Red highlighted texts represent its core business and strength;
Tencent owns 30% of WeBank and 15% of Zhong an P&C
资料来源： Company data, iResearch, Analysys, Gao Hua Securities Research
全球投资研究
32
2014 年 11 月 14 日
中国：金融服务
Baidu: potential in financial searches and WMP distribution; O2O worth watching
Unlike Alibaba and Tencent, Baidu has low e-commerce transaction/payment volumes. However, its strong data mining abilities and internet
search traffic could help it establish its franchise in financial vertical searches and WMP distribution.
We believe Baidu has the potential to establish a popular WMP platform and monetize its financial vertical search, with the
help of its large user traffic and strong data mining skills.
Baidu is the dominant domestic search engine provider — with over 85% market share in both PC and mobile market in 2013. Particularly,
Baidu enjoys large financial-related traffic (350mn financial-related search queries per day).
We believe Baidu could monetize these financial search queries by introducing clients to various financial product providers in a more
efficient and organized way. Financial vertical search could be a revenue driver for search engine companies. For instance, finance and
insurance search business contributes around 11% of Google’s advertising revenue in 2011.
By leveraging such a large volume of traffic, it is also possible for Baidu to develop popular WMP distribution platform like landing pages/
Baifa WMP platform, and become a gateway for various financial product providers.

Its landing page could convert search engine traffic effectively to WMP selling. For example, in future, when a customer searches for
“mutual fund” in Baidu, Baidu could present various mutual fund products and let users fulfill payment & transactions on its landing
pages instead of directing them to financial institutions’ web pages.

Its young WMP platform, Baifa, has the potential to develop to a platform with comprehensive financial products and precise product
recommendation based on its strong data mining skills.

