To make our economy truly financially inclusive, there are many things we need to address – from ensuring people are paid fairly to removing all biases from the financial ecosystem. The lending market especially is fraught with biases, and finding ways to ensure that women have equal access to credit and financing products is of paramount importance.
Emma Camilleri, Group HR & Operations Support Director at Creditinfo looks at the challenges to closing the lending gender gap and how to address them.
Though women make up almost 40% of the world’s workforce – particularly in developing economies – around 2.4 billion women are not afforded equal economic opportunities. Women’s involvement in the flow of capital through the economy is less than we might expect. The root of this problem is prejudice at every level – from financial decision making through to cultural factors. While cultural issues may be more difficult to overcome in the near term, governments, banks and credit bureaus can work together to address the structural issues preventing women from accessing finance and contributing to the economy.
The gender pay gap
In certain markets, the gender pay gap is particularly pronounced. A Creditinfo analysis of the Lithuanian market found that of the 81 sectors into which economic activity breaks down, men are paid more than women in 72, and the average pay for men often exceeds women by 30-50%. In sectors, such as air transport, gaming, and gambling, a man’s salary can be up to 127% above their female colleagues. Closing this gap is key to rebalancing the global economy and realising a more financially inclusive world. Work is already being done as part of Environmental, Social and Corporate Governance (ESG) initiatives to provide greater pay transparency, as well as representation of women on company boards.
However, pay issues aside, there are fundamental issues in the lending market that need to be addressed. Women are still disproportionately prevented from accessing credit and business financing compared to their male counterparts. This is where data can provide a way forward.
Disparities in data
For example, in Kenya women have higher average credit scores than men (628 vs 623), yet they have significantly smaller credit footprints (41% vs 59%) and utilisation (82.2% vs 93.9%). This is a marked difference and can have a widespread adverse impact. If women do not have access to financing on a personal level, their spending power and contribution to global annual revenue is significantly diminished. On a professional level, if women business owners can’t access financing, it means they can’t recruit, expand their service or product, or generate new revenues. This only bolsters the economic gender imbalance and will continue to stifle economic growth and development.
Many other developing economies are experiencing the same issues. In Morocco, for example, the lending market similarly favours men, with women only making up 31% of the active borrowing market. This needs to change.
To make our economy work for everyone, these structural barriers to financing need to be dismantled. One of the ways this can be done is through moving to digital lending as it minimises the chance of subjective human intervention in the process and helps to improve overall equality. It’s important that historic bias is not built into today’s credit score system algorithms as using data that reflects bias will sustain the bias. Credit scores need to be as fair as possible to reflect the actual risk of individuals based on real data such as an individual’s cash flow and their ability to pay rent or utility bills.
The role of regulators
Regulators also have a crucial role to play. Depending heavily on debt to income (DTI) in their supervisory rules can reinforce a strong gender bias. Evidence already shows that women’s salaries are lower than men’s salaries. Following DTI rules, large proportions of women can be forced into high-interest-rate lending or pushed out of the formal market and into the informal credit market without legal protection.
Creditinfo’s data shows that this is the case in Latvia, where the credit score is highly predictive of future non-payment and should be a significant element in any credit decision, it is proven to be predictive at all income levels. DTI is much less predictive and would eliminate many lower-income women from formal credit where strict rules around DTI exist.
The best way to start making changes is by using data, whether its ESG information or credit scoring. If we can identify the challenges to closing the lending gender gap and what needs to change then we can begin to address it. We can also measure and manage progress against key performance indicators (KPIs). For lenders, this can be a significant opportunity – having a large section of the economy with good credit scores and low credit utilisation means they can be savvy in how they target new products and services to cater to the needs of nascent markets and generate new revenue streams while tackling financial inclusion.
Ultimately, if the disparity between men’s and women’s access to finance endures, we stifle the potential growth of global economies. Closing the gender gap is not just a ‘nice to have’ – as well as being a moral obligation, it’s essential for the health of the financial services industry and economies more generally. Through de-risking the lending ecosystem, we can make the economy fairer and more sustainable.
