SMEs, Trade Finance Markets and Instruments: A Review of the Issues with Reference to Asia Downloaded from https://academic.oup.com/wbro/article/40/2/261/7670862 by Laura Mowry user on 05 August 2025 Tony Cavoli, David Christian, and Rashesh Shrestha Small and Medium Enterprises (SMEs) are an important source of employment and eco- nomic activity, but their expansion and growth may be limited by the existence of trade fi- nance constraints due mainly to a lack of access to external sources of finance. We present a conceptual framework for understanding trade finance transactions, instruments, and participants; and map this framework to the available data used to measure trade finance. Finally, we present some stylized facts on the relationship between various trade finance instruments, and their possible links to SME outcomes with reference to ASEAN countries. We find that there are many (though imperfect) proxies for trade finance activities; and that improving trade finance is associated with more desirable SME outcomes. JEL Codes: F19, F34, G21 Keywords: trade finance, international financial institutions, trade, financial crisis. Introduction Many firms, especially small and medium enterprises (SMEs), find it relatively difficult to engage in international trade, often due to a short supply of financing instruments required to trade internationally (USITC 2010, WTO and IFC 2019). Trade finance is broadly defined as loans and guarantees that financial (and non-financial) institutions provide to firms to facilitate cross country transactions of goods and services.1 The size of the so-called trade finance gap (an unmet demand for trade finance) is estimated to be trillions of dollars, much of it experienced by smaller firms in developing countries (ICC 2020, Auboin 2021, Kim et al. 2019). Mitigating the trade finance gap by deepening trade finance markets remains a crucial policy challenge for developing and emerging countries looking to improve SME participation in international trade. The World Bank Research Observer © The Author(s) 2024. Published by Oxford University Press on behalf of the International Bank for Reconstruction and Devel- opment / THE WORLD BANK. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com https://doi.org/10.1093/wbro/lkae006 40:261–289 The complexity of trade finance arrangements and paucity of systematic data on the trade finance ecosystem create hurdles for policymakers. The availability of trade finance depends on the nature and strength of relationships between key actors in the trade finance ecosystem, which comprises exporting firms, importing firms, govern- ment, large national banks, small local banks, and multilateral development banks. Absence of any of these relationships could be the underlying cause behind the ob- served trade finance gap, which may vary widely across countries. Thus, mitigating the Downloaded from https://academic.oup.com/wbro/article/40/2/261/7670862 by Laura Mowry user on 05 August 2025 trade finance gap through policies requires a clear view of the gaps in the ecosystem through systematic and detailed data. However, while there are many studies showing the importance of trade finance for firms in general and SMEs in particular, there is no systematic framework for the measurement of trade finance and, as such, no com- prehensive dataset that captures all of the salient characteristics of trade finance (IMF 2019b). This paper sheds light on the nature of the trade finance market for SMEs as well as the major impediments to securing trade finance for SME performance using the emerging and developing economies of ASEAN and East Asia as a case in point. Asia and ASEAN feature prominently in trade and trade finance issues in a global context. The Asian Development Bank (ADB) puts the trade finance gap at $1.7 trillion in 2020 (ADB 2021), of which the ADB (2019) reports that 34 percent exists in the Asia and the Pacific region. Among developing regions, Asia and the Pacific continues to have the highest proposal rate (40 percent of global proposals) and the highest rejection rate (34 percent of global rejections) for trade finance. Di Caprio et al. (2016)show that Asia and the Pacific accounts for 39 percent of all rejected trade finance transactions and approximately one-third of these are from China and India (7 percent of total rejec- tions each). SMEs generate the highest number of proposals with rejection rates above their proposal share—44 percent of all proposals, 56 percent rejected. Only 10 percent of proposals from multinational corporations (MNCs) and 34 percent from large cor- porates are rejected.2 As such, focusing on this region helps to highlight the key points of this paper. We firstly present a review of the pertinent literature with respect to trade finance, trade, and SME activity. We then examine the nature and strength of relationships between different actors in the trade finance ecosystem by presenting a conceptual framework for understanding trade finance transactions, instruments, and partici- pants. We then use this framework to map against the available data used to measure trade finance. Finally, by way of context and to illustrate some of the points raised in previous sections, we present some stylized facts on the relationship between various trade finance instruments, and their possible links to SME outcomes for ASEAN and Asia. Our main findings are as follows: Firstly, while there is an acknowledged lack of a systematic data source for trade finance, there are many proxies through which trade finance activity can be analyzed. Secondly, there is evidence, both in the wider litera- ture, and through our informal look at Asian data, that increasing trade finance activity 262 The World Bank Research Observer, vol. 40, no. 2 (2025) (and easing constraints) could improve SME outcomes; this in itself presents possible future research opportunities. We note that while available proxies provide an overall picture of the trade finance situation in a country, they are unable to distinguish between demand side and supply side constraints to trade finance. It is possible that the trade finance gap exists due ei- ther to (a) a low demand situation wherein firms are engaging in fewer transactions or simply unaware of the presence of the instruments (i.e., demand constraints) or (b) the Downloaded from https://academic.oup.com/wbro/article/40/2/261/7670862 by Laura Mowry user on 05 August 2025 fact that banks or financial institutions are less willing or able to provide finance to firms that are participating in international trade activities (i.e., supply constraints). While these two sources of the trade finance gap have distinct policy implications, available data on the trade finance gap may reflect either type of constraint or an inter- action of both.3 Future research and data collection should strive to create measures that can distinguish between demand and supply side trade finance constraints. This paper is structured as follows: The next section presents a brief and selective re- view of the relevant literature relating to financial constraints, international trade and economic activity. We then present a conceptual framework for assessing and catego- rizing trade finance activity and an analysis of the available indicators used to measure such activity. We follow up with some stylized facts pertaining to trade finance for the ASEAN region before presenting some conclusions and possible avenues for future re- search. Finance, Trade, and Growth: Brief Literature Survey The issue of trade finance can be viewed as part of the broader literature on the rela- tionships between finance, trade, and economic growth. King and Levine (1993) exam- ined the impact of financial development on real per capita GDP growth and found that financial services