Although only limited mutual fund products and insurance products are currently on sale on its Baifa platform, we believe it is
possible for Baidu to distribute more financial products since Baidu is open to various financial institutions and is applying for more
financial licenses.
We believe its push into O2O commerce could give Baidu an opportunity to develop its mobile payment and transactions for
consumer and SME banking business in the longer term, similar to Tencent. Baidu can leverage its map application (260mn+ subs in 2013) in
the O2O challenge against Alibaba and Tencent.
Although the number of its O2O applications is currently lower than Tencent and Alibaba, we believe the underpenetrated O2O or offline
commerce market will provide massive growth potential for all three of the BAT giants. The O2O market is still in an early stage of
development, and we don’t rule out the chance of the success of Baidu’s mobile payment and Baidu Connect (a customized m-commerce
page directly connecting Baidu Search App users and offline merchants).
全球投资研究
33
2014 年 11 月 14 日
中国：金融服务
Exhibit 30: Baidu is relatively weak in e-commerce transaction/payment, but its strong data mining skill & search traffic may help sell WMPs and/or generate
revenue from financial related searches. O2O worth watching
Baidu’s SWOT analysis in the internet finance space
Strengths
Weaknesses
1. Large user traffic and financial-related search
queries
1. Limited involvement in online B2B/B2C/C2C
commerce
2. Large behavioral database related to search,
hobbies and location
2. Negligible payment market share as a late
entrant and lack payment scenarios
3. Strong data-mining skills, esp. for precise
marketing
3. Weak in ID, transaction, payment and SME data
4. No bank license
4. Some penetration in offline merchants via
Baidu Map
Opportunities
1. Distribute WMPs with precise product
recommendation via its internet WMP platform
and landing pages
2. Provide precise marketing services to FIs
levering its search traffic and data mining skills
Potential Risk
1. Potential later mover into O2O
2. Difficulties in complying compliance standards
of anti-money laundering, customer education,
face-to-face interviews, etc. in its financial
services
3. Develop O2O commerce and payment
scenarios to catch up with Alibaba/Tencent
4. Enter online consumer/SME credit businesses
by cooperating with FIs
资料来源： CBRC, Gao Hua Securities Research.
全球投资研究
34
2014 年 11 月 14 日
中国：金融服务
Exhibit 31: Baidu’s internet finance strategy: convert virtual name accounts to BaiPay users; develop precise WMP selling capabilities; further grow financial
services related search business
Landing page
Baifa WMP platform
- Present various related
product info./link on the
landing pages when users
search for financial products
on its PC search engine
- Sold MMF with AUM Rmb23bn
to 361k users as a third-party in
1H14
- Sold negotiable deposit WMPs
- Likely to promote various
financial products as a thirdparty
Baidu micro-lending
- Launched in 2013
- Registered capital of
Rmb200mn
BaiPay
- New entrant with internet payment license since 2013 July
- Transaction volume's mkt share <1pp in 2013
Online
Search engine
350mn financial-related search
queries per day
Mobile
- 89.1% share, 400mn+ subs
PC
- 85.7% share
SNS
Baidu Tieba
- Subs 600+
- MAU 200mn+
- Based on
virtual name
account/hobbies
O2O websites/apps
Others with 100+mn subs
No.2 video player iqiyi
Internet explorer
Input method
Baidu Map
- 4Q13 share
25pp
- 260mn+
mobile subs
Groupons
Nuomi
Traveling
Qunar
- 7.6pp share
- 22% share in
- c.Rmb2bn sales online travelling
agency mkt
Top2 app download gateway
91wireless, etc.
Note: data in 2013 otherwise stated. Red highlighted texts represent its core business and strength
资料来源： Company data, iResearch, Analysys, Gao Hua Securities Research
全球投资研究
35
2014 年 11 月 14 日
中国：金融服务
Exhibit 32: Internet companies’ valuation comp table
Company
fx
Last
Price
Target
Price
+/Side
35.0
104.0
40.0
265.0
65.0
14.1
31.0
19.9
105.0
27.5
58.0
54.0
13.5
146.0
28.7
25.0
21.0
-24%
-12%
-7%
6%
15%
42%
28%
36%
45%
6%
39%
5%
56%
13%
20%
28%
-4%
15%
Neutral
Neutral
Neutral
Buy
Neutral
Buy
Buy
Buy
Neutral
Neutral
Buy
Neutral
Buy
Buy
Buy
Buy
Neutral
16%
18%
-6%
14%
7%
8%
17%
70%
21%
11%
41%
-3%
22%
17%
16%
Buy*
Buy*
Neutral
Buy
Neutral
Buy
Buy
Buy
Buy*
Neutral
Buy
Neutral
Neutral
Neutral
Rating
EPS CAGR, nonGAAP
14-17E
15-18E
P/E, non-GAAP
2015E
2016E
EV/Revenue
2015E
2016E
EV/EBITDA
2015E
2016E
EV/GCI
2015E
2016E
4,196
311,455
4,835
88,016
8,925
1,350
3,513
1,956
9,555
3,067
2,751
1,992
4,037
155,961
14,268
4,206
4,566
624,648
NM
44.5x
29.6x
25.3x
27.7x
11.2x
30.3x
13.7x
19.2x
NM
16.5x
35.1x
13.4x
29.1x
45.5x
50.1x
NM
28.4x
45.1x
34.0x
21.5x
19.0x
20.7x
8.6x
19.1x
10.3x
14.4x
55.9x
9.5x
14.5x
10.8x
22.7x
30.6x
24.4x
55.2x
20.7x
8.5x
17.8x
9.2x
7.3x
5.2x
0.8x
2.4x
2.6x
4.2x
6.2x
0.5x
0.3x
3.5x
8.6x
2.1x
8.5x
3.0x
4.2x
5.7x
13.9x
6.9x
5.4x
3.9x
0.7x
1.7x
2.1x
3.1x
3.7x
0.4x
0.2x
2.7x
6.7x
1.5x
6.1x
2.2x
3.1x
NM
34.4x
20.0x
18.0x
24.3x
3.4x
21.2x
7.8x
11.1x
NM
3.4x
2.4x
8.8x
19.9x
33.2x
38.2x
NM
19.0x
38.4x
26.4x
14.4x
13.4x
16.1x
2.8x
12.8x
6.3x
8.2x
25.2x
2.2x
1.7x
6.3x
14.6x
21.2x
19.3x
29.6x
14.4x
6.9x
10.4x
4.2x
5.8x
4.1x
0.6x
1.7x
2.4x
3.6x
5.0x
0.2x
0.3x
2.6x
10.2x
5.4x
6.4x
1.1x
4.1x
4.3x
7.7x
2.9x
5.1x
3.4x
0.5x
1.3x
1.8x
2.6x
5.9x
0.1x
0.3x
2.1x
7.2x
3.6x
4.8x
1.0x
2.9x
135%
30%
35%
34%
46%
24%
53%
35%
38%
NM
84%
NM
23%
30%
43%
435%
NM
37%
NM
27%
34%
27%
35%
21%
36%
25%
28%
275%
56%
95%
28%
27%
27%
59%
98%
31%
147,730
68,456
11,547
220,424
384,196
30,109
24,390
4,253
61,916
10,455
30,983
51,079
8,938
4,849
1,134,932
53.6x
17.2x
18.9x
38.5x
18.8x
65.2x
49.5x
29.3x
18.3x
29.0x
87.6x
64.7x
23.7x
56.4x
29.3x
36.5x
14.7x
15.9x
30.5x
15.6x
45.0x
30.2x
17.1x
14.8x
23.4x
40.1x
63.4x
18.9x
30.8x
21.5x
1.3x
3.2x
1.7x
11.8x
5.4x
8.4x
3.2x
2.9x
5.5x
6.0x
11.5x
8.7x
5.9x
7.8x
4.7x
1.1x
2.6x
1.4x
8.7x
4.7x
6.3x
2.5x
2.1x
4.3x
4.7x
7.2x
8.8x
4.6x
5.8x
3.6x
14.9x
10.4x
8.9x
20.0x
11.0x
29.5x
27.7x
23.1x
13.5x
16.7x
46.5x
28.5x
14.2x
39.0x
15.8x
11.6x
9.1x
7.7x
16.1x
9.3x
20.1x
17.2x
13.5x
10.9x
13.4x
25.2x
27.4x
11.4x
20.8x
12.6x
5.5x
1.9x
2.0x
9.1x
2.8x
6.9x
150.4x
19.7x
6.1x
7.4x
6.8x
0.8x
9.0x
16.5x
5.8x
4.3x
1.6x
1.7x
7.5x
2.4x
5.9x
93%
14%
17%
21%
17%
52%
55%
109%
23%
23%
185%
-19%
NA
53%
25%
39%
Mkt Cap
(US$mn)
PEG, non-GAAP
2014E
2015E
China Internet
58.com
$
46.12
Alibaba
$
118.20
Autohome
$
43.00
Baidu
$
249.82
Ctrip
$
56.72
E-house
$
9.94
Jumei
$
24.19
Leju
$
14.65
Qihoo
$
72.37
Qunar
$
26.02
Sina
$
41.84
Sohu
$
51.26
SouFun
$
8.68
Tencent
HK$
129.20
VIPShop
$
23.88
Weibo
$
19.47
Youku Tudou
$
21.83
Median (Sum for Mkt cap)
Global Internet
Amazon
$
311.51
eBay
$
54.06
Expedia
$
87.11
Facebook
$
74.72
Google
$
558
LinkedIn
$
231.13
Netflix
$
384
$
18.79
Pandora
Priceline
$
1,161
TripAdvisor
$
70.38
$
42.54
Twitter
Yahoo
$
50.60
Yandex
$
26.62
Yelp
$
60.58
Median (Sum for Mkt cap)
360.0
64.0
82.0
85.0
600.0
250.0
450
32.0
1,400.0
78.0
60.0
49.0
32.6
71.0
13.7x
5.6x
6.9x
5.5x
0.7x
6.9x
14.5x
4.3x
21%
16%
22%
3%
#
NM
2.0x
1.2x
1.1x
1.0x
0.6x
1.0x
0.6x
0.8x
NM
0.5x
NM
0.7x
1.3x
1.7x
NM
NM
1.0x
NM
1.7x
0.9x
0.9x
0.8x
0.5x
0.8x
0.6x
0.7x
NM
0.3x
0.4x
0.5x
1.1x
1.7x
0.9x
NM
0.8x
NM
1.4x
1.3x
2.1x
1.3x
NM
1.5x
NM
1.0x
1.5x
NM
NM
NM
1.5x
1.5x
1.4x
1.8x
1.2x
0.8x
24.6x
MEDIAN, GLOBAL
12%
1,968,289
21.5x
18.7x
3.2x
2.6x
13.4x
11.4x
3.6x
2.7x
33%
1.2x
Note: All target prices mentioned above are on a 12-m basis except for WUBA, ATHM, BIDU, CTRP, QIHU, QUNR, SINA, SOHU, SFUN, 0700.HK, WB, and YOKU, which are on an 18-month basis. *Denotes on GS
Conviction List..
资料来源： Company data, Goldman Sachs Global Investment Research.
全球投资研究
36
2014 年 11 月 14 日
中国：金融服务
Impact on financials: Marginalization a risk for midcap banks; Ping An, CMB, ICBC best
placed
Most China banks and financial service providers generally spotted the threats from internet players in 2013, and started to
react and defend their positions, by:

Setting up their own e-commerce websites to sell merchandise from their proved business partners;

Setting up their own P2P platforms to sell securitized loan products as a WMP to compete with other P2P companies, and setting up
money market funds like Yu’e’bao.
However, we believe their initiatives typically have not addressed the key threats from internet players, i.e. payment, consumer
banking, SME banking/O2O, and datamining/big data capabilities. As such, if the current situation continues, we believe banks may gradually
lose their advantage in payment, retail and SME banking business as e-commerce and O2O develop.
Although still very early days in the ascent of internet finance and therefore difficult to predict how the challenge from BAT can be met, we
believe three large-cap financials are best placed to defend their positions due to their strong IT capability and internet finance
strategic focus: Ping An Group, CMB and ICBC.
Those most at risk of marginalization, albeit in the longer-term, are mid-cap banks — specifically BoCom, CNCB, Shanghai Pudong
Development Bank, Huaxia and CEB — on relative weakness in their current retail banking franchise and their focus on SME business, which
we see as the second battleground for internet finance initiatives.
We assess banks’ retail banking franchise and IT capability (Exhibit 33), with ICBC and CMB ranking well, and CNCB, SPDB,
Industrial, CEB, Huaxia, BONJ CQRCB, BOCQ, ranking poorly. We look at:

Retail deposits as a share of total deposits — to show the current customer and funding franchise of banks, and as an indicator of
client stickiness.

Number of credit cards and bank card fees as a share of revenue as evidence of ability to market and attract credit card users.

