Digital Financial Inclusion and the Tech Giants

The concept of financial inclusion (puhui jinrong 普惠金融) was initially introduced by the United Nations during the International Year of Microcredit in 2005 and was officially recognized by Chinese state authorities in 2015.Footnote ⁶ The practice of financial inclusion varies across different countries; in China, it is more about technology-facilitated financialization initiated by the state, promoted by fintech companies and popularized by small investors.Footnote ⁷ Digital finance has opened up a new market beyond the traditional bank-dominated financial system and has rapidly transformed China's financial landscape.Footnote ⁸ To date, many social studies of China's financial inclusion and digitalization of credit evaluation focus on the big techs, such as the use of Alipay (a mobile payment platform introduced by Alibaba) and Sesame Credit (a consumer credit reporting system).Footnote ⁹ In China, digital financial development has been successful in the areas of mobile payment, online lending, digital insurance and online investment.Footnote ¹⁰ Studies worldwide indicate that applying digital technologies such as artificial intelligence, cloud computing and big data technology in financial institutions may improve risk management efficiency and enable lenders to include more users such as rural and low-income households.Footnote ¹¹ Bigtech credit, meaning digital lending by tech companies, focuses on big data instead of collateral and thus can significantly enhance financial stability and financial inclusion.Footnote ¹² Alibaba introduced Sesame Enterprise Credit for MSMEs in 2017, and its “Enterprise Sesame Strength Mark” service officially launched in 2023.Footnote ¹³ Still, loans approved through this innovative credit risk assessment model are usually in small amounts and for short durations.

Scholars have emphasized the role of political considerations in shaping China's financial landscape.Footnote ¹⁴ Key insights from China's fintech accomplishments include a flexible regulatory framework during the initial phase of financial innovation, strong political support and the effective oversight of tech companies to maintain competitive conditions.Footnote ¹⁵ However, the growth of fintech companies has raised privacy and regulatory concerns.Footnote ¹⁶ Since 2015, the Chinese government has been focusing on bolstering competition within the fintech industry while also seeking to manage the market dominance of tech giants.Footnote ¹⁷ This involves tightening controls over fintech business, merging financial credit scores with broader social credit scores and extending direct influence into the organizational structures of key players in the digital economy.Footnote ¹⁸ Rather than evaluating the effectiveness of fintech, this research focuses on how digital credit/loans are perceived, practised and mediated through human interaction, and what this reveals about the relationships between political and financial institutions.

The Chinese Banking Sector and its Financial Credit System

The banking industry is the key component of the Chinese financial system in terms of assets and corporation size.Footnote ¹⁹ As China's economic reforms progressed post-1978, there emerged a trend in which the shifting ethical narrative caused moral panic at multiple levels.Footnote ²⁰ The demand for a credit system in China stems from the 1980s phenomenon known as “triangle debts” (sanjiaozhai 三角债). This term commonly referred to enterprises obtaining multiple loans, delinquencies and evasions of bank debt, and exposed issues with loan defaults in both the commercial and financial sectors.Footnote ²¹ The situation was exacerbated by real estate developers in places like Hainan province who leveraged unfinished land projects as collateral to banks, leading to an increase in non-performing loans (NPLs).Footnote ²² To resolve the problems of triangle debts, the former Shenzhen branch of the People's Bank of China (PBOC) began to implement a “loan certificate” scheme, which was then promoted nationwide. In 1997, the PBOC began to prepare for the establishment of a bank credit registration and consultation system, which was put into operation in 1999. Since then, the system has been upgraded to a national centralized credit investigation platform that includes both a basic database of enterprise credit information (qiye zhengxin 企业征信) and a database of individual credit information (geren zhengxin 个人征信). Commercial banks are the main source of information for credit investigations by the PBOC, providing basic information on enterprises and individuals, loans in financial institutions, guarantees and other credit information, as well as major financial indicators. Notably, credit officers lacked training in evaluating loan applications commercially and faced no accountability for the high NPL levels in state-owned enterprise (SOE) portfolios until the late 1990s.Footnote ²³ The PBOC's database indicates that it had information on almost a billion people by 2020, while only half of these had credit records; yet the 50 per cent without a credit score have the greatest need for credit financial services, and they frequently struggle to provide satisfactory financial data and collateral assets.Footnote ²⁴ Less than one-fifth of MSMEs can obtain bank loans.Footnote ²⁵ In short, various factors made banks unwilling to lend to small private enterprises.