encourage growth by increasing capital accumulation as well as improving the efficiency of its use. Furthermore, trade seems to be an important link in this relationship. Facilitating the exchange of goods and services, including for inter- national trade, is one of several ways in which financial development induces higher growth (Levine 2004). Svaleryd and Vlachos (2005) and Hur et al. (2006) find that fi- nancial development affects the level of industrial specialization and leads to higher exports. Becker et al. (2013) find that financial development is associated with greater exports and imports. Castello and Gruber (2015) show that the trade-to-GDP ratio falls following a negative credit shock. Chan (2019) shows that financially constrained firms are more likely to use trade intermediaries in exporting, increasing costs and reducing competitiveness of exporters. The important role of finance in international trade is demonstrated empirically by papers that have studied the aftermath of large shocks that reduced the availability of finance, and in particular the 2007–08 global financial crisis.4 Cavoli, Christian, and Shrestha 263 Looking more specifically at trade finance issues, Hwang and Im (2013) reveal that the reaction of trade finance to shocks to financial variables (exchange rate volatil- ity and domestic and global liquidity constraints) is negative and persistent. Likewise, Del Prete and Federico (2014) find that credit supply shocks matter for financially con- strained exporters, although not just via specific constraints on trade finance but from reductions in the availability of ordinary lending. Antras and Foley (2015) report that the way trade is financed shapes the impact of crises. Importers transacting on cash Downloaded from https://academic.oup.com/wbro/article/40/2/261/7670862 by Laura Mowry user on 05 August 2025 in advance terms before the crisis reduce their purchases the most. Niepmann and Schmidt-Eisenlohr (2017a) show that the crisis of 2008 impacted firms’ trade finance choices, where letters of credit (conducted through banks) were used more than non- bank forms of trade finance. Several studies have specifically examined the impact of trade finance constraints on trade. Siregar (2010) and Korinek et al. (2010)report a robust positive relationship between trade credit and trade. Auboin and Engemann (2014) find that global down- turns in output and global liquidity negatively impacted the availability of trade credit and, in turn, trade. Wang and Ronci (2006) reveal a strong positive relationship between external short-term credit and both import and export flows at the country level. Bank for International Settlements (2014) found that while the individual impact of trade finance on trade flows is not statistically significant, it became robustly positive once interacted with a global financial crisis variable. Niepmann and Schmidt-Eisenlohr (2017b) show that a one-standard deviation neg- ative shock to a country’s letter-of-credit supply reduces US exports to that country by 1.5 standard deviations. This effect more than doubles during the 2007–09 financial crisis, suggesting that letters of credit may explain the collapse in exports in 2008–2009. The literature also points to other factors that explain magnitude of trade finance constraints, which may be categorized into four (very) broad groups as follows: First, bank-related factors: BIS (2014) and Garralda and Vasishtha (2019) find that the bank capital to total assets ratio impacts trade finance flows positively. Kim et al. (2019) suggest that the most prominent bank-related barriers to trade finance are high transaction costs/low fee income (reported by 59 percent of banks), and an is- suing bank’s low credit ratings (51 percent). From surveying companies seeking trade finance, the main reported cause of a higher rejection rate is their inability to fulfil standard bank requirements such as collateral, or documentation of valid company records. Second, regulatory and compliance factors: Di Caprio et al. (2016) find that con- cerns with anti-money laundering (AML) (90 percent of respondents reported con- cerns), Basel III (77 percent), know your customer (KYC) regulations (76 percent) are possible inhibitors. Third, governance and institutional factors: Antras and Foley (2015) find that im- porters from countries with weak contract enforcement will typically finance trans- actions from their end—cash in advance arrangements, rather than open account or 264 The World Bank Research Observer, vol. 40, no. 2 (2025) letter of credit. Niepmann and Schmidt-Eisenlohr (2017a) show that the 2007/2008 financial crisis affected firms’ payment choices, pushing them to use more letters of credit.5 Ellingsen and Vlachos (2009) examine the impact on trade finance arrange- ments during crises. It is found that trade finance markets tend to be impacted more when transactions take place with countries where there is less trust (in the buyer’s bank). The final group examines the impact of innovations in digital finance and fintech Downloaded from https://academic.oup.com/wbro/article/40/2/261/7670862 by Laura Mowry user on 05 August 2025 on trade finance and the trade finance gap. Auboin and DiCaprio (2017) find that dig- itization of banks and the rise of fintech have potential to shrink trade finance gaps, but the impact of these innovations currently remains marginal due to a lack of famil- iarity with the technology. A similar story emerges from the perspective of banks. Kim et al. (2019) report high cost of technology adoption as the most cited reason (57 per- cent) for banks to not use technology. Rice et al. (2020) find that fintech indicators (the percentage of the adult population that pays bills online and uses the internet) sig- nificantly impact the number of active correspondent banks—itself a proxy for trade finance. Cornelli et al. (2019) find that the complexity and paperwork-intensive nature of trade finance transactions have made distributed ledger technologies an attractive option for financing SMEs in the Asia and the Pacific region. The Architecture of Trade Finance In this section, we develop a conceptual framework to understand the nature of trade finance. The trade finance gap that is measured by the ADB, and whose existence forms a large part of the motivation for this paper, is derived from activity in trade finance markets from the point of view of both the supply and demand side (ADB 2021). In other words, by surveying both banks and firms, the gap itself captures conditions relevant to both parties, and, though they are not made explicit in the calculation, we can infer that trade finance constraints exist—firms cannot obtain sufficient finance and banks are unable or unwilling to supply it in sufficient volumes. In the following section, when we discuss various indicators that may proxy for trade finance, we are hampered by an inability to make such distinctions, so we focus in that section on the level of trade finance activity; taking the view that higher levels of activity in markets where trade finance takes place may imply that any constraints that exist are lower for both sides of the transaction. As such, we detail the nature of trade finance instruments such that we can obtain a sense of how these transactions might occur. An understanding of the relationships across various actors in the trade finance architecture provides a framework for analy- sis that ultimately aids in developing policies to expand trade finance for SMEs. Trade finance activity depends upon a nexus of relationships between various institutions, which collectively attempt to mitigate the risks inherent to international trade activ- ities and address the frictions they cause. As noted in earlier sections, many trade Cavoli, Christian, and Shrestha 