Number of branches for convenience to retail customers, and as an indicator of client stickiness.
We also look at banks’ SME banking franchises (Exhibit 34): we believe CMB, ICBC, ABC, Minsheng, Industrial Bank are best placed,
with BoCom, CNCB, SPDB, Huaxia, CEB much less so.
全球投资研究
37
2014 年 11 月 14 日
中国：金融服务
Exhibit 33: Potential rising marginalization of mid-cap banks in their retail
business: CNCB, SPDB, Industrial, Huaxia, CEB, BONJ, CQRCB, BOCQ etc.
Retail # of credit Bankcard
Current
deposits
cards
fees as %
consumer
as % of
(mn
of
No of
total
units)
revenue branches franchise
ICBC
47%
95.4
5%
17,550
5
BOC
41%
46.2
4%
11,497
4
CCB
45%
60.2
5%
14,729
4
ABC
58%
48.8
3%
23,583
5
BoCom
32%
33.4
6%
2,767
3
CMB
34%
54.6
7%
1,110
5
CNCB
20%
22.5
6%
1,098
2
SPDB
18%
NA
2%
991
2
Industrial
16%
12.6
4%
892
2
Minsheng
25%
18.7
9%
902
3
PAB
17%
15.2
9%
566
3
Hua Xia
16%
4.2
1%
558
2
BONB
25%
NA
8%
230
3
BOBJ
20%
NA
1%
281
3
BONJ
17%
NA
0%
122
2
CEB
21%
21.7
11%
896
2
CQRCB
73%
0.1
2%
1,772
4
BOCQ
18%
NA
1%
116
2
Ability
to
IT capability/
on-line focus defend
score
score
5
5
3
3.5
4
4
4
3
3
3
5
5
3
2.5
2.5
3
2.5
3
3.5
4
3.5
4
3
2.5
3.5
4
3
3
2
2
2.5
3
1
2.5
2
2
Exhibit 34: Potential increasingly marginalization of mid-cap banks in their
SME business due to BAT’s O2O push: BoCom, CNCB, SPDB, Huaxia, CEB.
Note: 1. Higher scores represent strong capabilities.
2. Red-marked banks indicate those likely to suffer the most severe marginalization.
3. Consumer franchise scoring is based on credit card market share, retail deposit proportion
and bankcard fee contribution. IT scores are based on our assessment of its IT strength and
the quality of their internet banking and mobile banking applications. The score of the ability to
defend is the average the scores of consumer franchise and IT skill/internet focus.
Business stickiness score
SME as %
Branch
ERP/
Total
score
cloud service
Focus
of loans
ICBC
17%
4
4
4
12
BOC
NA
3.5
3
3
9.5
CCB
11%
4
3
3
10
ABC
10%
5
3
3
11
BoCom
NA
3
2
3
8
CMB
NA
3
5
5
13
CNCB
6%
3
3
2
8
SPDB
NA
2.5
3
3
8.5
Industrial
6%
2.5
4
5
11.5
Minsheng
24%
2.5
4
5
11.5
PAB
11%
2
4
5
11
Hua Xia
21%
2
3
3
8
BONB
44%
4
2
5
11
BOBJ
29%
4
2
4
10
BONJ
34%
4
2
4
10
CEB
18%
2
3
3
8
CQRCB
31%
5
1
4
10
11
BOCQ
33%
4
2
5
Note: 1. Higher scores represent strong capabilities.
2. Red-marked banks indicate those likely to suffer the most severe marginalization.
3. Consumer franchise scoring is based on credit card market share, retail deposit proportion
and bankcard fee contribution. IT scores are based on our assessment of its IT strength and
the quality of their internet banking and mobile banking applications. The score of the ability to
defend is the average the scores of consumer franchise and IT skill/internet focus.
资料来源： PBOC, Company data, Gao Hua Research.
资料来源： PBOC, Company data, Gao Hua Research.
全球投资研究
38
2014 年 11 月 14 日
中国：金融服务
Exhibit 35: ICBC was the Top 1 credit card issuer, followed by CCB and CMB
in 2013
88
Exhibit 36: Big banks and CMB are Tier 1 players in terms of credit card
transaction volume in 2013
1,614
No. of credit cards issued by 2013, mn units
Credit card transaction volumn, Rmb bn
1,273
52
1,020
51
44
806
42
940
791
585
583
30
17
21
20
459
528
14
资料来源： Company data
PAB
CEB
CNCB
Minsheng
CMB
BoCom
BOC
ABC
CCB
ICBC
Hua Xia
PAB
CEB
CNCB
Minsheng
CMB
BoCom
BOC
ABC
CCB
ICBC
4
资料来源： Company data
Assessing internet finance strategies of key financial institutions
Ping An Group: comprehensive internet finance strategy, top rank IT and integrated platforms
Among the Chinese financials, we believe Ping An Group was one of the first to determine a comprehensive internet finance strategy, and it
has recently stepped up the pace of implementation. However, we point out that many of its endeavors are still at an early stage of
development and the ability to add value depends on future execution.
Instead of treating the internet as another distribution channel, Ping An’s internet finance seeks to incorporate financial services into
consumers’ everyday life through health, food, housing (home) and transportation (auto) needs. Ping An has set up seven subsidiaries such
as Wanlitong Loyalty Points Program, Lufax, Ping An Haoche (used car trading platform), and Ping An Pay etc. The plan is to utilize these
subsidiaries as ‘platforms’ to access and attract potential customers, maximize contact points with consumers, gather personal
information/perform data mining.
If utilized well, these platforms should help Ping An to understand their target consumers better and offer precision marketing, and eventually
help migrating customers from non-financial services to the consumer financial services that Ping An specializes in. They could also help lock
全球投资研究
39
2014 年 11 月 14 日
中国：金融服务
in customers via cross-selling, loyalty programs and other value-added services, and eventually creating a closed loop or ecosystem around it,
instead of just being the downstream of the value chain.
For example, Ping An Haoche aims to provide an efficient used car trading platform in the nascent used car market in China, utilizing Ping An
P&C’s auto database/pricing expertise. The goal eventually is to migrate customers from such a platform to traditional businesses, and
provide a one-stop financial service associated with used car trading, such as car loans (Ping An Bank) and car insurance (Ping An P&C).
Subsidiary Lufax is a trading platform for non-standard credit assets (NSCAs), providing liquidity in NSCAs for financial institutions via
securitization products like ABS for individuals, corporates and FIs. We believe such a platform might create some a revenue stream
(underwriting fees charged over the borrowers, distribution fees over retail and institutional clients at a rate of 5-20% and commission for
secondary market NSCA deals at a commission rate at 0.5-5%), and help acquire new clients for the group.
At present, it selects borrowers, conduct risk management offline and securitize NSCAs by P2P and sell them to households. As of 1H14,
Lufax attracted 17mn+ registered clients and sold Rmb300bn+ P2Ps. Most of the P2Ps receive a guarantee from Ping An’s subsidiary at
present, although Ping An is trying to educate investors and remove guarantees eventually.
We see these key strengths in Ping An Group’s strategy and capabilities to help it defend against the threat:
•
Development of internet services for consumers and SMEs’ daily life, aiming to acquire customers and data. The services include
used car online trade platform, online housing promotion, healthcare prepaid card, points-for-prizes platform, along with Ping An
Bank’s orange E platform providing B2B commerce and IT solution services to SMEs.
•
Apply “one-account system” to all internet applications and financial services to lock in clients and integrate the multi-dimensional
data of one-account users. Ping An’s one-account system could be viewed as a real-name ecosystem to integrate Ping An’s product
offerings across life insurance, P&C insurance, banking, trust and brokerage business. This could help Ping An undertake crossselling among various businesses and capture multi-dimensional data about clients’ solvency/credit worthiness.
•
Ping An’s IT strengths and the integrated back-office to enable Ping An to consolidate online/off-line data to run data mining for retail
loans, insurance pricing and smart WM service, etc.
•
Better management incentive scheme to develop internet finance than its peers. As a privately owned financial service group, we
believe Ping An’s management are more long-term focused than peers, especially in light of its proposed Employee Share Purchase
Scheme, which could help better align the long-term interests of management/key employees and shareholders. By contrast,
management in many other China financial service companies are state-owned.
There are still areas for improvement, such as attracting customers to use them more by adding more usage scenarios, and improving
user experience and datamining capabilities in its internet finance platforms. We believe that except for Lufax and Wanlitong, its internet
businesses’ user base is still relatively small, due to its late entrance, weaker user experience and absence of sufficient differentiation/traction.
全球投资研究
40
2014 年 11 月 14 日
中国：金融服务
Exhibit 37: Ping An’s internet finance strategy: develop key online financial services for daily life (auto, housing, P2P/WMP, health care, etc) and consolidate
online/off-line data to run data mining for retail loans, insurance pricing and smart WM service.
]
Home & Auto
(Haoche/Haofang)
Internet businesses
Acquire clients/data
B2B commerce
(PAB Orange E) One account
system
Healthcare prepaid card
P2P platform
(Lufax)
Points‐for‐prizes
platform
Payment
Clients/data pass
through funnel to left line
Traditional
financial services
Clients/data pass
through funnel to right line
Share
Ping An Bank
Ping An Insurance
Data mining for retail loans
Data mining for P/C pricing
Share
Ping An
WM
Data mining for smart WM service
资料来源： Company data, iResearch, Analysys, Gao Hua Securities Research
全球投资研究
41
2014 年 11 月 14 日
中国：金融服务
Exhibit 38: Ping An aims to use its 7 internet subsidiaries to access & attract potential customers, maximize contact points with consumers, gather personal
information/perform data mining.
Ping An’s internet finance subsidiaries
Ping An internet finance subsidiaries
Lufax
Core business
Online peer‐to‐peer funding platform Business highlights
Target customers
Rmb 300bn trading volume, 17mn+ registered users (Mar'12 to June'14)
‐ Grass‐root investors; Build a comprehensive and ‐ Individuals/small businesses transparent platform for P2P, with funding needs
B2C, B2B, F2F etc. transactions
Yield 40% above PBOC loan rate, currently (7.5%‐9%)
Principle and interest guaranteed by a Ping An subsidiary for most P2Ps
Ping An Wanlitong
Ping An Pay
Points‐for‐prizes platform e‐Wallet (mobile payment and social network app)
Cash‐equivalent points exchangeable among cooperating platforms Mass internet users
Transfer internet users to Ping An's customers
‐ Mobile payment and social network users
‐ Ping An financial services users
‐ Provide customers with mobile payment option
‐ Strengthen the stickiness of existing customers
60mn+/14mn registered users/MAU, 300 cooperating shopping websites and 200,000 offline retailers
5mn+ registered users; very few payment scenarios linked to it
Lack differentiation vs. Alipay/Wechat
Functions in the future: pay for all financial services by Ping An and its cooperating institutions
Strategic purpose
Free used car information and auto diagnose
Ping An Haoche
Used car trading platform
Auto insurance, loans and maintenance services
Branches in 11 major cities ‐ Used car sellers and buyers Promote auto insurance and ‐ Used car dealers
auto loan businesses
Several thousand cars sold via the platform within 1 year of its launch
Ping An Haofang
Real estate trading platform
Ping An Health
Healthcare + Health insurance network
Ping An Financial Technology
One Account; Ping An tech subsidiaries' incubator
Coupon distribution for property developers and financial service
Current model lack differentiation vs. market leader
Home sellers and buyers
Launched in 2014 and expected to have 26 branches by the end of 2014
Introduced prepaid card for 20,000 drug stores in 35 cities
Core product "Healthcare Expert" under development
Customers with healthcare or Promote health insurance
health insurance needs
Incubator of Ping An’s tech subsidiaries (Haoche, Ping An Pay, Lufax etc.)
One Account is the customer's account for all Ping An services
Established in Aug 2011; 400 employees
Promote P&C insurance and home loan businesses
All Ping An customers
‐ R&D for the Group
‐ Maintain and support internet finance services
资料来源： Company data
全球投资研究
42
2014 年 11 月 14 日
中国：金融服务
CMB: strong in IT service for SMEs, NFC trial, consumer/credit card brand and IT capability
Among China banks, we believe China Merchants Bank has the following strengths in its internet finance development, and in defending its
business from BAT competition:

CMB has one of the best consumer and SME banking expertise and brands to serve mid-to-high end customers.

CMB has a first-tier IT team capable of above-peer data mining for consumers/credit cards/SMEs and excellent PC banking and
mobile banking user experience, evidenced by its mobile banking app and credit card apps (rank Top 2 and 3, respectively among
financial institutions apps with over 25mn MAU (Monthly Active User) in Aug 2014 based on iResearch)

In terms of SME banking, CMB is in the process of collecting SME data online by offering IT/ERP (Enterprise resource planning)
software services to SME clients. It provides free IT services including comprehensive settlement mobile app, corporate email/call
center/ERP software, etc. to 30k+ SMEs.
We view this as an efficient way to bond with SMEs clients, collect their operational information such as sales, inventory, salary payment and
payment information so that CMB can better serve these corporate clients by offering trade finance products, as well as better perform credit
risk management.
Moreover, we believe CMB’s SME ERP service can differentiate it from IT software players in the following ways:

Its SME IT software provides more comprehensive solutions than IT software players. CMB can provide settlement, WMP
investment and other payment services while the latter can’t do due to the lack of bank or third-party payment license.

Its software is free while IT software companies charge fees for some core software. CMB monetize such services by its SME loan
interest income and banking service fees.

It could lock in its SME customer relationships since SME clients are usually unwilling to change their IT software after they become
familiar with it. Corporates prefer stable back-end system, unlike consumers who tend to embrace changing technology fashions. So
far BAT have employed only limited efforts in this market (only Alibaba provides some IT/ERP services to the SMEs in its commerce
platform). Therefore, CMB could still enjoy early-mover advantage in our view.
CMB has differentiated its NFC model from other banks so far, and could be a good basis for O2O payment in the future.
We believe CMB’ NFC model (NFC chip in cellphone) differentiates it from many other banks’ NFC models such as SPDB, as:

It has a slightly simplified money-charge process and hence better user experience.

CMB set up a JV with China Unicom (No.2 telecom player in China) to promote its NFC tool.

Its relatively young customer mix could make such new payment technology more easily accepted.
In contrast, we note SPDB’s NFC model (NFC chip in SIM card) employs a more complicated process than CMB’s, as users have to go to
China Mobile outlets to apply for an NFC-SIM card and sign-off.
全球投资研究
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2014 年 11 月 14 日
中国：金融服务
ICBC: strong retail/SME franchise and IT capability; data mining and marketing needs to improve
Among big banks, we believe ICBC has a better than peer retail and SME banking franchise, IT capability, and management focus in terms of
internet finance initiatives, as:

ICBC has one of the largest retail banking client base, credit card issuance and branch network among big banks. ICBC has a large user
database with 135mn mobile banking users and 95mn credit cards in issuance, all ranking No.1 as of 1H14.

Its IT team also ranks in the top tier among banks, with strong capability to deal with over 50mn transactions per second.

We also believe ICBC’s payment tool “Express Payment” could differentiate it from BAT payment tools, with a good balance between
user experience and security. It attracted 22mn users as of August 2014.
Nevertheless, we believe ICBC needs to improve its datamining capability, and refine its targeted marketing. For instance, ICBC’s credit card
business units have plenty of daily banking card transaction data for ICBC to do datamining (e.g. which customers buy what goods) and then
target their marketing efforts. However, the datamining team of ICBC credit card center is very small, and such efforts so far have remained
limited.
Minsheng Bank: reasonably strong SME/IT capability; trial in direct banking and O2O services
Minsheng Bank has strong SME banking franchise and focus, and strong management incentives to compete with internet finance and
reasonably good IT capability. Its recent moves into direct banking and its trial of O2O services associated with community outlets are
interesting moves, and worth watching.

