Banking

Is your bank officer gender-biased? The case of SME lending in Turkey

Access to financial services is increasing globally, with over 69 percent of adults worldwide having an account with a financial institution or through a mobile money service, according to the last Global Findex report. However, women are less likely than men to have a financial account. In developing countries, the gender gap has remained stable at 9 percentage points since 2011. This is a challenge for women entrepreneurs, who typically run smaller businesses. Gender disparities in small and medium-size enterprise (SME) lending may be impeding the growth of millions of women-led firms. Some 70 percent of formal women-owned SMEs in developing countries report being shut out by financial institutions or unable to receive financial services on adequate terms to meet their needs , facing an estimated annual credit shortage of $1.5 trillion.

Women-run businesses tend to have a smaller asset base and are more likely to operate in the informal economy — factors that can make it harder for women to meet the requirements for obtaining a loan. In Turkey, for example, 58 percent of loans require collateral when the business is managed by a woman, versus 37 percent when the business is run by a man (Enterprise Survey 2019) . Another reason for the observed gender gap in SME financing could be that even when women-and men-run businesses have identical characteristics, financial institutions discriminate against women entrepreneurs. Our working paper examines a potential driver of these disparities: gender-biased loan officers. Our goal was to determine if gender bias exists in lending decisions and, if so, what is driving the bias — so that adequate policies can be developed to address it.

What did we do?

A new World Bank operation in Turkey focuses on improving access to finance for women-owned enterprises. The Inclusive Access to Finance Project (P163225) provided an ideal testing ground to explore this gender bias issue in more depth. We conducted an experiment on gender bias among loan officers in Turkish banks. Turkey is a particularly interesting country for this analysis, as it has one of the largest gender gaps in financial inclusion in the world. Although the situation has recently improved — 69 percent of adults now have an account in Turkey, up from 57 percent in 2014 — only 54 percent of women have an account, compared with 83 percent of men. This 29 percent gender gap is roughly three times as large as the average gender gap in emerging economies.

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We randomly selected Turkish bank branches after stratification by region, and then one SME loan officer per branch was contacted to participate in a survey. The survey administered to the 77 sampled loan officers included a loan application experiment, which was designed to test the loan officer’s degree of gender bias by asking them to review and make credit decisions on identical fictional loan applications from men and women entrepreneurs.

What we find

We find that 35 percent of loan officers are biased against women applicants, where gender bias is measured as any positive difference between the amount of money allocated to men versus women loan applicants in the experiment. Interestingly, this is about twice as high as the percentage of loan officers who believe that Turkish banks are biased against granting credit to women entrepreneurs versus men entrepreneurs. In the loan allocation experiment, women applicants received approximately $14,000 less. This corresponds to women receiving a 7.5 percent lower loan amount compared with men. The difference remains large and significant even controlling for a range of loan officer and bank branch characteristics.

What can explain this gender bias? Experience in the banking sector emerges as the key explanatory variable. Indeed, each additional year of experience working in the banking sector is associated with a 2 percent reduction in the degree of loan allocation biased against women entrepreneurs. The more experienced a loan officer is, the less likely they are to resort to gender bias in decision making. This relationship does not appear to be driven by age or position within the banking hierarchy; it is associated with years on the job or non-gender biased (or indeed, pro-women applicant) loan officers surviving on the job longer.

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What are the policy implications?

We find that gender bias in SME lending is prevalent and substantial. Moreover, in our context, the main driver of gender bias in SME lending is not an immutable characteristic like the loan officer’s gender. Rather, it is the amount of experience that loan officers have in evaluating loan applications. This is consistent with the use of gender as a “rule of thumb” that loan officers use to evaluate creditworthiness, given limited information and risk aversion. In other words, less experienced loan officers may rely on gender bias as a mental shortcut, while experienced loan officers are more skilled in evaluating loan applications on their merits and thus exhibit less biased decisions. 

Interventions such as sensitization on the prevalence of gender bias among loan officers, promotion of women entrepreneurs’ success stories, and information on the success rate of women-owned SME loans may be useful in overcoming this gender bias. However, our results show that initiatives to help loan officers gain on-the-job skills without addressing gender explicitly can also help.  This could include awarding more time to newer loan officers to review applications or providing higher frequency and higher quality training for less experienced loan officers so that they can better discern loan application quality. Artificial intelligence (AI)-assisted loan application review, whereby the approval process is not automated through an algorithm but where the loan officer can cross-check his or her decision with data from a wider range of sources, may also be beneficial.[1]

Our findings highlight the urgent need for policy solutions to address the impact of gender bias on women entrepreneurs’ ability to obtain capital and grow their businesses. Future research should shed light on the cross-country relevance of our findings and pinpoint other causal mechanisms that may be at play.

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For more information about the study, contact Aletheia Donald ([email protected]). For more information on the Turkey Inclusive Access to Finance Project, contact Alex Pankov ([email protected]).

Thank you to Fannie Delavelle for excellent assistance in preparing this blog.

[1] Fully automated AI in particular is at risk of algorithmic bias. See for example NPR (2017), “Will Using Artificial Intelligence to Make Loans Trade One Kind of Bias for Another?”

Source : blogs.worldbank.org

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