265 Figure 1. The Trade Finance Landscape Downloaded from https://academic.oup.com/wbro/article/40/2/261/7670862 by Laura Mowry user on 05 August 2025 Source: Authors’ illustration. finance instruments are available. Underlying these instruments are relationships between various actors in the trade finance ecosystem. One important distinction be- tween trade finance and other forms of finance is that the relationships that underpin them are cross-border in nature. The key players in this trade finance ecosystem include importing firms, export- ing firms, banks in importing country, banks in exporting country, financial service providers, regulators, and multilateral development banks. Figure 1 displays a simpli- fied version of some of these relationships.6 First, we have firm-to-firm relationship between suppliers and buyers. About 60 per- cent of global exports are conducted on open-account terms (ADB 2019), where sup- pliers agree on a commercial contract with buyers, deliver the goods to the buyers, and then receive a clean payment7 from the buyers via a banking transfer by an agreed due date. In doing so, suppliers essentially extend a trade credit to the buyers. This requires a pre-existing relationship between firms across borders, something that is rarer for SMEs than for larger organizations such as multinationals. An increasingly important subset of open-account trade is the supply chain finance (SCF) wherein an open account trade is intermediated by a third-party financier. This financier may be banks or non-bank financial institution (e.g., factoring compa- nies). The four most popular SCF instruments (accounting for 90 percent of all SCF) 266 The World Bank Research Observer, vol. 40, no. 2 (2025) are factoring, receivables financing, payables financing, and forfaiting. Some of these instruments (e.g., forfaiting) can be repackaged and traded in a secondary market. Sup- pliers have incentive to utilize SCF as it mitigates the risks of non-payment and allows them to receive the payment earlier and have better working capital flexibility. Bank-to-bank relationship is another prominent feature of trade finance architec- ture. Facilitating payment for international trade activity requires a bank in the sup- plier’s country to enter a correspondent relationship with the bank in the buyer’s coun- Downloaded from https://academic.oup.com/wbro/article/40/2/261/7670862 by Laura Mowry user on 05 August 2025 try. These banks can take up various roles, ranging from issuing bank, confirming bank, advising bank, and negotiating bank, depending on the specific instrument involved. These roles can be assumed by a same global bank or by different physical banks in both countries. The cutback in correspondent banking relationships observed globally (Bank for International Settlements 2016) in the past decade has created further diffi- culties for financing trade activities. Forty percent of global trade is conducted via traditional bank-intermediated trade finance instruments such as Letter of Credit (LC) and Documentary Collection (DC) (ADB 2019). This typically requires a correspondence between banks in both the sup- plier’s and buyer’s country, through which the bank provides suppliers a guarantee for the payment obligations from the buyers by underwriting the payment with exchanges of shipping documents. Bank-intermediated trade finance is more costly and less flex- ible than open account trade finance, but it offers greater protection for suppliers, and is generally preferred for trade activities involving riskier clients or destinations. For SMEs, availability of banks that can provide LC services becomes crucial for their in- ternational expansion. In bank-to-firm relationship, commercial banks may provide direct trade loan for ex- porters or importers. Furthermore, banks also perform customers due diligence (CDD) on firms whom they finance. Through a CDD process, banks typically request infor- mation regarding Know-Your-Customers (KYC), Anti-Money Laundering (AML), and Counter Financing of Terrorism (CFT) measures to ensure they stay compliant to reg- ulations in these areas. This is due to the existence of regulator-to-bank relationship, in which global regulators publish regulatory guidelines or frameworks covering CDD- related measures on KYC, AML, CFT, as well as things pertaining to banking prudence, such as Basel III rule on capital requirement. In addition, jurisdiction-specific regula- tors supervise banks, check their compliance on the measures above, and sometimes impose penalties upon their violations. Risk of non-payment is among the most crucial features to mitigate in a typical in- ternational trade transaction. Undersupply of trade finance can partially be explained by the high risk of non-payment inherent to certain segments of trade perceived as risky (e.g., SMEs in less developed countries). This is the reason for why insurance and guarantee play an important role in the trade finance architecture. In insurer-to-insuree relationship, there are generally three types of insurers (private, public, multilateral organizations) offering protection for two types of insurees ( firms Cavoli, Christian, and Shrestha 267 and finance providers). For example, some domestic or global private insurance firms offer trade credit insurance for exporters to compensate them in case importers de- fault on the payment. Meanwhile, the public sector, typically represented by national export credit agencies (ECAs) or export-import banks, also offers trade credit insur- ance and/or guarantees programs for commercial banks, with the aim of sharing the risk burden and increasing their incentives to finance trade transactions of the other- wise excluded client segments such as SMEs. They can also offer the same thing directly Downloaded from https://academic.oup.com/wbro/article/40/2/261/7670862 by Laura Mowry user on 05 August 2025 to the exporting firms or through the firm representatives, such as KSURE in the Re- public of Korea (henceforth Korea). In some cases, federal governments also play a role as a reinsurer for national ECAs. Finally, multilateral development banks or organiza- tions (MDBO), such as Asian Development Bank (ADB) or International Finance Cor- poration (IFC), have been providing similar types of insurance and guarantee either to banks issuing the LC or to financiers of open-account trade (i.e., SCF providers). In government-to-bank/firm relationship, governments sometimes provide a trade loan subsidy to local or national banks, as well as an export loan or working capital loan aimed directly and specifically at SMEs, which represent another alternative source of financing for firms to participate in international trade. Measuring Trade Finance While there are a number of different variables that have been used as measures and proxies for trade finance (see below), there is no systematic framework or comprehen- sive dataset capturing of the main instruments of trade finance. Auboin (2021, p. 3) in referring to this, describes a “great paucity of ‘hard’ trade finance statistics.” IMF (2018) notes that “trade finance encompasses a wide range of financial instruments that span more than one of the standard financial account classifications in the existing macroe- conomic statistics.” The diverse nature of the relationships between the various actors in trade finance, as depicted in Figure 1, confirms this. Table 1 illustrates this scattered nature of the trade finance data by providing a com- pilation of various trade finance indicators, subject to the availability of the data. It classifies various trade finance instruments under the aforementioned relationships in the trade finance architecture. This framework can be extended to assess the relative strength of relationships among trade finance actors and inform the data collection gap. It is worth noting that table 1 only captures financial instruments specifically for trade activities, and it leaves out general/all-purpose financial indicators, which are more readily available. First, interfirm trade credit represents a direct firm-to-firm relationship. These are arrangements between firms (importers and exporters) that provide for how trade will be financed directly (without the help of an intermediary). These may include cash-in-advance, or open account arrangements. Unfortunately, while this relation- ship represents about 60 percent of global merchandise export, the data availability is 268 The World Bank Research Observer, vol. 40, no. 2 (2025) Table 1. Data Mapping of Trade Finance Indicators ASEAN + 6 # Relationship Indicators Source Availability? 