Minsheng recently launches O2O services associated with community outlets. It provides online localized services like networking,
transportation, payment services and financial products for community residents, while the offline community outlets will support online
product promotion, transportation, a help-desk staffed by real people for elderly people, etc.
We believe such O2O services may have the potential to deliver differentiated local information and payment scenarios by leveraging its
offline outlets. However, the implementation and business model success remains to be closely monitored.

Minsheng is the early-mover into online direct banking to compete with online T+0 money market fund WMPs such as Yu’ebao
Its direct bank sells money market funds and structural deposits, and is going to launch online instant consumer loans secured by clients’
financial assets.
While this helps it retain and attract retail customers, we believe this could raise its funding costs. It may also be difficult for its direct bank
to attract a large number of sustainable customers given the lack of payment scenarios and mobile traffic.
全球投资研究
44
2014 年 11 月 14 日
中国：金融服务
Industrial Bank: potential in developing internet WMP platform, retail/SME franchise weak
We believe Industrial bank may have potential in developing the internet WMP platform, thanks to its strong product innovation capability and
interbank platform. However, we think it may still face marginalization risk in consumer banking and SME banking given its relatively weak
retail/SME banking franchise and focus, and IT capability.
Industrial Bank recently develop an online bank WMP platform named “Bank Bank Platform” (YYPT in Chinese), which sells in-house and
third-party bank WMPs, MMFs and other mutual funds.
The platform’s MMF AUM quickly expanded to Rmb52bn and become comparable to the Rmb62bn AUM of WeChat MMF in 1H14, thanks to
its high return.
Baidu may direct traffic to YYPT based on their strategic cooperation contract.
Bank of Beijing: cooperation with Xiaomi in NFC; value-added marketing services at an early stage
Bank of Beijing (BOBJ) has a reasonably strong retail banking and SME banking franchise in its home market, Beijing City, partly as it
historically mainly serve SMEs in Beijing, and partly as Beijing local government provides access for BOBJ to handle retail customers’
pension and medical care bank accounts.
Despite its relatively weak IT capability, it recently launched several interesting internet finance initiatives by cooperating with Xiaomi
rd
Company (the 3 largest cellphone manufacturer worldwide in 3Q14)

BOBJ launched NFC payment and LBS coupon recommendation in Xiaomi cellphones. Xiaomi is a leading smartphone manufacturer
offering cost-effective smartphones and their inhouse-designed cellphone operating system. Xiaomi also aims to develop its own
ecosystem similar to Apple’s such as APPs, payment tools, etc.
We believe Xiaomi could help BOBJ improve the user experience of its NFC-wallet application and introduce Xiao’mi clients who may
quickly embrace new payment tools.
We believe the LBS coupon application (Location Based Services) could be a value-added service, albeit very new. The success or
otherwise of its further implementation remains to be seen.

BOBJ direct bank model combines offline non-manual outlets offering bankcard issuance, video face-to-face interview and 24/7 services
with online banking services and leverages the experience of ING Direct bank. Its board approved the setting up an individual company
for the direct bank.
CNCB: actively developing mobile code payment and POS loan; strategy unproven
CBCB has been actively developing mobile code payment products and new SME loans named POS loans. However, we believe the
effectiveness of this new strategy remains to be seen especially after CNCB changed its President in May 2014.
We think CNCB is at some long-term risks of being marginalized in consumer banking and SME banking, given its relatively weak franchise,
and that its initiatives may not be sufficient enough to change this.
全球投资研究
45
2014 年 11 月 14 日
中国：金融服务

CNCB launched its code payment app named Cyber Payment in 2013 which supports several offline and online payment scenarios in
both PC and mobile banking. However, we believe its payment scenarios are weaker than BAT and could face regulatory uncertainty
after PBOC halted code payment.

