• Hsiao-Hui Lee, S. Alex Yang and Kijin Kim

The Role of FinTech in Mitigating Information Frictions

Micro, small and medium enterprises (MSMEs) in developing countries rely on external finance to sustain their operations and grow their business, both domestically and internationally. However, many MSMEs that could deliver orders successfully still face great challenges in accessing finance. According to the 2017 Trade Finance Gaps, Growth, and Jobs Survey by Asian Development Bank, approximately 40% of worldwide proposal (i.e., firm requests to banks for trade finance) rejections are from Asia and Pacific, among this 40% rejections, MSMEs and mid-cap firms accounts for 74% of rejections, and finally, 36% of these trade finance rejections could have been funded. Many reasons that banks reject trade finance applications lead to the existence of information frictions, including the failure to meet the regulation on Know Your Customer and insufficient collateral or information.

To resolve information frictions, financial institutions have been searching for FinTech tools that enable them to extract more and use better information. Depending on the specific role such technologies play, these technologies can be classified into two categories: information processing technology and information collecting technology. The former refers to technologies that convert a vast amount of raw data that banks own (or could obtain) into useful information in lending decisions, such as advanced analytics and Artificial Intelligence (AI). The latter refers to those that collect additional new data, such as digitalization and automation, biometrics and identity management, and blockchain. The advancement of technology especially benefits MSMEs by responding to their financing needs more efficiently at lower costs. Yet, the role of different types of FinTech tools in facilitating trade is still under-explored in such a context. With a focus on how financial technology can play a role in enhancing access to trade finance for MSMEs, Lee, Yang, and Kim (2019) study how trade finance products can contribute to reducing the unmet demand for trade finance by taking advantage of technology. An intuitive approach is to facilitate trade finance for the rejected trade finance transactions that could have been funded by banks, if more information is available.

Using a game theoretical model, Lee, Yang, and Kim (2019) find that FinTech can help close the trade financing gap by reducing information frictions using information processing technology (Type A) and/or information collecting technology (Type B). The paper finds that both types of FinTech tools help close financing gaps by offering a more accurate signal to identify the good firms that deserve loans. Next, Lee, Yang, and Kim study a bank's investment decisions, and find that the bank's Type A investment increases with the bank's size, profit margin, and the fraction of good firms in the market. The two types of FinTech can be either complements or substitutes while their relationship depends on whether Type B investment can further lower the financing gap or not. Banks invest in Type B if and only if the investment in Type A is sufficiently small (so the two types can be substitutes). Finally, the study investigates the gap between the banks' optimum and social welfare optimum. In other words, a bank will invest in Fintech up to the point where its profit is maximized. However, it may be less than the socially optimal level where the sum of the bank and firm’s payoff is maximized. Due to the double marginalization between the bank and the borrower, the bank's optimal FinTech investment level is lower than the socially optimal level. This calls for additional mechanisms supported by public sectors, including governments and international organizations such as the International Standards Organization (ISO) and the World Customs Organization (WCO) to simulate and complement banks' investment in FinTech. In particular, public sectors can support mechanisms to lower the cost of technology adoption such that it becomes easier and cheaper for banks to adopt FinTech tools. Such mechanisms include (i) developing digital standards and ecosystems to reduce entry barriers for technology adoption, (ii) establishing legal entity identifiers to reduce the time and effort for banks to conduct due diligence, and (iii) implementing rules and legislation for digital trade to lower banks' legal risks for adopting new technologies.

Hsiao-Hui Lee - Department of Management Information Systems, National Chengchi University

S. Alex Yang - London Business School

Kijin Kim - Asian Development Bank (ADB)

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