Moreover, the banks’ traditional business model has been threatened as tech companies have entered the market of mobile payment and credit loans. China's tech giants are able to leverage their nationwide e-commerce platforms and exploit customer data to provide a variety of tailored financial services to hundreds of millions of customers that the bricks-and-mortar banks cannot reach.Footnote ²⁶ Despite continued market reforms and restructuring, banks in China have relied heavily on interest margins and large (SOE) corporate clients, a situation which has increased their fragility and weakened their competitiveness. Consequently, their strategies in response to the changing competitive landscape are intertwined with the conceptualization, implementation and potential mediation of state-initiated digital credit/loans.

Promoting Trust and Financial Inclusion through “Credit Easy Loan”

“Credit easy loan” is one of the major “Credit easy+” (Xinyi 信易+)” incentive programmes under China's social credit construction plan. According to the State Council, the purpose of the social credit system is to improve the integrity and credit level of individuals, and of both the private and public sectors, thereby gradually establishing a more “trustworthy” society.Footnote ²⁷ The PBOC continues to be responsible for regulating financial credit evaluations, whereas the NDRC oversees other types of credit evaluation. In 2017, the National Center for Public Credit Information (NCPCI) was established as an affiliate of the NDRC.

In April 2018, the NDRC introduced the concept of “credit easy loan” for the first time.Footnote ²⁸ The NCPCI uses information derived from the national credit information-sharing platform to build a national comprehensive “credit easy loan” platform, which integrates credit information taken from areas such as taxation, market supervision, customs and justice departments, water, electricity and gas bills, as well as social security and housing payments, and provides information services to financial institutions through local “credit easy loan” platforms.Footnote ²⁹ MSME owners can use local “credit easy loan” websites to search and apply for loans. Since loan products rely solely on “credit data” for guarantees, applicants without collateral can apply and all stages of the application are completed online. Similar to the top-down microcredit programmes that form part of the government's rural development strategy, “credit easy loan” platforms are not institutions themselves but rather are policy frameworks that promote and facilitate transactions between disadvantaged (and “virtuous”) borrowers and financial institutions.Footnote ³⁰ The state sees the collaboration between the NCPCI's social credit database and the PBOC's financial credit database as a means to enhance MSME financing: banks can utilize digitalized “credit data,” instead of physical collateral, for automated loan decision making.

Since 2021, the China Banking and Insurance Regulatory Commission (CBIRC) has explicitly required large and joint-stock banks to increase the number of first-time borrowers from MSMEs through issuing notices.Footnote ³¹ Credit supply for most types of bank loans is rationed by their headquarters, which are regulated and monitored by the PBOC.Footnote ³² Currently, banks’ loan decision-making processes are complicated by manifold internal and external factors.Footnote ³³ Meanwhile, researchers have noted the gap between the state's digital ambitions and local implementation.Footnote ³⁴ Has MSME access to bank loans changed under the ongoing digital transformation and financial inclusion policy? In the context of rapidly developing digital finance and the political imperative of financial inclusion, the actual practices of bank digital lending to MSMEs have become the locus for understanding the relationship between fintech, banks and the state's digital-political goals.

“We Are Not in Big Data Mode Yet”: Credit Risk Evaluation and Loan Decision Making in Two Banks

One afternoon in July 2022, Deng took me to a branch of X Bank in City A. The physical setting of the branch was similar to others I had visited years before – a few standard offices and meeting rooms, with few digital elements. The computers appeared to be rather old but had to comply with the bank's security system. After I expressed my research interest in the use of credit data and fintech in banks, Rui, the branch president, nodded:

Rui's claim suggested the existence of incompatible interests between the two areas. Guo, the manager of the branch's risk management department, added, “As bank people, we think about risk in a different way from tech people; we care about profit and want to eliminate risk.” She told me how the late payment rate on credit cards in X bank had increased to above 6 per cent since the COVID-19 pandemic, and raised the question: “What about larger loans?” The tension was evident when it came to online credit loans. JD Finance's Jintiao and Alibaba's Jiebei, for instance, are two giant big-tech credit platforms that enable users to apply for and receive loans within minutes, highlighting their low barrier to access, high efficiency and flexibility. For most banks, on the other hand, the credit risk assessment and loan approval processes are more complicated and time-consuming. Only some micro/small personal credit loans (10,000–300,000 yuan, depending on the bank) can be accessed entirely via the internet or an app, and usually on the condition that the loan applicant has used the same bank's credit card for a specified length of time while maintaining a stable income status. People without a local hukou 户口 (household registration) and no history of local social security and housing fund payments are further marginalized in the process of credit loans, as they are unable to apply for a credit card.

