A decade of rapid debt accumulation has allowed bad assets and excessive risk to build up in China’s financial system. These debts have now reached such an extent that, if left unchecked, they could threaten both financial and economic stability. In response, Beijing has launched a sweeping—albeit little understood—campaign to clean up the financial system.
But unlike a similar campaign Beijing launched at the turn of the century—the last time the financial system needed cleaning up—this time there are no top-down bailouts or recapitalizations. The process is still at an early stage, but one thing is already clear: the cleanup isn’t proceeding from some pre-written, tried-and-true playbook. In some cases, Beijing is borrowing techniques used elsewhere and adapting them to China’s circumstances; in others, it is experimenting with entirely new approaches; and while some efforts are being shaped by authorities, many are being driven by bottom-up innovation.
The result is a unique and fast-evolving ecosystem of financial institutions, products, and regulations that will have a huge impact on whether China manages its financial risks in such a way that allows it to transition to a more sustainable economic model while minimizing the turmoil that could accompany such a monumental task. However, thus far this ecosystem has received relatively little attention. The Cleanup intends to remedy that.
The Cleanup contains two main features: data dashboards and analysis.
The analysis aims to explore and explain aspects of the changes now underway in the Chinese financial sector. In the main, the focus of this analysis is topics that are not generally covered elsewhere. The intent is to contribute a more nuanced understanding of the dynamics of financial reform in China today. New analysis will be published regularly.
The data section includes dashboards on such topics as asset management corporations and bad loans disposals that explain visually some of the trends at play in the cleanup of the financial system and explicated in the analysis. New dashboards will be added in future but data for existing dashboards will be updated whenever it becomes available.
Data and Methodology
Broadly speaking, the data utilized by The Cleanup is drawn from the earnings report, bond prospectuses, and credit ratings reports of Chinese financial institutions. These are sourced and cited in the products on The Cleanup wherever numbers appear. Both the analysis and dashboard features of The Cleanup also rely on corporate records disclosed by the State Administration of Industry and Commerce (SAIC), company and asset information disclosed in auction filings posted on financial asset exchanges, statistics from the China Banking Regulatory Commission (CBRC) and People’s Bank of China (PBOC), and open source primary resources from China’s financial institutions and official government statements.
Although many of the dashboards should be self-explanatory, some require further explanation, which we provide below:
DASHBOARD 1: BAD LOANS
Charge-offs at Chinese vs. US banks
Disposals of bad loans by China’s banks are rising, but it is difficult to put that into context. After all, how do disposals in China compare with disposal levels in other countries? This chart compares the volume of loans being disposed of by Chinese banks with those at US banks. To do this, we first took data published by the US Federal Reserve on US bad loan disposals, then created a comparable dataset for Chinese banks.
The Fed data in question relates to charge-offs at banks with more than $20 billion worth of total assets. Charge-offs refer to the volume of loans written-off by banks (or, to use the more precise accounting formulation, the value of loans charged against the loss reserve) in a given period, less recoveries that banks managed to make on loans written off in earlier periods.
Meanwhile, although the US banking system has hundreds of banks, the vast majority of banking system assets are concentrated in a much smaller group of institutions. Hence, it is possible to get a good overview of the US banking system by limiting the sample to only the largest banks—for instance, to those with more than $20 billion worth of total assets. At the end of 2016, there were 66 banks with more than $20 billion in total assets, which together accounted for 83.8% of total banking system assets.
In recreating the Fed charge-off data for the Chinese banking system, we first determined what subset of Chinese banks represented a comparable sample size to US banks with more than $20 billion worth of assets. Between 2010 and 2016, US banks with assets more than $20 billion accounted for between 81.5% and 83.8% of total US banking assets. Working from a list of China’s 100 biggest banks complied by China Banking magazine, published by the government-backed banking industry association, we compiled data on total assets of the 30 biggest Chinese banks between 2010 and 2016. Comparing those figures to annual commercial banking data published by the China Banking Regulatory Commission (CBRC), we determined that Chinese banks with more than 700 billion yuan ($120 billion) worth of total assets in any given year accounted for a comparable proportion of Chinese commercial bank assets as US banks with more than $20 billion worth of total assets did in the United States. In 2011, Chinese banks with 700 billion yuan worth of total assets accounted for 84.7% of total commercial banking assets, a ratio that declined to 81.33% in 2016. The 2010 figure is slightly less representative, with banks with more than 700 billion yuan in assets accounting for 78% of the total.
We then calculated annual charge-offs at Chinese banks with more than 700 billion yuan worth of assets by adding write-offs to transfers out (that is, bad loans sold to third parties, a category that is often combined with write-offs on Chinese banks’ balance sheets), and subtracting recoveries on previously written-off loans.