1 Firm-to-Firm: Interfirm trade credit: Direct Open account N/A. SWIFT or BIS∗ Sparse Cash in advance N/A. SWIFT or BIS∗ Sparse 2 Firm-to-Firm: Traditional trade finance: Cavoli, Christian, and Shrestha Intermediated Letter of Credits (L/Cs) SWIFT (MT 700) Extensive Documentary Collections (D/Cs) SWIFT (MT 400) Extensive Supply chain finance (SCF): Factoring Factoring Chain International Extensive Forfaiting Financial institutions (FIs) Sparse Receivables/payables financing Financial institutions (FIs) Sparse Other supply chain instruments Financial institutions (FIs) Sparse 3 Bank-to-Bank Banking correspondence relationships and statistics BIS, IMF Extensive Cross-border bank claims or liabilities BIS Extensive 4 Bank-to-Firm∗ Trade-specific loan or credit for firms Domestic sources/FIs Sparse Working capital financing for export Domestic sources/FIs Sparse Trade finance rejection rates Survey: ADB or ICC Moderate Customer due diligence process & monitoring Survey or FIs Sparse 5 Regulator-to-Bank Regulatory strictness (Basel III, AML, KYC, CFT, etc.) – Sparse Banks’ compliance cost N/A. Survey or FIs Sparse 6 Insurer-to-Insuree Export credit insurance (ECI): Public: ECI from national export credit agencies (ECAs) Domestic sources when available Moderate Privately sourced ECI Berne Union Extensive Reinsurance or guarantees for banks, non-bank FIs or ECAs Domestic sources/Int’l organization Sparse International organization’s programs (e.g., ADB, WTO, IFC, etc.) International organization Sparse Risk participation agreements or similar measures International organization Sparse Revolving credit facility or similar measures International organization Sparse Other forms of support, especially for local financial institutions International organization Sparse 269 Downloaded from https://academic.oup.com/wbro/article/40/2/261/7670862 by Laura Mowry user on 05 August 2025 270 Table 1. Continued ASEAN + 6 # Relationship Indicators Source Availability? 7 Government-to- Direct loan or subsidy to banks/FIs assisting trade Domestic sources when available Sparse Bank or Firm Credit for firms or SMEs participating in trade Domestic sources when available Sparse Note: Extensive = cover all or most countries, time period is frequent; Moderate = cover some countries, time period is not very frequent; Sparse = cover few countries or not country-specific, time period is not frequent or one-offs. In some cases, close to non-existent. ∗ Detailed and systematic data of trade credit is currently unavailable. Nevertheless, trade credit flow can be roughly approximated by a combination of several types of SWIFT messages that deal with cross-border payment orders, such as MT103 (single customer credit transfer) and MT202 (interbank payment), and the more specifically trade-related payment advice of MT400. However, it is extremely important to note here that SWIFT messages traffic is a valid proxy for trade credit volume only to the extent to which they reveal anything about the underlying transactions. Unfortunately, given the diversity (both trade- and non-trade-related) of transaction types involving those messages, it remains unclear what that extent is, and thus how reliable of a proxy for trade credit they really are. In addition, BIS also compiles statistics on credit to private non-financial corporations in 44 economies, including both domestic and cross-border credit. With similar caveat as above, this could also serve as a rough proxy for trade credit. The World Bank Research Observer, vol. 40, no. 2 (2025) Downloaded from https://academic.oup.com/wbro/article/40/2/261/7670862 by Laura Mowry user on 05 August 2025 scarce. However, some types of messages through the Society for Worldwide Interbank Financial Telecommunications (SWIFT) and credit statistics from the BIS can roughly approximate trade credit with a caveat, as explained in table 1. The remaining 40 percent of trade activities are intermediated or aided in one way or another by banks or other finance providers (e.g., factoring companies, insurers). Some data are available here. As mentioned in the previous section, one of the better- known instruments of trade finance is the letter of credits (L/Cs). This is an off-balance Downloaded from https://academic.oup.com/wbro/article/40/2/261/7670862 by Laura Mowry user on 05 August 2025 sheet instrument whereby a bank makes a payment to an exporter on behalf of an im- porter once delivery of goods is confirmed. While 91 percent of L/Cs are used for cross- border transactions, these and other documentary credits are not recorded in macroe- conomic statistics (see Niepmann and Schmidt-Eisenlohr 2013, IMF 2018). However, the traffic of LCs and DCs are recorded by SWIFT as trade finance messages. It records messages sent and received by banks relating to trade finance. The SWIFT network collects data on the number of payment messages, and their value. Specific data is col- lected on trade finance related instruments; MT 700 is a data source for documentary credit such as letters of credit between banks, while MT 798 are messages for firm to bank documentary flows (Auboin 2021). Another type of intermediated trade finance is a prominent form of supply chain fi- nance called factoring (see Auboin et al. 2016). Factoring involves the selling of a firm’s accounts receivable to a third party ( factor) who assumes the credit risk for those re- ceivables. This helps to address the needs of both suppliers and buyers; a supplier would prefer to receive payment when the items are shipped whereas the buyer would prefer to pay when in receipt of the items. The factor receives payment from the buyer on delivery who uses the proceeds to pay the advance made to the seller. The data are provided by Factor Chain International.8 Intermediated trade finance also heavily involves a bank-to-bank relationship, which is captured by correspondent banking statistics. Correspondence banking is an ar- rangement where a bank (correspondent) can hold deposits for client banks and pro- vide services such as cross-border payments for trade finance (Rice et al. 2020). A lacking or declining banking correspondence relationship in a country is often trans- lated into greater difficulty of conducting payment (and hence trade) with firms in that country. Much of this information is recorded by SWIFT. In addition, there are also data sources that provide some overlap with payment messaging, in the form of bank- intermediated finance flows, which is available in the BIS’ Locational Banking Statis- tics. These involve various measures of cross border loans that capture foreign claims and liabilities on banks for the purposes of trade finance. This overlap also exists with correspondent bank relationships; as Rice et al. (2020, p. 2) point out, “a cross border payment from one bank to another identifies a correspondent bank relationship.” The data for bank-to-firm relationship is generated by the banks or official domestic sources when available. The data on the volume of trade-specific