**1. Introduction**

E-commerce and FinTech are currently booming in China. The growing consumer market is accompanied by internet finance, by which consumers can easily borrow money from financial institutions through online platforms. As a result, the growing risks of the financial institutions are of concern to the government and regulatory bodies. Consequently, the securitization market in China has grown rapidly in recent years. Securitization in China has experienced a great increase since 2014, and it is now the second-largest securitization market in the world (Hogan Lovells 2019). The main reason for this rapid growth is the simultaneous release by the China Banking Regulatory Commission (CBRC) and the China Securities Regulatory Commission (CSRC) of documents to implement a reform that replaced the approval system for asset securitization with a filing system (Tang et al. 2017). Due to financial disintermediation and the need for central banks to establish interest rate corridors, commercial banks are increasingly enriching their asset allocation choices, which also influence the investment in securities (Huang et al. 2019). In 2019, the total volume of ABS issued in China reached USD340 billion, marking a 16.69% increase compared with 2018. The total outstanding volume of ABS by the end of 2019 stood at USD566 billion, a 27% increase compared with 2018 (Phua 2020). The remarkable growth of securitization in China is similar to that in the United States before the global financial crisis of 2007–2009. The securitization market in the United States also experienced rapid growth before the global financial crisis from 2007 to 2009. Many commentators cite the remarkable growth

**Citation:** Chen, Xueer, and Chao Wang. 2021. Information Disclosure in China's Rising Securitization Market. *International Journal of Financial Studies* 9: 66. https:// doi.org/10.3390/ijfs9040066

Academic Editor: Thanh Ngo

Received: 16 September 2021 Accepted: 19 November 2021 Published: 1 December 2021

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of securitization in the United States as a major contributor to the ensuing crisis. Part of the argument is that securitization creates an additional layer of information asymmetry in the origination of a loan, which results in adverse selection, moral hazard problems, and thus higher default rates. China's securitization market, as mentioned, has also experienced remarkable development. The question of whether securitization affects the financial stability in China has yet to be answered and is a growing concern for authorities. The answer might depend on the standard of information transparency, and a high degree of information transparency will always benefit an authority's monitoring activities and help to protect investors.

One of the effective ways to improve the standard of information transparency is to apply FinTech and emerging technologies in the securitization market against the background of the digital transformation of banking. Due to the new digital giants in China—Alibaba and Tencent—and the COVID-19 pandemic, traditional Chinese banks have tended to increase their focus and efforts on digital transformation. For example, some of these traditional banks have leveraged FinTech and emerging technologies, such as machine learning, artificial intelligence, big data, cloud computing, and blockchain, to shape their operating model enterprise-wide. Machine learning and artificial intelligence have had a strong impact on credit risk management, which can be used to deal with the problems of information asymmetry (Mhlanga 2021). According to Deloitte's (2018b) report, cloud computing, big data, artificial intelligence, and blockchain technology entered the stage of comprehensive application in the banking industry in 2018, and "FinTech", "Inclusive Finance", and "Asset Management" have become key words in many banks' annual reports. FinTech and emerging technologies have also been applied in the securitization market to enhance its standard of information transparency. More specifically, all loan data can be placed on a blockchain. Those loan data thus become immutable and are time-stamped on a verifiable audit trail (Structured Finance Industry Group & Chamber of Digital Commerce 2017). Blockchain technology could be used to automatically share and analyze data in line with regulatory requirements; underlying loans, for example, could be easily and automatically matched against the securitization's proposed structure, thus making compliance easier (Sindle et al. 2017).

It is currently unclear whether the digital transformation of banking can reduce the impact of information asymmetry and whether information transparency regulations are sufficient for the supervision of securitization or the need to leverage FinTech and emerging technologies. Thus, this study aims to answer the following question: Does China need a higher standard of information disclosure to protect against its risks? To answer this research question, we examined the potential moral hazard and adverse selection problems in securitization and compared those problems in two periods. The first period is pre-2017Q4 and the second period is post-2017Q4. Post-2017Q4 represents the stage of FinTech's comprehensive application in the banking industry.