The 2016 data for Chinese banks includes 28 banks: Industrial and Commercial Bank of China (ICBC), China Construction Bank (CCB), Agricultural Bank of China (ABC), Bank of China (BOC), Bank of Communications (BOCOM), China Industrial Bank, China Merchants Bank, China CITIC Bank, China Minsheng Bank, Shanghai Pudong Development Bank, Everbright Bank, Ping An Bank, Huaxia Bank, Bank of Beijing, Guangfa Bank, Bank of Shanghai, Bank of Jiangsu, Zheshang Bank, Evergrowing Bank, Bank of Nanjing, Shengjing Bank, Bank of Ningbo, Bank of Bohai, Chongqing Rural Commercial Bank, Huishang Bank, Beijing Rural Commercial Bank, Bank of Hangzhou, and Shanghai Rural Commercial Bank.
Finally, given that different countries have different rules and incentives that shapes banks’ decisions to dispose of bad loans, the US and Chinese data displayed here isn’t a perfect comparison. However, it is useful in showing the relative trends in both countries.
DASHBOARD 2: PROVINCIAL NPLS
Commercial Bank NPLs Versus Total Banking System NPLs
China’s financial regulators publish two different nonperforming loan (NPL) ratios: one for commercial banks and another for the entire banking system. The more commonly used measure is the one for commercial banks, which the CBRC updates quarterly. That includes the big five banks (also known as the state-owned commercial banks, a group that includes ICBC, CCB, BOC, ABC, and BOCOM), the joint stock banks, the city commercial banks, the rural commercial banks, and foreign banks. The total banking system NPL metric includes the commercial banks listed above, as well as policy banks, trust companies, finance companies owned by non-financial conglomerates, the postal savings banks, rural credit cooperatives, and other non-bank rural financial institutions.
The charts demonstrate a significant difference between the two measures, both at a national level and for some Chinese provinces. While the commercial bank NPL figure is more commonly used, the total banking system figure may grow in significance, particularly as Beijing’s efforts to clean up the financial system stretches beyond the commercial banks. Moreover, it appears to be an indicator that the regulators themselves are watching. When CBRC Chairman Guo Shuqing disclosed data on bad loan disposals in 2017 (for analysis, see here), his benchmark was total banking system loans, not commercial banks only.
The CBRC discloses in its annual reports a figure for the national year-end total banking system NPL ratio, and total outstanding NPLs. The CBRC also discloses in its annual report provincial NPL ratios and outstanding NPL levels for commercial banks. The PBOC provincial branches disclose NPL ratios and outstanding NPLs for the total banking system in their annual “financial operations reports.” Some CBRC provincial branches also disclose the data on their websites. However, the data is inconsistent. Some provinces do not disclose total outstanding NPLs, and some do not disclose the provincial NPL ratio.
Bank Disposals by Province
Currently most provinces do not publish data on annual write-offs by their banks. Those that do only started doing so fairly recently. Based on MacroPolo’s research, only five provinces—Jiangsu, Zhejiang, Shandong, Henan, and Inner Mongolia—have published more than one year’s worth of write-off data as of The Cleanup’s launch. The local branch of the People’s Bank of China (PBOC) (China’s central bank) in those provinces publishes the data in annual “finance operations” reports that are posted on the State Council website, and Chinawealth.cn, a website run by the China Central Depository and Clearing Co.
We have chosen to compare provincial write-offs against total banking system NPLs (explained above) because that is the measure of NPLs the PBOC branches disclose in their financial operations reports. Usually disposals data is disclosed in the paragraph or even the same sentence as the total banking system NPL data, implying the disposals data takes into account more than just commercial banks.
DASHBOARD 3: Asset Management Companies
Cinda and Huarong—Distressed Assets by Type of Borrower
While Cinda and Huarong, two of the four main Chinese asset management companies, traditionally acquired only bank NPLs, in recent years their operations have increasingly been dominated by NPLs acquired from “non-financial entities.” That refers to the bad debts that have accumulated between companies. Companies routinely sell goods and services to each other on credit—in other words, rather than pay cash up front, the seller will allow the purchaser to pay at some predetermined point in the future. However, sometimes the purchaser fails to pay. These are the sorts of NPLs that Cinda and Huarong acquire from “non-financial entities.”
This chart shows Cinda and Huarong’s purchase of NPLs from “non-financial entities” compared with those acquired from banks, and from non-bank financial institutions.
Cinda and Huarong—Newly Acquired NPLs by Bank Type
The data presented here does not represent all bank NPLs acquired by Cinda and Huarong. However, the category of data excluded typically represent less than 2% of the two AMCs’ annual bank NPL acquisitions. Cinda and Huarong provide data on four categories of banks from which they acquire NPLs: large state-owned commercial banks (ICBC, CCB, BOC, ABC, and BOCOM), joint stock banks, city and rural commercial banks, and “other banks” (which includes policy banks, foreign banks, and the postal savings bank). Meanwhile, the CBRC provides quarterly NPL data on large commercial banks, joint stock banks, city commercial bank, rural commercial banks, and foreign banks—but not policy banks or the postal savings bank. Hence, we have excluded the AMCs’ “other banks” category of NPLs because the CBRC itself does not have a comparable category. Nonetheless, the exclusion of that data does not distort the trend we are showcasing here, whicn is that the distribution of the AMCs’ purchases of bank NPLs differs significantly from where NPLs are concentrated in China’s commercial banking system.