credit delivered to firms in a country is generally sparse, although some banks might have this informa- Cavoli, Christian, and Shrestha 271 tion. One publicly available indicator, however, is the trade finance rejection rates, which measures the proportion of banks’ rejection of firms’ trade finance applications. These are captured by the Asian Development Bank (ADB) through surveys of banks as well as firms (Di Caprio et al. 2016, Kim et al. 2019). Kim et al. (2019) report findings from 2019 in which 112 banks from 47 countries, 336 firms from 68 countries, as well as ex- port credit agencies and forfeiters, were surveyed. The banks are surveyed on, among other characterizations, the proportion and value of trade finance applications that Downloaded from https://academic.oup.com/wbro/article/40/2/261/7670862 by Laura Mowry user on 05 August 2025 are rejected as well as the details about the nature of the counterparties. Nevertheless, cross-country or cross-time comparison is difficult, given the nature of the survey data. For insurer-to-insuree relationship, there exists extensive data on export credit insur- ance. These are data pertaining to insured credit exposures including bank credit and interim loans. They are available from the Berne Union members’ direct insurance or lending. The data are stock data—the total outstanding long-term and medium-term exposures. Meanwhile, publicly provided export credit insurance is typically delivered by export credit agencies (ECAs) or other institutions with a similar function. The data is sparse, relying on domestic official sources when available in rare cases. Finally, an- other important feature is the reinsurance, in which either governments or multilat- eral organizations, programs such as ADB’s Trade Facilitation Program or IFC’s Global Trade Finance Program, insure local banks, export credit agencies, non-bank finance providers, or private insurers that disburse trade finance instruments. However, the data for this is hard to find, and mostly reserved in the multilateral organizations who hold such programs. A common refrain we note from this observation is that most of these trade finance data are generated by financial institutions, which operate on the supply side of the trade finance market. There is generally even less information available on the demand side—those generated by firms who wish to engage in international trade. The ADB’s measure of the gap for the most part captures the supply constraints better since only trading firms (including SMEs) in need9 of trade financing were included in the survey. However, many of the other available trade finance indicators that we have detailed rely predominantly on activity in the various instruments and cannot inherently dis- tinguish between the two constraints. To date, there is still a lack of studies evaluating the extent to which each type of constraint manifests into trade finance gap and the in- teraction between the two, especially in the specific context of SMEs. In broad terms, however, those indicators pertaining to bank activity are likely to speak more to supply- side constraints, while those that related to firms are more likely to pick demand char- acteristics, although this represents quite a crude distinction. In fact, many external factors such as crises, regulatory issues, and supply chain considerations potentially impact both sides simultaneously (Dornel et al. 2021). These are nonetheless impor- tant indicators, since data recorded under these instruments represents evidence of activity, or otherwise, in these markets. According to IMF (2018), this still represents a challenge with respect to trade finance markets in that these instruments help gauge the size of such markets. 272 The World Bank Research Observer, vol. 40, no. 2 (2025) Trade Finance Markets, SMEs and Trade: A Summary of Key Rela- tionships with Reference to Asia While trade finance constraints exist in all regions, we have chosen to use Asia, and ASEAN countries more specifically, to illustrate the main issues and key relationships for the reasons outlined in the literature section above. As a region with sophisticated international production networks and strong trade liberalization through the recent Downloaded from https://academic.oup.com/wbro/article/40/2/261/7670862 by Laura Mowry user on 05 August 2025 passing of the Regional Comprehensive Economic Partnership (RCEP), there is con- siderable scope for ASEAN and East Asian SMEs to participate in international trade. However, lack of access to trade finance could significantly curtail the opportunities available to SMEs. This section applies the framework presented in the previous sec- tion to understand the trade finance ecosystem in ASEAN and East Asia. Furthermore, by way of illustrating the analytical approach that one could take, we present some stylized facts about the possible nexus between trade finance and SME outcomes as a possible avenue for future research. As indicated in table 1, regularly collected, directly comparable, country-specific data on trade finance instruments are in most cases sparse for ASEAN + 6 countries. Such a data gap presents a unique challenge in conducting cross-country empirical analysis on trade finance in this region. Despite such limitations, table 1 also shows that there currently exist some indicators for which the data availability is extensive, such as letters of credit, factoring, correspondence banking, and export credit insur- ance. While they do not represent the entirety of trade finance volume, they are rou- tinely used in the literature as proxies for trade finance availability. What follows are some observations pertaining to the trade finance landscape for ASEAN economies for the measures presented above, subject to the availability of data. The first is total credit outstanding from banks to the nonfinancial sector as a percent- age of GDP from the Bank for International Settlements (BIS). The data is available only for nine East Asian countries: Australia, China, Japan, Korea, Indonesia, Malaysia, New Zealand, Singapore, and Thailand. It is worth adding that the credit data provided here is not only for international trade, but also relates to all credit flows. Among ASEAN countries, the amount of credit outstanding is highest for Singapore, and reflects Sin- gapore’s prime position as a destination for credit flows. On the other hand, Indonesia’s outstanding credit is only 23 percent of GDP over the period, indicating weak credit availability and hence weak bank-to-firm relationships. We can also compare the extent of outstanding credit for the sample of ASEAN coun- tries with those from other countries in the Asia-Pacific region; namely China, Japan, and Korea, and Australia and New Zealand (Figure 2). Outstanding credit for Singapore is higher than the rest, except for China, while outstanding credit for the other ASEAN countries is generally lower, except for Malaysia, which is broadly similar to Australia and New Zealand. Cavoli, Christian, and Shrestha 273 Figure 2. Total Credit to Nonfinancial Firms—ASEAN Comparison Downloaded from https://academic.oup.com/wbro/article/40/2/261/7670862 by Laura Mowry user on 05 August 2025 Source: Bank for International Settlements. The next proxies for trade finance are cross-border claims and liabilities from global banks to non-bank counterparties. These claims are in USD and are taken from the BIS locational banking statistics database. Again, these positions are not only for inter- national trade but are a good source of information about the ease with which cross- border flows take place. Figures 4 and 5 present averages of claims and liabilities re- spectively for each country for 2013–2019. Singapore records both the highest amounts and growth rates, with high levels of claim