It also launched online POS loan products targeting on small and micro merchants based on the data mining of POS data.
CNCB select POS merchants by data mining POS transaction data bought from UnionPay and then market their SME working capital
loan products to those selected merchants. The selected merchants can apply for loans online within several hours and CNCB will
quickly decide loan approval/quota based on their risk management programs, POS flow, ID and entity data. For post- loan management,
CNCB monitors POS transaction data and updates its risk programs per two months. This POS loan, launched in 2013, earns c.12%
loan yield with less than 1% NPL ratio and about Rmb 900mn loan balance as of 1H14.
We appreciate its innovation and good utilization of data mining for SME loans. However, we note that as the POS data cooperation with
UnionPay is non-exclusive, the entry barrier is low and hence the model has been duplicated by many peers already.
SPDB: early mover in NFC with China Mobile but user experience remains a key issue
SPDB is the NFC payment early mover with over 1.2mn NFC cards issued as of year-end 2013, cooperating with its shareholder China
Mobile. The NFC chip is embedded in China Mobile’s SIM card rather than in the cellphone (as per the ApplePay and CMB models).
However, our tests suggest that its NFC product has more complicated process than CMB/ApplePay, for instance, users have to go to China
Mobile outlets to apply NFC-SIM card and sign-off. As such, we believe SPDB will need to improve its user experience in NFC payment
services.
We also believe its NFC payment service may not be sufficient to offset its weak retail, SME banking franchise, IT capability and
management incentives in enhancing competitiveness as it faces the threat coming from internet players and other banks.
全球投资研究
46
2014 年 11 月 14 日
中国：金融服务
Stock ratings, target prices and risks
We rate Ping An Group H/A shares Buy (Conviction list), with 12 month target prices of HK82.24/Rmb66.62 on 1.36x 14E P/EV. Key risks
for Ping An include: macro hard landing; too rapid expansion of Ping An Bank’s loan book that could hurt Ping An’s credit risk profile and
capital positions.
We rate CMB H/A shares Buy, with 12 month target prices of HK17.1/Rmb13.6 on 1.1x 14E P/B.
Key risks: macro hard landing, CMB’s EPS and asset quality misses.
We rate ICBC H/A shares Buy, with 12 month target prices of HKD5.9/Rmb4.7 on 1.13x 14E P/B.
Key risks: macro hard landing, CMB’s EPS and asset quality misses.
We rate Minsheng H/A shares Neutral/Sell, with 12 month target prices of HK7.17/Rmb5.67 on 0.83x 14E P/B.
Key risks: Minsheng’s EPS and asset quality improvement
We rate Industrial Neutral, with 12 month target prices of Rmb10.9 on 0.88x 14E P/B.
Key risks: macro hard landing, severe capital and provision requirement on its loan securitization books; Industrial’s EPS and asset quality
misses and beat
We rate BOBJ Neutral, with 12 month target prices of Rmb6.67 on 0.79 14E P/B.
Key risks: macro hard landing, BOBJ’s EPS and asset quality beat or misses
We rate CNCB H/A shares Neutral/Sell, with 12 month target prices of 5.0/Rmb3.9 on 0.69x 14E P/B.
Key risks: macro hard landing, CNCB’s EPS and asset quality beat or misses
We rate SPDB Neutral, with 12 month target prices of Rmb10.4 on 0.81 14E P/B.
Key risks: macro hard landing, BOBJ’s EPS and asset quality beat or misses
全球投资研究
47
2014 年 11 月 14 日
中国：金融服务
信息披露附录
申明
我们，马宁、 吴双、 李南, CFA，在此申明，本报告所表述的所有观点准确反映了我们对上述公司或其证券的个人看法。此外，我们的薪金的任何部分不曾与，不与，也将不会与本报告中的具体推荐意见或观点直
接或间接相关。
投资摘要
投资摘要部分通过将一只股票的主要指标与其行业和市场相比较来评价该股的投资环境。所描述的四个主要指标包括增长、回报、估值倍数和波动性。增长、回报和估值倍数都是运用数种方法综合计算而成，以确
定该股在地区研究行业内所处的百分位排名。
每项指标的准确计算方式可能随着财务年度、行业和所属地区的不同而有所变化，但标准方法如下：
增长是下一年预测与当前年度预测的综合比较，如每股盈利、EBITDA 和收入等。 回报是各项资本回报指标一年预测的加总，如 CROCI、平均运用资本回报率和净资产回报率。 估值倍数根据一年预期估值比率综
合计算，如市盈率、股息收益率、EV/FCF、EV/EBITDA、EV/DACF、市净率。 波动性根据 12 个月的历史波动性计算并经股息调整。