Local AMC Ownership
To chart the ownership of China’s local AMCs, we started by finding lists of local AMCs compiled by Chinese media. We then looked for confirmation that those companies listed by local media had in fact been granted AMC status by the CBRC by looking for notices that confirmed their status on government websites, and in stories carried by the People’s Daily, Xinhua, and other official media. We then built a profile of the AMCs’ ownership structures based on shareholder data from records of the State Administration for Industry and Commerce (SAIC). In the case of Shandong Financial Asset Co. and Suzhou Asset Management Co., SAIC data was insufficient, however large shareholders in both companies disclosed the companies’ ownership structure in public filings. We subsequently sorted the AMCs into five categories:
Wholly state-owned: companies where all the shareholders are either wholly-owned or majority-owned by local government departments and agencies.
Majority controlled by local authorities: companies where shareholders that are wholly-owned or majority-owned by local government departments and agencies have contributed more than 50%, but less than 100%, of registered capital. In some cases, owners include a mix of local government agencies and other government agencies from different areas within a province.
Majority owned by private interests: companies where shareholders that are either wholly-owned or majority-owned by non-state shareholders have contributed more than 50% of registered capital. It is important to note that majority ownership does not necessarily denote control. In some cases, there may be multiple non-state shareholders that together own more than half of a company. But their disparate interests may mean that they do not constitute an effective ownership bloc, which means that real authority may still lie with a large—albeit minority—state shareholder.
Controlled by state-owned financial institutions: a number of financial institutions have taken minority interests in local AMCs, but this chart only identifies those companies in which financial institutions are responsible for more than 50% of registered capital, which they contributed either directly or through subsidiaries.
Publicly traded companies: although a number of publicly traded companies hold minority interests in local AMCs, publicly traded firms have contributed the majority of registered capital—either directly, or through subsidiaries—in only two instances.
Insufficient data: in one instance, neither SAIC records nor other official sources provided sufficient information to determine the nature of the dominant shareholding group.
Our list of local AMCs is not static. We expect that more local AMCs will be approved in coming years. We will strive to update this chart with new information whenever possible. Our list is also significantly shorter than those reported in the Chinese media. The Chinese press has reported that a number of companies have been tapped to become an AMC by local authorities, but as of March 5, they had not been approved by the CBRC.
Please note that English names were not available for many of the local AMCs. The names we’ve used are based on our own translations.
Local AMCs’ NPL Acquisitions
Very little information is disclosed by local AMCs about the volume and nature of the NPLs they acquire. The data disclosed here is aggregate, year-end data disclosed either by the AMCs themselves, their parent company, or a credit rating agency. While some AMCs—most notably Zheshang Asset Management Co., Jiangsu Asset Management Co., and Fujian Mintou Asset Management Co.—post regular statements on their websites about NPLs they have acquired, those statements do not necessarily provide a full accounting of what the AMC has acquired. AMCs are required by government regulations to disclose publicly details pertaining to any NPLs they acquire, however there are exemptions for loans deemed sensitive and strategic that make the website disclosures incomplete.
Users should note that the data included in this chart refers primarily but not exclusively to loans acquired from banks. For example, the data for Guangdong Finance Asset Management includes NPLs acquired from non-bank financial institutions, according to the company’s credit rating reports. Meanwhile, Zheshang’s data includes loans acquired from the big four AMCs (i.e. Cinda, Huarong, China Orient, and Great Wall), according to disclosures on Zheshang’s website.
Finally, the Guangdong, Liaoning, and Shanghai data explicitly refers to bad loans acquired in batches, not individual loans. The Zheshang data does not specify. However, nowhere in their credit rating reports or prospectuses is there mention of those AMCs acquiring individual NPLs, so it is likely fair to assume that the data presented here fairly represent total NPLs acquired by the local AMCs. The exception is data for Anhui Goho Asset Management. In statements on the company’s website, Goho says that in addition to commercial bank NPLs, it also acquires NPLs directly from companies.
The acquisitions data is compared to total outstanding NPLs at commercial banks at year-end. We have chosen to use commercial bank NPL levels rather than total banking system NPLs (see here for an explanation of the difference because, in the case of Anhui and Guangdong, data on total outstanding bank system NPLs is not available. Moreover, based on the available data, the local AMCs we have included acquire almost all of their NPLs from commercial banks.
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