being recorded against Indonesian coun- terparties. The remainder of the ASEAN countries sampled are relatively low. Figures 3 and 4 show the dynamic properties of each outstanding amount (with Singapore omit- ted) and we can see that there has been a general increase in cross border activities for more countries during that time. The next observation pertain to factoring activities. These relate more specifically to trade finance and are available for five ASEAN countries (Indonesia, Malaysia, Sin- gapore, Thailand, and Vietnam). Table 2 presents international factoring turnover, as well as the proportion of international factoring to total factoring by ASEAN coun- try. When we observe the international factoring turnover data, we see that Singapore has the highest rate—indicating a high level of sophistication in its banking markets and general pro-business environment. For the percentage of international to total 274 The World Bank Research Observer, vol. 40, no. 2 (2025) Figure 3. Cross Border Claims and Liabilities for ASEAN (Average 2013–19) Downloaded from https://academic.oup.com/wbro/article/40/2/261/7670862 by Laura Mowry user on 05 August 2025 Source: Bank for International Settlements. Figure 4. Cross Border Claims (a) and liabilities (b) ASEAN (2013–19) Source: Bank for International Settlements. factoring, Vietnam rates the highest. This suggests that the overwhelming majority of factoring activity is for domestic rather than foreign trade for most countries except Vietnam and, to a lesser extent, Singapore. The final observation is on the extent of export insurance as reported by the Berne Union. The data is available for eight ASEAN countries except Brunei and Cambodia and most of East Asia. Figure 5 presents a comparison with other countries in the Asia Pacific. Among ASEAN, Singapore, as well as Indonesia and Vietnam, are high. As with the credit data above, China records the highest levels with the highest ASEAN coun- tries exhibiting similar exposures to Japan and Korea. From our observation of the available data, Singapore records materially higher ac- tivity in trade finance and related markets. Vietnam presents as having a high level of activity also. Cavoli, Christian, and Shrestha 275 Table 2. International Factoring Year Int Int factor share (to total) Year Int Int factor share (to total) Indonesia 2013 11 1.34% China 2013 82,677 21.86% 2014 10 1.23% 2014 144,529 35.59% 2015 2 0.29% 2015 126,279 35.79% 2016 2 0.29% 2016 64,419 21.36% 2017 2 0.29% 2017 64,803 15.98% Downloaded from https://academic.oup.com/wbro/article/40/2/261/7670862 by Laura Mowry user on 05 August 2025 2019 137 29.91% 2018 39,789 9.67% 2019 40,350 10.00% Malaysia 2013 357 20.03% 2014 357 20.03% Japan 2013 830 1.07% 2015 230 69.70% 2014 660 1.29% 2016 657 43.03% 2015 1,055 1.95% 2017 330 20.00% 2016 882 1.78% 2018 72 1.61% 2017 813 2.18% 2019 72 1.61% 2018 7,213 14.62% 2019 1,303 2.64% Singapore 2013 3,440 34.50% 2014 8,086 21.37% Korea 2013 5,000 40.51% 2015 16,700 42.93% 2014 5,150 40.51% 2016 21,000 51.85% 2015 5,304 40.51% 2017 18,700 42.50% 2016 5,728 40.50% 2018 18,700 42.50% 2017 5,299 40.47% 2019 16,830 42.50% 2018 9,232 36.00% 2019 9,694 36.00% Thailand 2013 36 1.08% 2014 44 1.06% India 2013 240 4.58% 2015 48 1.09% 2014 840 19.35% 2016 150 2.83% 2015 1,200 32.43% 2017 150 2.68% 2016 388 10.00% 2018 0 0.00% 2017 427 10.00% 2019 0 0.00% 2018 532 11.74% 2019 589 11.57% Viet Nam 2013 80 80.00% 2014 80 80.00% 2015 285 85.07% 2016 492 74.77% 2017 300 42.86% 2018 1,100 100.00% 2019 1,100 100.00% Source: Factor Chain International. 276 The World Bank Research Observer, vol. 40, no. 2 (2025) Figure 5. Export Credit Insurance—Comparison Downloaded from https://academic.oup.com/wbro/article/40/2/261/7670862 by Laura Mowry user on 05 August 2025 Source: Berne Union. Trade Finance and SME Trade Activity Using the trade finance measures presented above, the following presents a brief eval- uation of the relationship between trade finance and some general SME outcomes, as well as between trade finance and trade outcomes, for ASEAN countries (subject to data availability for each measure). SME activity is quite high in ASEAN. Table 3 shows the number of SMEs and the extent of SME employment for ASEAN using data from the ADB SME monitor (ADB 2020). Indonesia is most exposed to SME activity with over 60 million SMEs employing some 115 million people. This is naturally going to reflect the country’s size overall. However, from these numbers we can also denote the average employment per SME by dividing the second column by the first. This offers a sense of the scale of SME operation in each country. In Indonesia, each firm employs almost two people, while each of Vietnam and Singapore’s SMEs employ approximately 11.6 and 10 people respectively. Indonesia also has the highest proportion of people employed in SMEs with nearly 97 percent of total employed people, while the ratio is relatively low for Vietnam. Cavoli, Christian, and Shrestha 277 Table 3. Small- and Medium-Sized Enterprises, Employment, ASEAN Country Number of SMEs SME Employment SME Employment to Total Brunei Darussalam 5,615 65,444 56.30 Cambodia 512,780 1,345,100 71.75 Indonesia 60,410,156 115,211,574 96.95 Lao PDR 124,539 472,380 82.63 Malaysia 907,065 – 63.86 Downloaded from https://academic.oup.com/wbro/article/40/2/261/7670862 by Laura Mowry user on 05 August 2025 Myanmar 54,990 – – Philippines 934,646 4,993,807 62.90 Singapore 254,217 2,483,333 72.34 Thailand 2,899,336 11,908,623 81.31 Viet Nam 470,900 5,592,662 42.33 Source: Asian Development Bank (2020), Asia Small and Medium-Sized Enterprise Monitor 2020—Volume I: Table 4. Small- and Medium-Sized Enterprises, GDP, Selected ASEAN Countries Country SME GDP (USD millions) SME Share of GDP Brunei Darussalam 3,500 26.68 Indonesia 496,547 60.43 Malaysia 112,971 36.87 Singapore 141,280 46.91 Thailand 176,068 41.19 Source: Asian Development Bank (2020), Asia Small and Medium-Sized Enterprise Monitor 2020—Volume I: Country and Regional Reviews (October). Available at http://dx.doi.org/10.22617/TCS200290-2. Table 4 presents SME GDP and the share of SME GDP to total GDP for available ASEAN countries from ADB (2020). Indonesia (60.43 percent) has a relatively high in- volvement of SMEs in economic activity. The other countries for which data is available show that the SME to total GDP ratio is around 1:3 to 1:2. SME Finance in ASEAN Table 5 shows some data derived from The World Bank’s Enterprise Surveys on fi- nancial indicators of ASEAN firms, distinguished by their size and exporting status. For each indicator, we present three rows of statistics. The first of these pertains to all firms. The second row is for SMEs, and the third is for SMEs who are exporters. We show data for eight ASEAN Member States, excluding Brunei and Singapore due to data un- availability. For comparison, we also include averages for all countries and for ASEAN overall. These data do not provide direct evidence of trade finance, but overall access to finance for SMEs. 278 The World Bank Research Observer, vol. 40, no. 2 (2025) Table 5. Selected Indicators of ASEAN Firms’ Access to Finance Indicator ALL SEA CA ID LA MA MM PH TH VN Percent of firms with a bank loan or 33.2 29.4 15.6 32.1 26.2 37.2 18.3 27.9 14.3 48.2 line of credit 29.9 26.3 16.8 28.3 24.2 34.0 16.3 25.1 11.6 45.0 40.9 35.4 16.7 43.0 23.7 40.4 23.8 24.3 23.2 51.1 Percent of firms not needing a loan 44.4 42.8 45.0 34.8 53.0 37.3 54.0 52.1 34.5 44.1 44.9 44.5 43.4 34.2 54.2 39.4 54.5 55.3 37.4 44.9 Downloaded from https://academic.oup.com/wbro/article/40/2/261/7670862 by Laura Mowry user on 05 August 2025 45.1 39.8 46.7 41.8 57.9 29.4 38.1 57.9 31.7 35.0 Percent of firms applying for new 21.9 20.4 12.6 13.0 20.6 25.3 13.9 18.4 7.9 43.5 loans in the last year 19.4 18.3 13.0 12.1 19.5 23.1 12.0 