Best Transaction Bank for Technology 2020
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AwardsBest Transaction Banks in China

Best Transaction Bank for Technology 2020

China Merchants Bank

Hou Weirong, CMB.jpg
Hou Weirong, China Merchants Bank

All Chinese banks are keen to adopt financial technologies, but none has taken the mission to heart as much as China Merchants Bank. Since about 2014, executives at the bank have repeatedly said that the bank’s goal is to become a financial technology bank. Last year, the bank put that promise on paper. In October, the bank amended its Articles of Association to include specific amounts of fintech spending – the first Chinese commercial bank to do such a thing.

The bank promised that its overall budget for investing in fintech in any given year would not be less than 3.5% of the bank’s operating income in the previous year.

That seems a reasonable target.

In 2019, China Merchants Bank spent Rmb9.36 billion ($1.3 billion) on information technology investment, a 44% increase from the year before. That number was equivalent to 3.72% of its net operating income in 2019 (and 3.8% of the operating income for 2018).

In 2019, Hou Weirong, general manager of the transaction banking department, led the bank’s move to enhance the ‘Cloud Bill’, a unified payment and settlement platform that allows online and offline transaction verification and identification. The volume of transactions conducted on the platform reached Rmb287.3 billion in 2019.

CMB also leveraged technology in online financing services for small and medium-sized enterprises (SMEs). It added the self-service management and verification functions to its ‘Invoice Cloud’ platform in April last year.

By the end of 2019, the bank had provided services to 2,131 corporate customers, and checked and verified funds amounting to Rmb126 billion, according to the bank’s annual report.

CMB continued to leverage technology to control risks. It built a smart pre-warning system last year based on machine learning algorithms for corporate customers. By the end of 2019, the accuracy ratio of the system identifying corporate customers with potential risks reached 75%.

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