X bank performs credit checks for even the smallest loans in person, although several state-owned banks have already started conducting basic credit checks via their online apps. X bank's loan officers collect the necessary documents and prepare a report for the preliminary examination. The loan application then goes to the risk management department and then to the branch president for approval. Smaller loans may be processed within the branch, but a large number are passed up to a higher-level branch (for example, the city/province level). Guo and Cong often had to spend inordinate amounts of time organizing document folders that piled up on their desks.

Rui mentioned that, based on past experience, the bank did not usually loan money to anyone without a credit history (baihu 白户), or a local hukou. For example, some uneducated villagers had fallen victim to scammers who had promised them “free money.” The tricksters had taken the villagers in trucks to the bank and then using their IDs had taken out credit cards and small personal loans in the villagers’ names. These credit cards then became bad debts for the bank. Even today, online financial services are troubled by disproportionately high levels of fraud, forcing banks to constantly come up with effective antifraud measures.Footnote ³⁵ That is one reason why applying for a credit card (and even a debit card in some regions) is becoming increasingly difficult. The loan managers I interviewed all emphasized the importance of borrowers owning local properties, as the bank can auction them off in the event of non-payment.

Qiao, my uncle's friend, had been working in Y bank for more than 25 years. I interviewed her in her office in September 2022. The next day, Qiao introduced me to Luo, an upbeat and talkative woman. Luo had been working in a business loans department for more than 30 years, and her credit evaluation method had been standardized. After she had received an application, she would first go through the company's financial statements on condition that the applicant had held a credit card with the bank for more than three years, and that their personal and enterprise zhengxin 征信 (financial credit) reports were in good order. Luo would then investigate the company personally. This included verifying the company's actual business/goods and profit points, and its purpose in applying for the loan. Luo emphasized that she would also check that neither the upstream nor downstream partners of the applicant company would be adversely affected by the debt, and that their collaboration would continue to run smoothly. Finally, Luo would issue a risk assessment report to the bank manager and recommend a rate of interest for the loan. In most cases, business owners would find out that they could apply only for collateral-based loans and not for credit loans. Similar to X bank and other smaller banks, Luo emphasized the importance of owning residential property locally, and she had to go in person to the local real estate bureau to verify a property's value and complete the mortgage registration. According to Luo, none of these tasks could be done online. Her workflow has not changed in the last decade. During the course of my fieldwork, I came to understand that most of the senior officers in the branch were not tech-savvy, and there were many complaints by the younger employees about the outdated system and equipment.

I explained to Luo about digital lending platforms such as “credit easy loan” and how a creditworthy person or enterprise might apply for credit loans without having to own an expensive flat in the city. In response, she said:

Luo and Qiao mentioned that, based on past lessons, their branch had issued a substantial credit loan to a private hospital on the basis that it was a large enterprise with a good reputation in City A. They knew the two owners so well that collateral assets were not required. Similarly, Cong, at X bank, told me that the bank once had a client who was 500,000 yuan in debt. If the bank had looked only at his financial credit report, which was issued by the PBOC, this would have been the end. However, the client, a senior manager of a foreign-invested company, privately communicated (dazhaohu 打招呼) with the president of the superior city-level bank branch. Subsequently, Cong prepared (or faked) a set of “clean” documents to support the loan application and X bank issued a loan of 500,000 yuan to the client by the end of the day. As Cong explained, “Sometimes being a debtor doesn't mean the person is not good, just like this one. Once he has enough to go around his business, he will be okay.” According to them, it is about understanding the client's personality and capability to pay.

