Market Summary

The estimated size of China’s leading financial information services providers’ revenues for 2019 is US$1,865 Million (CN¥12,948 Million), indicating an overall market size in excess of US$2,000 Million

This is based upon known reported figures for listed companies and estimates for the largest unlisted companies including Bloomberg and Refinitiv.

This makes China potentially the largest market for financial information services outside the United States, United Kingdom, European Union, and Japan, albeit with a larger retail component

The market data vendors act as a bellwether for the financial industry as a whole, from the earnings data sources make from information services to the amount financial institutions spend on data they need for their operations.

This paper provides an analysis of the state of the market data vendors in China, which vendors are enjoying success, and the issues they need to address to develop their businesses in an environment which is undergoing significant transformation due to a range of factors:

Observations

  1. The China market for financial data is larger as many smaller players have been omitted, please see above
  2. Unlike other Asian markets, China vendors dominate, whereas the market leaders in other territories regionally are Bloomberg and Refinitiv (including Japan)
  3. Importantly there are no obvious cyclical trends across the entire market indicating individual corporate strategies play a large role in success

REVENUES PERFORMANCE ANALYSIS

The US$1,865 Million, (CN¥12,948 Million) revenues is based upon known reported figures for listed companies, plus estimates for unlisted companies, Bloomberg, and Refinitiv in China.

For these 6 companies combined the revenue growth from 2010 to 2019 was 279%, with a range from -24% for China Finance Online to 1,183% for Beijing Compass.

Key Points:

  1. There are fewer specialist ‘market data vendors’ competing, notably DZH and Wind Information, as vendors have adopted strategies to compete by offering break-out value-added services,
  2. Successful exponents are EastMoney and Hexin Flush which first developed new-media then built flow through retail brokerage businesses around their data services
  3. Hundsen Technology is primarily a Technology business that has acquired market data businesses designed to feed data towards their IT products and services

This makes direct comparative analysis of the businesses difficult, however, in the datasphere each company is competing with the others aggressively for similar client bases

REVENUES ANALYSIS

The revenues listed are for all business activities which can include trading, news, index creation, technology, and other services. The unlisted estimates are indicative as these companies do not make their data available publicly or not in detail. The number of large competing businesses is indicative of the competitive nature of the China market. Bloomberg and Refinitiv are strong in the professional space, but lack client diversity

Observations

  1. In comparison with the top 6 global vendors whose combined revenues for 2019 totalled US$31,747 Million, (CN¥220,354 Million) for all businesses
  2. The average revenue of the top 6 global vendors was US$5,291 Million, (CN¥36,726 Million)
  3. The top 6 global vendors are Bloomberg, Factset, ICE Data, Refinitiv, S&P Global

MARKET CAPITALISATION

One way to judge one’s value is to have others measure it for you. In financial markets that measure is market capitalisation.

It is noticeable that only China Finance Online is listed on the US NASDAQ exchange whereas the other 5 are all traded locally on either the Shanghai or Shenzhen Stock Exchanges. This does have an impact on their overall valuation, however CFO is an obvious under-achiever in revenue generation as well

Observations:

  1. The total market capitalisation of the six Chinese listed vendors is US$44,300 Million, (CN¥307,487 Million) as at 07/05/2020
  2. The average market cap is US$7,383 Million, (CN¥51,248 Million)
  3. This compares to the estimated total market capitalisation of the 6 largest global market data vendors of US$178,275 Million, (CN¥1,237,409 Million) with an average of US$29,713 Million, (CN¥206,235 Million)

MARKET CAPITALISATION/PRICE-SALES RATIO

What the Sales/Price ratio indicates is the China vendors are valued far higher on a revenue basis than the big global vendors. Also that investors prefer businesses with a more diverse portfolio of services than vanilla market data vendors

Observations: 1.The average Price/Sales Ratio (Market Cap divided by Revenue) for the 6 China vendors is 35.3 2.The average Price/Sales Ratio (Market Cap divided by Revenue) for the 6 leading global vendors is 6.18

Note: Beijing Compass switched its listing from Peking based NEEQ market to the Shenzhen Stock Exchange which certainly improved its attractiveness and accessibility to investors

SUMMARY

In China both market data vendors and data sources, like exchanges, are too fixated upon physically counting the numbers of users rather than implementing fee structures formulated around the principle of how data is consumed and then put to work by their clients, the Financial Institutions, on an enterprise basis. As Western organisations have discovered this leads to data saturation and reduces revenue opportunities

However to bring China’s market data vendors and exchanges forward requires a two-pronged strategy, the first relates to business structure, and the second to the principle that not all clients can be treated identically while having to understand how to track data and workflows 

To summarise:

  1. There are opportunities for China’s market data vendors, and by extension the exchanges and other data sources to expand their client footprint and enter into, then exploit, new markets
  2. However, for these companies to achieve revenue success in the next step of their business development will require adoption of new strategic approaches designed to align with how different types of clients consume data in different ways. This must be backed by a business structure that is flexible enough to accommodate dynamic change in data utilisation variables 

Keiren Harris 16/06/2020

www.datacompliancellc.com

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