15.2 6.5 41.0 26.9 31.2 10.7 18.0 21.1 43.9 28.6 13.6 8.2 50.4 Percent of firms whose recent loan 7.2 3.2 2.6 1.9 3.1 1.0 8.3 2.5 3.6 4.1 application was rejected 8.9 4.2 3.0 2.9 3.5 1.5 7.6 4.3 5.7 5.4 5.6 3.0 33.3 0.0 0.0 0.0 0.0 7.7 20.0 4.6 Percent of firms using banks to 30.1 24.8 8.6 25.0 18.0 58.1 11.5 18.7 21.6 33.8 finance investments 27.3 20.7 9.2 21.0 15.4 54.8 9.8 16.9 21.3 30.4 33.3 28.2 7.7 62.5 7.7 48.2 16.7 7.8 46.2 36.8 Proportion of investments (i.e., fixed 17.6 13.3 2.7 9.3 11.9 17.7 6.8 15.1 14.6 18.3 assets) financed by banks (%) 16.1 11.4 2.4 8.4 10.5 19.8 5.5 13.2 15.8 16.0 18.7 13.7 3.9 18.8 7.7 10.7 6.7 6.3 38.5 18.7 Percent of firms using banks to 33.3 32.6 22.5 38.4 30.0 58.2 16.4 14.8 28.8 41.5 finance working capital 30.1 29.4 21.7 32.1 29.2 53.9 14.5 13.9 26.8 39.0 40.7 45.0 13.3 49.4 29.0 73.6 33.3 13.8 43.9 41.6 Percent of firms using supplier or 27.6 22.8 7.0 40.8 5.5 51.0 19.9 7.5 12.3 14.6 customer credit to finance working 26.8 20.4 7.4 35.3 4.6 45.9 20.2 8.4 10.5 14.6 capital 32.8 33.9 6.7 51.9 10.5 67.2 19.1 11.2 14.6 17.5 Proportion of working capital 13.2 12.8 9.2 10.6 15.2 18.7 7.0 7.1 15.9 18.4 financed by banks 12.0 11.7 8.5 9.0 14.8 18.9 6.3 6.6 14.5 15.9 14.9 16.1 3.3 12.9 16.8 19.5 16.0 8.4 24.3 18.6 Percent of firms identifying access to 22.0 12.0 11.7 21.2 21.7 10.4 12.1 10.6 2.3 9.8 finance as a major or very severe 23.6 12.3 12.4 19.3 22.6 10.6 12.3 12.0 2.4 10.7 constraint 21.8 10.7 29.6 9.0 18.4 8.9 15.0 10.1 3.7 12.9 Note: For each indicator, the first, second, and third row represent the calculation results for all firms, SMEs, and export- ing SMEs respectively. ALL = All countries; SEA = ASEAN countries; CA = Cambodia (2016); ID = Indonesia (2015); LA = Laos (2018); MA = Malaysia (2015); MM = Myanmar (2016); PH = Philippines (2015); TH = Thailand (2016); VN = Viet Nam (2015). Source: World Bank Enterprise Survey. The data reveals a generally limited use of external finance among ASEAN firms. Less than 30 percent of ASEAN firms reported having a bank loan/line of credit, and even less among SMEs. In addition, only about one in five ASEAN firms applied for a new loan in the last fiscal year. It is worth noting, however, that this number is higher among exporting SMEs, at 31 percent, than for SMEs in general. This relative under- utilization of bank loans among firms in the region coincides with the fact that as much Cavoli, Christian, and Shrestha 279 as 83 percent of bank loans in ASEAN require some collateral. While the size of the collateral varies across ASEAN Member States, it averages substantially higher than the world average at around 2.5 times the loan amount, with SMEs having to contend with even higher requirements. Table 5 also shows that banks play a less prominent role in meeting firms’ financ- ing needs. Approximately 75 percent of ASEAN SMEs used internal source of funds. The remaining 25 percent used bank loans to finance their working capital, but this in- Downloaded from https://academic.oup.com/wbro/article/40/2/261/7670862 by Laura Mowry user on 05 August 2025 creased to 45 percent for exporting SMEs. Compared to all SMEs, this form of financial engagement is significantly higher for exporting SMEs in Indonesia, Malaysia, Myan- mar, and Thailand. Even among those who used bank loans, bank financing on average was only responsible for less than 14 percent of their working capital and investments spending. This indicates that there is ample room for much needed improvement in international trade in the region, as insufficient working capital is often a prominent factor holding firms (especially SMEs) back from participating in international trade. Another common source of financing working capital for exporting SMEs in Indonesia and Malaysia is credit from suppliers or customers, which over half of the SMEs rely on. Most of the indicators in table 5 suggest that ASEAN SMEs tend to have greater diffi- culties to access finance from external sources, compared to firms in general. Despite this, exporting SMEs in particular seem to be considerably better connected to exter- nal finance than SMEs in general, which likely corresponds to their growth strategy and their ensuing greater need for financing. It is also worth noting the diversity across ASEAN countries, where firms in more developed economies with more established fi- nancial market and inclusion, such as Malaysia, tend to have better access to external finance than those in less developed economies. Why is SME financing low in ASEAN? There could be multiple reasons. For example, Machmud and Huda (2011) examine SME access to finance for Indonesia. They find that the number of SMEs that rely only on external formal sources is only 3 percent of total respondents. The dependency on internal and/or informal financial sources along with external-formal sources for maintaining their businesses may reflect not only the presence of uncertainty but also the high opportunity cost of accessing exter- nal sources. Overall, this picture may indicate that despite having access to external formal sources of finance, most SME respondents in Indonesia still have traditional mindsets in their way of doing business. This also explains the low share of loan inter- est payments in the cost structure. Yoshino and Taghizadeh-Hesary (2018) present a study that analyses the difficulties of Asian SMEs in accessing finance and provide measures for mitigating them. As most Asian countries are bank-dominant economies, with underdeveloped capital markets and lack of venture capital, capital market financing is not a realistic option for SMEs. Those factors identified as presenting difficulties in SMEs accessing finance include: (a) lack of information infrastructure for SMEs, (b) insufficient collateral and high in- terest rate. Some of the identified remedies for tackling SMEs difficulty in accessing 280 The World Bank Research Observer, vol. 40, no. 2 (2025) finance include: (a) credit guarantee schemes (CGS) developed by government, (b) de- velopment of SME credit risk databases, credit bureaus, and SME credit ratings, and (c) specialized banks for SME financing. With this background in mind, Figure 6 examines the association between trade fi- nance and SME share of GDP. The first panel shows a strong positive association be- tween insured export credits and SME share of GDP, suggesting that an increase in trade finance activity may bring about beneficial outcomes for SMEs. The next pan- Downloaded from https://academic.oup.com/wbro/article/40/2/261/7670862 by Laura Mowry user on 05 August 2025 els reveal a positive connection between cross border assets and SME GDP share, but no association between cross border liabilities and SME GDP share. Figure 7 presents scatterplots capturing the relationship between trade finance and SME share of employment (or SME employment to total employment). For all three graphs, which capture insured trade credits, cross border assets, and liabilities, the as- sociation is positive. This implies that the increasing trade finance activity in ASEAN is associated with higher SME employment. The four panels of Figure 8 examine the connection between trade finance and trade openness ([imports + exports]/GDP). The first panel shows the relationship between trade openness and insured export credits. The second looks at trade openness and international factor shares. The third examines the relationship with total credits to nonfinancial corporations (NFCs), while the fourth looks at the connection between trade openness and cross border claims. While all four show a positive association— indicating that greater activity in trade finance is associated with greater international trade—the relationship with total credit to NFCs appears especially strong for the coun- try/years sampled. Generally, trade