Chinese Green Finance Gets a Boost from Big Data

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Chinese banks are making increasing use of big data and other forms of fintech to drive growth in green finance and ESG lending.

Green finance was flagged as a key policy priority in September 2020, when Beijing unveiled the twin carbon targets of achieving peak carbon by 2030 and carbon neutrality by 2060. At the start of 2021 the People’s Bank of China announced the launch of concerted green finance drive, using moral suasion to push domestic lenders to step up lending to key areas.

At the 2022 Two Sessions meeting of Chinese congress in March, multiple representatives hailing from banks and other financial institutions took part in discussions on innovation in green finance products and services. These institutions included the Postal Savings Bank of China, China Merchants Bank, Shanghai Pudong Development Bank, Industrial Bank Co., Huaxia Bank and Bank of Beijing.

According to an opinion piece published by Cebnet.com.cn, fintech, and big data in particular, have emerged as key tools employed by Chinese banks to expedite growth in green finance.

“In the process of driving green finance, big data has already emerged as the ‘bullseye’ for major financial institutions to invest their efforts,” writes Cebnet editor Fang Jie (方杰).

“Big data centres serve as key infrastructure for the financial sector, and play an extremely important role in the wave of rapid development of fintech and digital transformation.

“With the twin carbon targets, the financial sector is also actively exploring the creation of high-efficiency, secure and green big data centres. Big data centres can use big data and artificial intelligence to increase the innovation capability of financial institutions, and form highly digitised carbon financial product systems.”

Fang highlights the role of big data when it comes to credit assessments and risk control in relation to ESG lending.

“When it comes to risk management, digital technology can replace numerous credit risk management methods such as survey reports and automatic risk warnings,” he writes.

“With technologies such as big data and artificial intelligence, information in relation to green financial services targets can be subject to loan risk identification, comparisons and judgements using risk management systems, to determine whether or not they satisfy green project requirements.”