The moral hazard and adverse selection problems can be tested by the motivations for the securitization of loans. More details and reasons can be found in Section 2. The original research on the determinants of the securitization of loans emerged during the 1980s, when a strand of U.S. research studied loan sales, an instrument that is similar to loan securitization (Giddy 1985; Pavel 1986; Pavel and Phillis 1987). Giddy found that capital requirement is an important determinant for loan sales. Pavel and Phillis (1987) proved that securitization provides a means of reducing a bank's credit risks. After the global financial crisis of 2007–2009, research in this area resurfaced. The starting research was on the determinants of European banks' engagement in loan securitization (Bannier and Hänsel 2008). They examined firm-specific and macroeconomic factors that drive financial institutions' decisions to engage in loan securitization transactions. Bank size, credit risk, liquidity, and performance are the four main factors of load securitization transactions in European banks. Two similar papers then reported an empirical study on Italy and Spanish loan securitization markets, respectively (Affinito and Tagliaferri 2010; Cardone-Riportella et al. 2010). The result of the study from Affinito and Tagliaferri (2010) is

similar to that of Bannier and Hänsel. However, Cardone-Riportella et al. (2010) claimed that liquidity and performance are the only two decisive factors in securitization. Credit risk is not the main determinant. Acharya et al. (2013) also found that risk exposure failed to promote increased securitization growth, which means that banks were securiting without transferring the risk to investors. Recently, the topic on the determinants of loan securitization in European banks was studied again (Farruggio and Uhde 2015), and the determinants of loan securitization in the pre-financial crisis and the post-financial crisis were compared. The determinants of loan securitization changed remarkably over the pre-crisis and crisis periods.

In accordance with these recent journals, (1) the first contribution of this paper is to study the determinants that drive securitization in the Chinese banking section. Markets in different regions and countries reflect the varying outcomes of securitization determinants. The determinants of securitization in China might be quite distinct from previous research. This paper compares the determinants in different types of bank, and how securitization in these various types of banks are affected by the determinants. (2) Additionally, this study proposes and explains why the four determinants mentioned above can be used to examine the problems of information asymmetry in securitization. Specifically, a securitization determinant study reflects not only the motivation of securitization in the banking section, but also the financial stability. Financial stability is influenced by information asymmetry. Information asymmetry is reflected by moral hazards and adverse selection. Moral hazards and adverse selection are tested by the four determinants. After examining how these four determinants are related to the moral hazard and adverse selection problems in securitization, we can then assess whether current information transparent standards are sufficient for securitization development in China. (3) Finally, this study investigates the effect of FinTech in China's banking sector by comparing the change in securitization determinants in the two periods.

Summarizing our results, we find that the risk exposure is the most significant determinant, followed by liquidity and profitability before the comprehensive FinTech application in China. After that, risk exposure is still the motivation of securities issuance, but there is no evidence that liquidity and performance can promote loan securitization transactions. Capital requirement could be the motivation for securities issuance in commercial banks. Additionally, by comparing the outcomes of the determinants at two stages, this study finds that the application of FinTech can reduce information asymmetry in the securitization market dramatically, especially for moral hazards. However, we still cannot fully reject the influence of banks' incentives on risk transfers to outside investors after a comprehensive FinTech application. Therefore, the answer to the research question is that China still requires a higher standard of information disclosure to protect against its risks. The remainder of the paper is organized as follows: Section 2 provides the theoretical background and summarizes earlier empirical evidence on securitization determinants, followed by the theories of adverse selection and moral hazards. In Section 2.3, we will explain how those securitization's determinants are linked to adverse selection and moral hazards. Subsequently, Section 3 presents the empirical methodology, a data description, and variable definitions and empirical models. Empirical results are presented in Section 4, where both univariate analysis and multivariate analysis are given. According to the empirical results, Section 5 will discuss the findings and link them to the adverse selection and moral hazard problems. Section 6 will provide corresponding recommendations. Section 7 concludes.

#### **2. Theoretical Foundation**

#### *2.1. Determinants of Loan Securitizations*

The research addressing the reasons for securitizations includes the need for new sources of funding (liquidity), credit risk management (risk exposure), the search for new profit opportunities (regulatory capital arbitrage), and performance.