Kexin, a consultant who specializes in the digital transformation of banks in City B, explained that when banks claim to use the “big data risk control” method, they usually mean that they use the client's data from within the bank and tax credit records. This kind of “big data” is less informative than client data from tech companies such as Alibaba. In my interviews with senior bankers, I asked each one: “As bank people, do you feel you are in big data mode now?” They all replied, “Not yet.” When I asked how they made decisions on loans, loan managers from both X and Y banks said, “We still depend on guanxi” (haishi henkan guanxi 还是很看关系). Such a statement underscores the ongoing significance of moral accountability and reputation achieved through the cultivation of good relations/guanxi.Footnote ³⁶ In traditional Chinese society, social organization revolved around various local social circles, where individuals’ moral reputations were tied to their positionality within each social relationship.Footnote ³⁷ People tended to rely on personal trust cultivated through long-term guanxi and mutual understandings within the same social circles. Trust continues to be a crucial element in most informal financial organizations in China. One such example is rotating savings and credit associations, where members, often tied by kinship and specific local networks, commit to contributing a fixed amount of money at regular intervals, typically weekly or monthly, and then take turns to withdraw the entire sum.Footnote ³⁸

Traditionally, banks assess credit risk based on three factors: an examination of the financial data, the applicant's collateral assets and the applicant's relationship with the bank.Footnote ³⁹ The two bank branches I visited tended to rely on relationship lending and local collateral assets to assess the risk for business loans, while digital technology and the so-called big data credit were less important. According to X and Y banks, the financial credit report from the PBOC was no more than basic, and the social credit (shehui xinyong 社会信用) information provided by the NCPCI was not relevant. In this context, the branches’ credit risk management was heavily dependent on the loan officer's personal experience and professionalism. The concept of using financial technology such as big data to regulate credit risk was still vague to Luo and the other senior loan officers, particularly in regard to business loans involving larger amounts. Moreover, banks’ relationships with loan applicants, particularly MSMEs, are complicated by third-party agencies.

“Packaging Agencies”: Beautifying or Faking Credit Data?

“Packaging agencies” are intermediaries that assist clients in preparing, checking and “beautifying” their bank loan applications. These agencies usually charge a commission of 2–3 per cent. Their services include conducting “comprehensive credit checks” of clients and their businesses, which includes reviewing financial credit reports and documents, and then selecting the most suitable loan product. Most packaging agencies’ clients are unclear about the official names or registrations of these intermediaries. They exist outside the banking system and are unregulated. In news reports, these agencies are usually referred to as “black intermediaries” (heizhongjie 黑中介) who trap desperate loan applicants.Footnote ⁴⁰

Despite the packaging agencies’ bad reputation, many MSMEs still use them for want of a better option. For instance, Sheng, a kindergarten owner, had applied for several quick big-tech loans of around 80,000 to 200,000 yuan in recent years. Despite owning two local apartments, Sheng's loan applications were turned down by several major banks because of his flawed financial credit report. During fieldwork, I accompanied Sheng and his wife to the office of a packaging agency as they submitted their loan application documents. The agency was called “KD Investment Management Company” and shared office space with three other companies, all belonging to the same owner. There were several front-line salespersons making phone calls from a list gathered through different channels; that was why Sheng said these agencies are “nothing special, just looks like a multi-level marketing/pyramid scheme company.” Potential clients visiting the office would be greeted by a consultant. In 2020, Sheng signed a contract with the KD Investment Company in which it stated that KD would provide financial services to Sheng for a commission of 50,000 yuan. Eventually, KD helped Sheng to successfully apply for a business loan product from a joint-stock bank for a loan of 1,000,000 yuan. In September 2022, Sheng's wife signed another contract with the same consultant, with whom they were familiar, rather than with the company. This, Sheng suspected, was due to legal concerns. Sheng believed the agency was reliable and assured me that he and his wife would soon receive the money to keep their kindergarten running.

In Sheng's view, packaging agencies saved applicants the time and effort required to polish application documents and cultivate good relations with banks. Decades earlier, Sheng had successfully obtained a variety of loans with state-owned banks. He emphasized that this was not about bribing or sweet-talking the bankers:

As the banking sector became increasingly regulated and the financial credit system more standardized, Sheng found himself facing different constraints. Many of Sheng's banker friends had been either retired or arrested. He came around to the view that using the agencies could take the effort as well as the risk out of building a rapport with bank officers. Doing business, in this sense, was still about managing interpersonal relationships rather than a faceless transaction.Footnote ⁴¹ Sheng and his fellow businesspeople seemed to acknowledge, and to some extent appreciate, the emergence of packaging agencies because these agencies took care of not only the documents but also the guanxi with banks.