finance tends to correlate positively with SME GDP share, SME em- ployment share and openness to trade for the sample of ASEAN countries examined. This ought to motivate the need for further research in this area, to establish causal relationships. Such research might include the analysis of the determinants of (various indicators of) trade finance as well as the effects of activity in trade finance markets on a range of economic well-being outcomes. Conclusion and Way Forward This paper assessed issues relating to trade finance with a particular focus on SME ac- cess to trade finance with application to the economies in Asia and the ASEAN region. The available data shows the importance of SMEs in generating economic activity and employment. Yet, they are hampered somewhat by their limited access to credit in gen- eral and trade finance in particular. Existing studies on the relationship between finan- cial development, trade, and economic growth suggest that trade finance gap can hurt growth by limiting SMEs’ participation in international trade. This is often exacerbated during times of economic and financial crisis. Cavoli, Christian, and Shrestha 281 Figure 6. Trade Finance and SME GDP Share Downloaded from https://academic.oup.com/wbro/article/40/2/261/7670862 by Laura Mowry user on 05 August 2025 Source: Authors Calculations. 282 The World Bank Research Observer, vol. 40, no. 2 (2025) Figure 7. Trade Finance and SME Employment Share Downloaded from https://academic.oup.com/wbro/article/40/2/261/7670862 by Laura Mowry user on 05 August 2025 Source: Authors’ Calculations. Cavoli, Christian, and Shrestha 283 Figure 8. Trade Finance and Trade Openness Downloaded from https://academic.oup.com/wbro/article/40/2/261/7670862 by Laura Mowry user on 05 August 2025 Source: Authors’ Calculations. 284 The World Bank Research Observer, vol. 40, no. 2 (2025) We proposed a conceptual framework that relates availability of trade finance to strengths of relationships between different actors in the trade finance architecture, which include firm-to-firm relationships, bank-to-bank relationships, and firm-to- bank relationships. The important roles of government policies and regulations, as well as international development institutions are also discussed. There is currently a widely acknowledged lack of consistent data and an absence of a coherent and coordinated methodology for the measurement and collection of trade Downloaded from https://academic.oup.com/wbro/article/40/2/261/7670862 by Laura Mowry user on 05 August 2025 finance statistics. There is certainly a data gap that could be filled through systematic surveys of banks and firms with countries in order to gather information about the pos- sible sources of, and barriers contributing to, trade finance problems within countries. It is also necessary to develop databases that could distinguish between demand- and supply-side sources of low trade finance activity. While this data issue is no doubt problematic, trade finance does encompass a range of financial products. There are several identified proxy measures which allow for a picture to be painted on certain aspects of the trade finance markets that exist globally. We have presented several such proxies by way of simple application to a sam- ple of ASEAN countries—subject to data availability. From the presented measures, we find that Singapore has the most activity and highest involvement in the trade finance markets. This result is emphatic and perhaps unsurprising given its position within the region as a financial center. The paucity of data does present an opportunity to investigate the relationship be- tween the disparate measures of trade finance. Such work might include categorization of trade finance data according to the types of relationships they represent (as per our conceptual framework), as well as the creation of composite indicators of trade finance using relevant methodologies. Finally, we employed these measures of trade finance activity to see how they corre- late with key indicators of SME activity and trade. Here, we find that some, but not all, trade finance indicators are positively associated with the share of SMEs to GDP, em- ployment, and trade openness for the sample of ASEAN countries that were examined. Further research to establish causal link in this area is warranted. Such research may include analyzing the determinants of the various indicators of trade finance as well as the impact of trade finance activity on economic well-being—generally and for SMEs. Notes Tony Cavoli (corresponding author), is University of South Australia; email: tony.cavoli@unisa.edu.au ; David Christian (david.christian@eria.org) and Rashesh Shrestha (rashesh.shrestha@eria.org) Economic Research Institute for ASEAN and East Asia. We thank the Economic Research Institute for ASEAN and East Asia for generous financial support. We also acknowledge the excellent comments from three referees of the journal; the usual caveats apply. 1. In monetary terms, the WTO reports that in 2018 there was an estimated $18 trillion in global trade flows, as such, there needs to be a trade finance market worth around $14 trillion (WTO and IFC 2019). In Cavoli, Christian, and Shrestha 285 2014, the Bank for International Settlements estimated the global market for trade finance between $6.5 trillion and $8 trillion. Trade finance is estimated to govern 80 percent of international trade transactions (ICC 2020). It involves loans and guarantees from banks that underpin imports and exports—through ei- ther directly providing funding or through unfunded guarantees to the exporter on behalf of the importer. There are a number of different financing contracts through which this can occur (see WTO and IFC 2019, and van Wersch 2019 for a description of the possible arrangements). 2. The 44 percent and 56 percent refer to percentages of SME trade finance proposed and rejected (respectively), relative to total proposals and rejections. It is important to note that SMEs do tend to be more acutely impacted by trade finance issues. This is because, generally speaking, these firms typically Downloaded from https://academic.oup.com/wbro/article/40/2/261/7670862 by Laura Mowry user on 05 August 2025 have limited cash reserves, relatively low access to credit, they have few assets and are less likely to benefit from large scale, general stimulus packages (International Labour Organization 2020). 3. We thank an anonymous reviewer for valuable insights on this issue. 4. See, for instance, Amiti and Weinstein (2011), Bricongne et al. (2012), Behrens, Corcos, and Mion (2013), and Coulibaly, Sapriza, and Zlate (2011), Chor and Manova (2012), Spatareanu et al. (2018), Iacovone et al. (2019). 5. Rather than open account or cash in advance. 6. To this end, IMF (2018, 2019a, 2019b) provide a typology of trade finance instruments and identifies three categories: - Traditional bank intermediated instruments. These include cross border loans to finance im- ports/exports, letters of credit and performance guarantees. - Open account or inter/intra firm trade finance. These include trade credit and advances between affiliated or unaffiliated enterprises. - Supply chain financing and other working capital-related financing. These include receivables pur- chasing such as factoring and loans/advances to suppliers against receivables. 7. Clean payment refers to a banking transfer that is not underwritten by the exchange of shipping documents, which in this case are handled directly between the exporter and importer. 8. The factoring data are found the annual reports from Factor Chain International and can be found here: https://fci.nl/en/annual-review. 9. Demonstrated by the respondent firms’ applications for trade financing. 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