Digital credit and gender
Understanding gendered and other imbalances in digital credit
Misdirection in magic happens when a magician moves the audience in one direction to keep them from seeing or noticing something else. The key to misdirection is that the audience is unaware of it, and feels that its attention was precisely where it wanted it to be throughout the performance — studying the magician, looking for their sleight of hand. The result of this is that the audience misses how what is happening occurs — creating the illusion of magic.
A major illusion in digital credit is that it is accessible to all, but this does not hold true for women. Theoretically, digitalization should help to significantly reduce the existence and impact of human biases on the distribution, suitability and overall experience of credit. While digital financing has been crucial in moving the needle for financial inclusion, it has equally been limited in its ability to effectively close the gender gap. Granted, social and cultural factors are still huge influences on levels of individual autonomy in financial decision making, with women’s financial activities still largely controlled by either spouses or parents.
Lack of access to digital credit for women is preceded by limited smartphone ownership, compared to men. Even with access to smartphones, and autonomy of choice in digital credit options, women are then faced with credit-scoring algorithms skewed towards men, who are historically the primary consumers of credit. Even more unfortunate is that these algorithms are difficult to detect and regulate.
Various studies report that women default on their loans less frequently than men do. However, this does necessarily mean that they are better at repaying loans than men — although this could also be the case. Alternative reasons could be that lenders approve credit to only low-risk female borrowers, while approving both average and low-risk male borrowers. This means that very few women, and only those with the ability to pay, are cleared for credit. Conversely, more men with relatively higher risk of defaulting are granted credit. Enter micro-finance institutions (MFIs), whose business model enables credit provision to low-income and rural women at scale. Digital credit providers interested in expanding their female clientele could benefit from emulating MFIs when developing digital products.
While internet enabled digital credit platforms such as non-bank Fintech loans may present better value propositions, they also lock out women without internet connectivity. If women-run small enterprises cannot use digital tools, then no data trails can be produced for use by lenders to add value to their businesses. Consequently, female entrepreneurs are more likely to opt out of the credit market due to perceived low creditworthiness.
Finally, and most importantly, is financial education. Without it, male and female borrowers alike will not effectively use digital credit services. Education in this context includes understanding the total cost of the loan, planning for repayment, saving and investing, among other relevant topics.
How can digital credit providers begin to make the environment more accessible for all? Watch this video on our YouTube channel to find out our recommendations for providers.
This blog is the third in a four part series on digital credit. Follow us on social media to get notified as soon as the next and final blog comes out. In case you missed it, read Part 1 and Part 2 of our series. If you liked this, head over to our YouTube channel to watch the corresponding Part 3 video on our Digital Credit study.