Deng's case shows more explicitly that banks may employ packaging agencies directly. In 2020, Deng applied for a loan product from X bank following Rui and Cong's instructions. For Deng, they offered the good guanxi with senior bankers that make loans possible for her. Normally, Deng would not be eligible to apply for a mortgage to buy a flat because of her complicated work and family status. Cong advised her that since she needed a large amount of money, it would be more beneficial for her to apply for business loans, even if the funds were intended for personal use. Cong then referred Deng to an agency to “beautify” her education and employment history. “The only thing that can't be counterfeited is the PBOC financial credit report,” Cong explained, echoing what other bankers had said. According to Cong, their department cannot check every piece of information with local authorities as that would be too time consuming. Deng's husband had been blacklisted as a “dishonest debtor” (shixin beizhixingren 失信被执行人), so the agency also faked a divorce certificate for Deng to avoid her husband's bad credit history affecting her loan application.

Cong and the agency helped Deng apply for a “credit easy loan” under the category of a small enterprise. To be eligible, Deng needed to have a company. The preparation of the company document only took an afternoon. Deng described the scene over dinner:

Later, Deng registered a bogus sports training company that would receive the loan. Deng's friends in X bank were aware that she used the agency to create a fake company tax report and said nothing. Deng eventually received 1,880,000 yuan within a week and purchased a new flat. It was obvious that Rui and Cong were not worried that Deng would not pay the loan off in time and leave them with a bogus company. As well as being old friends with Deng, Rui and Cong are also familiar with her financial status and her partner's business. Deng has always lived a luxurious lifestyle and been generous with friends; her husband's company owns a well-known brand that has yet to be sold. In this way, Cong and Rui trusted Deng (and her husband)'s ability to make the repayments. Deng reassured Rui and Cong by saying, “I always make the repayment on time. You can trust me!”

Young entrepreneurs also find it necessary to engage packaging agencies when applying for business loans or loans other than microloans from banks. Yang started a company with college friends in 2017 in City B. The 15 friends mostly design web games for big companies like ByteDance. Yang never liked the idea of borrowing money, whether it was from the bank or through peer-to-peer lending. However, restrictive gaming policies and the pandemic caused great financial stress, and several of Yang's business partners left. He had to turn to MSME financing in 2021.

Yang came across “credit easy loan” when he was researching bank loans. He found the interest rates of big-tech credit loans too high, and the traditional bank business loans required local collateral assets, which he did not have. When he submitted his loan application through the “credit easy loan” platform, it was rejected by the bank with the information that it was “not good enough.” This left Yang confused as he did not have a bad credit history. One of Yang's friends recommended a packaging agency which claimed to provide loan-related services. The agency took on the burden of applying for the loan and following the application updates, as well as making suggestions to improve the creditworthiness of Yang's company. Yang's initial, rejected application showed that his company's revenue from 2019 to 2020 was deemed too low, and the agency told Yang that the bank did not believe his company would turn a profit. In the second attempt, the agency included profits that were not the result of game sales in the company's annual report (commonly referred to as “beautifying the document”). Subsequently, the loan application was approved, and Yang was able to borrow 500,000 yuan. The entire process took two months. It should be noted that the amount of the loan – 500,000 yuan – is small compared to what “credit easy loan” claim to offer MSMEs.

These informal intermediaries perform functions similar to those offered by the “credit easy loan” platform: they gather financial documents from applicants, assess their creditworthiness and match them to bank products, hence easing the information asymmetry between the bank and the enterprise. Their structures vary, as some have risk controls and legal professionals and others hire former bank employees. These agencies also play a role similar to an informal guarantor in terms of their close relationship/guanxi with the bank. When faking credit data materials, they would ask their banker friends to bypass the verification process. Therefore, these agencies cannot be simply categorized as private financing consultants or “black intermediaries.” These agencies can save the banks time when reaching out to potential clients and do the donkey work for them. The next section further unpacks the motivation of banks when employing these informal agencies.

“Unrealistic” Policy, “Practical” Implementation

Big-tech credit has enabled thousands of MSMEs in China to borrow money. The widely recognized digital lending model for small loans is “3-1-0”: 3 minutes to submit the loan application, 1 second for the loan to be released, 0 human intervention. Again, this model has been developed mainly by tech giants since 2010 and has recently been adopted for bank credit loans to MSMEs. To what extent have MSMEs benefited from the state-initiated bank digital lending platforms such as “credit easy loan”? Among the 13 MSME owners I interviewed, only Yang had successfully obtained a business credit loan without a collateral asset, and the process took much longer than the advertised “3-1-0” model.