#### 2.1.1. Liquidity

The first reason to securitize an asset is an alternative source of funding. Banks can transform loans into cash by the securitization mechanism (Kothari 2002). This mechanism is typically related to 'true sale' transactions when a bank transfers parts of loan portfolios to SPV (Special Purpose Vehicle) and in turn receives liquidity from the issuance of loanbacked securities by the vehicle (Farruggio and Uhde 2015). In this way, banks can acquire alternative funding resources in a new way beyond traditional equity, as well as debt financing. Thus, securitization makes banks less vulnerable to liquidity shocks.

The empirical evidence clearly shows that the liquidity effect is a significant determinant for loan securitization in European markets. Cardone-Riportella et al. (2010) found that liquidity is one of the main factors that drives securitization in Spain according to a sample of 408 observations in the pre- and post-financial crisis. The same conclusion can be found in Italy during the period from 2000 to 2006 (Affinito and Tagliaferri 2010). Similarly, Bannier and Hänsel (2008) found that low liquidity triggered securitization issuances from 17 European countries between 1997 and 2004.

#### 2.1.2. Risk Exposure

Securitization enables banks to lower risk exposure through credit risk transfers. It is related to 'true sale' transactions and the 'bankruptcy-remoteness' principle. When a bank transfers parts of loan portfolios to SPV, the corresponding loans are also removed from the bank's balance sheet, and the underlying assets from the bank are isolated. After that, investors do not have any claims against the bank's assets once a default or bankruptcy occurs. The 'true sale' transaction and the 'bankruptcy-remoteness' mechanism allow credit risk sharing with investors, and banks do not have obligations to maintain value and reap the excess returns. The risk exposure is distributed by securitization rather than held by one bank, which minimizes the financial distress cost. Early theoretical journals proved that securitization provides a means of reducing a bank's credit risks by this mechanism (Greenbaum and Thakor 1987; Pavel and Phillis 1987). However, in some cases, credit risks are difficult to transfer out of banks, because the originator generally retains the first-loss tranche (low- or zero-rated securities). This means that risks inherent to the securitized assets are considered in the banks but off-balance sheet (Calomiris and Mason 2004; Higgins and Mason 2004). The other problem is that the transfer of low-quality loans to SPV could lower a bank's reputation, and only those banks with reputational advantages can repeatedly enter the securitization market and place multiple transactions (Ambrose et al. 2005).

Corresponding to the theoretical predictions, the empirical evidence is ambiguous. Some empirical studies, including those of Minton et al. (2004) and Bannier and Hänsel (2008), show that credit risk exposure is important for banks' securitization decisions, while other empirical evidence indicates that, compared with risk transfers, issuing banks prefer to retain low-risk loans in their portfolio and remove high-risk loans from the balance sheet to build their reputation (Altunbas et al. 2010; Ambrose et al. 2005; Albertazzi et al. 2015).

#### 2.1.3. Regulatory Capital Arbitrage

Banks can reduce regulatory capital via securitization because of the different capital requirements between the bank's assets on the balance sheet and those within the first-loss piece. Under the First Basel Capital Accord (Basel I), because the amount of required regulatory equity capital was comparably low when securitizing banks' assets, banks were able to provoke arbitrage profit by keeping the largest part of default risks (e.g., corporate and retail loans) within the first-loss piece rather than keeping them on banks' balance sheets (Ambrose et al. 2005; Calomiris and Mason 2004). However, before the financial crisis of 2007–2009, the Basel commitment required a higher standard regarding regulatory capital to improve financial stability (Basel II), and this resulted in fewer opportunities of regulatory capital arbitrage. Basel II follows a 'substance over form principle', which more precisely determines the required regulatory capital for all retained tranches of a securitization (Blum 2008) and strongly stimulates incentives to transfer subordinated tranches and the first-loss piece to external investors (Farruggio and Uhde 2015).

The empirical evidence on the regulatory effect is also ambiguous. There is no strong evidence indicating an opportunity to realize regulatory capital arbitrage spur securitizations in U.S. banks from 1993 to 2002 (Minton et al. 2004). By contrast, other U.S. securitization market research yielded different outcomes by employing 112 financial institutions from 2001 to 2005 (Uzun and Webb 2007). Ambrose et al. (2005) provide a similar conclusion and noted that securitization is driven by regulatory capital arbitrage.