Quantum
Quantum 是提供具体财务报表数据历史、预测和比率的高盛专有数据库，它可以用于对单一公司的深入分析，或在不同行业和市场的公司之间进行比较。
GS SUSTAIN
GS SUSTAIN 是侧重于长期做多建议的相对稳定的全球投资策略。GS SUSTAIN 关注名单涵盖了我们认为相对于全球同业具有持续竞争优势和出色的资本回报、因而有望在长期内表现出色的行业领军企业。我们
对领军企业的筛选基于对以下三方面的量化分析：现金投资的现金回报、行业地位和管理水平（公司管理层对行业面临的环境、社会和企业治理方面管理的有效性）。
信息披露
相关的股票研究范围
马宁：中国金融行业。李南, CFA：中国券商、中国金融行业。
中国券商：银河证券、招商证券、中信证券(A)、中信证券(H)、光大证券、海通证券(A)、海通证券(H)。
中国金融行业：农业银行(A)、农业银行(H)、北京银行、中国银行(A)、中国银行(H)、重庆银行、交通银行(A)、交通银行(H)、南京银行、宁波银行、中国信达、中信银行(A)、中信银行(H)、建设银行(A)、建设银行
(H)、光大银行、中国人寿(A)、中国人寿(H)、招商银行(A)、招商银行(H)、民生银行(A)、民生银行(H)、中国太保(A)、中国太保(H)、中国太平、重庆农村商业银行、远东宏信、华夏银行、工商银行(A)、工商银行
(H)、兴业银行、新华保险(A)、新华保险(H)、人保集团、人保财险、平安银行、中国平安(A)、中国平安(H)、浦发银行。
与公司有关的法定披露
以下信息披露了高盛高华证券有限责任公司（“高盛高华”）与北京高华证券有限责任公司（“高华证券”）投资研究部所研究的并在本研究报告中提及的公司之间的关系。
高盛高华在过去 12 个月中曾从下述公司获得投资银行服务报酬： 农业银行(A) (Rmb2.64)、农业银行(H) (HK$3.60)、中国银行(A) (Rmb3.10)、中国银行(H) (HK$3.86)、中信银行(A) (Rmb5.15)、中信银行(H)
(HK$5.49)、招商银行(H) (HK$14.92)、工商银行(A) (Rmb3.76)、工商银行(H) (HK$5.11)、平安银行 (Rmb11.05)
高盛高华在今后 3 个月中预计将从下述公司获得或寻求获得投资银行服务报酬： 农业银行(A) (Rmb2.64)、农业银行(H) (HK$3.60)、北京银行 (Rmb8.39)、中国银行(A) (Rmb3.10)、中国银行(H) (HK$3.86)、交通银
行(A) (Rmb4.64)、交通银行(H) (HK$5.97)、中信银行(A) (Rmb5.15)、中信银行(H) (HK$5.49)、光大银行 (Rmb3.06)、招商银行(H) (HK$14.92)、民生银行(A) (Rmb6.83)、民生银行(H) (HK$8.04)、工商银行(A)
(Rmb3.76)、工商银行(H) (HK$5.11)、平安银行 (Rmb11.05)、浦发银行 (Rmb10.94)
高盛高华在过去 12 个月中与下述公司存在投资银行客户关系： 农业银行(A) (Rmb2.64)、农业银行(H) (HK$3.60)、北京银行 (Rmb8.39)、中国银行(A) (Rmb3.10)、中国银行(H) (HK$3.86)、交通银行(A)
(Rmb4.64)、交通银行(H) (HK$5.97)、中信银行(A) (Rmb5.15)、中信银行(H) (HK$5.49)、招商银行(H) (HK$14.92)、工商银行(A) (Rmb3.76)、工商银行(H) (HK$5.11)、平安银行 (Rmb11.05)、浦发银行 (Rmb10.94)
没有对下述公司的具体信息披露： 中国平安(A) (Rmb44.30)、中国平安(H) (HK$60.55)
公司评级、研究行业及评级和相关定义
买入、中性、卖出：分析师建议将评为买入或卖出的股票纳入地区投资名单。一只股票在投资名单中评为买入或卖出由其相对于所属研究行业的潜在回报决定。任何未获得买入或卖出评级的股票均被视为中性评
级。每个地区投资评估委员会根据 25-35%的股票评级为买入、10-15%的股票评级为卖出的全球指导原则来管理该地区的投资名单；但是，在某一特定行业买入和卖出评级的分布可能根据地区投资评估委员会的决
定而有所不同。地区强力买入或卖出名单是以潜在回报规模或实现回报的可能性为主要依据的投资建议。
潜在回报：代表当前股价与一定时间范围内预测目标价格之差。分析师被要求对研究范围内的所有股票给出目标价格。潜在回报、目标价格及相关时间范围在每份加入投资名单或重申维持在投资名单的研究报告中
都有注明。
全球投资研究
48
2014 年 11 月 14 日
中国：金融服务
研究行业及评级：分析师给出下列评级中的其中一项代表其根据行业历史基本面及／或估值对研究对象的投资前景的看法。 具吸引力(A)：未来 12 个月内投资前景优于研究范围的历史基本面及／或估值。 中性(N)：
未来 12 个月内投资前景相对研究范围的历史基本面及／或估值持平。 谨慎(C)：未来 12 个月内投资前景劣于研究范围的历史基本面及／或估值。
暂无评级(NR)：在高盛高华于涉及该公司的一项合并交易或战略性交易中担任咨询顾问时并在某些其他情况下，投资评级和目标价格已经根据高华证券的政策予以除去。 暂停评级(RS)：由于缺乏足够的基础去确定
投资评级或价格目标，或在发表报告方面存在法律、监管或政策的限制，我们已经暂停对这种股票给予投资评级和价格目标。此前对这种股票作出的投资评级和价格目标(如有的话)将不再有效，因此投资者不应依
赖该等资料。 暂停研究(CS)：我们已经暂停对该公司的研究。 没有研究(NC)：我们没有对该公司进行研究。 不存在或不适用(NA)：此资料不存在或不适用。 无意义(NM)：此资料无意义，因此不包括在报告内。
一般披露
本报告在中国由高华证券分发。高华证券具备证券投资咨询业务资格。
本研究报告仅供我们的客户使用。本研究报告是基于我们认为可靠的目前已公开的信息，但我们不保证该信息的准确性和完整性，客户也不应该依赖该信息是准确和完整的。我们会适时地更新我们的研究，但各种
规定可能会阻止我们这样做。除了一些定期出版的行业报告之外，绝大多数报告是在分析师认为适当的时候不定期地出版。
高盛高华为高华证券的关联机构，从事投资银行业务。高华证券、高盛高华及它们的关联机构与本报告中涉及的大部分公司保持着投资银行业务和其它业务关系。
我们的销售人员、交易员和其它专业人员可能会向我们的客户及我们的自营交易部提供与本研究报告中的观点截然相反的口头或书面市场评论或交易策略。我们的自营交易部和投资业务部可能会做出与本报告的建
议或表达的意见不一致的投资决策。
本报告中署名的分析师可能已经与包括高华证券销售人员和交易员在内的我们的客户讨论，或在本报告中讨论交易策略，其中提及可能会对本报告讨论的证券市场价格产生短期影响的推动因素或事件，该影响在方
向上可能与分析师发布的股票目标价格相反。任何此类交易策略都区别于且不影响分析师对于该股的基本评级，此类评级反映了某只股票相对于报告中描述的研究范围内股票的回报潜力。
高华证券及其关联机构、高级职员、董事和雇员，不包括股票分析师和信贷分析师，将不时地对本研究报告所涉及的证券或衍生工具持有多头或空头头寸，担任上述证券或衍生工具的交易对手，或买卖上述证券或
衍生工具。
在高盛组织的会议上的第三方演讲嘉宾（包括高华证券或高盛其它部门人员）的观点不一定反映全球投资研究部的观点，也并非高华证券或高盛的正式观点。
在任何要约出售股票或征求购买股票要约的行为为非法的地区，本报告不构成该等出售要约或征求购买要约。本报告不构成个人投资建议，也没有考虑到个别客户特殊的投资目标、财务状况或需求。客户应考虑本
报告中的任何意见或建议是否符合其特定状况，以及(若有必要)寻求专家的意见，包括税务意见。本报告中提及的投资价格和价值以及这些投资带来的收入可能会波动。过去的表现并不代表未来的表现，未来的回
报也无法保证，投资者可能会损失本金。
某些交易，包括牵涉期货、期权和其它衍生工具的交易，有很大的风险，因此并不适合所有投资者。外汇汇率波动有可能对某些投资的价值或价格或来自这一投资的收入产生不良影响。
投资者可以向高华销售代表取得或通过 http://www.theocc.com/about/publications/character-risks.jsp 取得当前的期权披露文件。对于包含多重期权买卖的期权策略结构产品，例如，期权差价结构产品，其交易成本
可能较高。与交易相关的文件将根据要求提供。
所有研究报告均以电子出版物的形式刊登在高华客户网上并向所有客户同步提供。高华未授权任何第三方整合者转发其研究报告。有关某特定证券的研究报告、模型或其它数据，请联络您的销售代表。
北京高华证券有限责任公司版权所有 © 2014 年
未经北京高华证券有限责任公司事先书面同意，本材料的任何部分均不得(i)以任何方式制作任何形式的拷贝、复印件或复制品，或(ii)再次分发。
全球投资研究
49