During the COVID-19 pandemic, many shops and restaurants experienced significant financial stress. In early 2021, City B's government introduced a “credit easy loan” product aimed at restaurants. It has two guarantee methods: credit or collateral. Two weeks after the launch of this loan product on City B's “credit easy loan” platform, Jiu, who owns a barbeque restaurant in City B, complained that the term “credit easy loan” was deceptive. Before that, Jiu and other restaurant owners on the same street had been approached by community workers asking them to register their businesses with the “credit easy loan” platform. The community workers’ tasks were assigned by local authorities and often turned out to be performative. MSMEs were requested to actively participate in local government-initiated outreach activities of this kind, but many registered MSME owners, like Jiu, later realized that they were not eligible for many of the “credit easy loan” products on offer. By the end of 2022, City B's government reported that its “restaurant credit easy loan” platform had released loans to 764 catering businesses. It cited a hotpot chain catering enterprise as one example of a successful loan applicant – a business which hardly fits the definition of an MSME.

Several respondents who are MSME owners used their credit cards as their funding resource, while some used small personal loans such as consumer loans. In other words, they applied for loans as individuals rather than as an enterprise, and thus the lending decisions were based on themselves rather than on the business. It is crucial to note that most big-tech credit borrowers are individuals, although big-tech lenders have extended loans to small businesses.Footnote ⁴² Teng, who had been using his credit cards to keep his flower shop operating, explained, “We can't get loans if applying as an enterprise, [there is] too much paperwork and qualification requirements.” These respondents said the bank knew their reasons for applying for credit cards and personal consumer loans and so, in this scenario, the banks are practising illegal lending. The small business owners described it as “using illegal means to achieve lawful ends” (feifa shouduan dadao hefa mudi 非法手段达到合法目的).

Since 2021, state media have been lauding the “credit easy loan” as a nationwide achievement.Footnote ⁴³ Meanwhile, the bank managers and even NDRC officials I encountered during my fieldwork expressed bewilderment upon hearing this news, dismissing it as a stunt (xuetou 噱头). This, again, implies a gap between state policy and local implementation. Most respondents complained that since China has no bankruptcy law similar to that in Western countries, individuals must be responsible for their debts. Furthermore, bank branches now operate in a different competitive landscape. Internally, branches are ranked according to their profit, with the lowest-performing branches receiving warnings; externally, banks must compete against each other as well as tech platforms to attract the best clients. Rui, the branch president said, “The top-level people say they are helping small enterprises, but, at the end of the day, we take on the risk by ourselves.” Rui complained that most MSMEs have no actual property to offer as collateral: they usually rent their premises and even the factory equipment is not worth money. He did not believe in the sustainability of MSMEs, which often “die” within three years. Similarly, Qiao and Luo from Y bank displayed an indifferent attitude and were sceptical about “credit easy loan” platforms. As Luo lamented, “We are affected by the policy, but the policy and reality are often contradictory. The policy is very political, but then, how do we give money to the small companies that may not survive? Who takes care of the bad debts we have?” Such statements suggest that the state-initiated digital platform, which claims to incorporate various public credit data sources, has limitations when it comes to assessing an individual's repayment capability or credit risk.

City A's government has been promoting “credit easy loan” since 2021, with X Bank being highlighted as one of the partnering financial institutions in news reports. I inquired about the reasons behind lending over 4 billion yuan to MSMEs, despite an initial reluctance to provide them with credit loans. Rui offered the following explanation:

It is clear from Rui's explanation that banks have their ways of meeting the loan quotas for the “credit easy loan” and similar MSME credit loans. In interviews, I came across another tactic used by the banks, “labelling” (tiebiao 贴标), which refers to classifying a big company as a micro-small enterprise so that the loan would be categorized as an MSME business loan in the bank's digitalized system. Normally, when a company's registered information fits the definition of a micro-small enterprise, it is automatically listed on the “Directory of small and micro enterprises” website.Footnote ⁴⁴ “Labelling,” then, involves human input and relations of trust between the business loan applicant, the bank, third-party packaging agencies and possibly government officers. All parties share the secret, and the risk, for their own interests.

The CBIRC conducts annual random checks on loan documents, and banks that approve fraudulent application documents may face penalties. Large state-owned banks like Y Bank would rather avoid working (directly) with informal intermediaries because they are investigated more frequently and more thoroughly. However, X bank and other smaller banks are more inclined to work with “packaging agencies” to increase the possibility of acquiring creditworthy borrowers and thereby improve their performance and competitiveness. Senior bankers emphasized that they were concerned about legal consequences, but this was “the only way.”