Location of things
Nearshoring could relocate some low-cost production and jobs to outside of the developing world, particularly in sectors that are female-dominated, such as textiles.
At the same time, remote services (e.g. banking, credit checks, education, health, insurance, weather info, etc.) can increase equity in access to a range of services vital to women’s economic empowerment (e.g. finance, education, healthcare, etc.).
- Opportunity
- medium
Remote services can increase women’s access to knowledge and resources.
- Risk
- medium
Nearshoring could move some low-cost production (and jobs) outside of the developing world.
Consumer protection and privacy issues could erode women’s independence.
- Opportunity
- low
- Risk
- low
Currently, women in the low and middle-income countries produce substantially less data than men. Women are 10 percent less likely than men to own a mobile phone and 23 percent less likely to use mobile internet. Mobile banking and big data analytics based on data from the internet of things can provide the information necessary to improve credit assessment technologies and increase financial inclusion for women. For example, companies such as Lenddo and EFL use a wide range of data in their credit scoring algorithms, from social media and smartphone records to psychometric tests.
To harness the potential for AI to increase financial inclusion, gender-smart investors could:
- Integrate AI into existing investees’ credit scoring methodology, where possible.
- Invest in innovative companies produce AI for institutions, working with investees to maximise utility and drive down costs to customers.
Sources: https://www.fico.com/blogs/where-and-why-efl-alternative-credit-scores-work https://www.cio.co.ke/mobile-phone-penetration-rises-despite-the-gender-gap-ownership-disparities/
- Opportunity
- medium
- Risk
- medium
Nearshoring could move some low-cost production and jobs to outside of the developing world. Under particular threat are several industries dominated by female employment, such as textiles. McKinsey states: “Tomorrow’s successful apparel companies will be those that take the lead to enhance the apparel value chain on two fronts: nearshoring and automation.”
Gender-smart investors could improve women’s job retainment by supporting investees to partner with stakeholders focused on skills development. This would provide employees in female-dominated sectors at high risk of automation with the skills required by future working environments.
- Opportunity
- low
- Risk
- low
AI has the potential to adapt educational content according to student’s needs, delivering individualised remote learning (e.g. putting greater emphasis on certain topics, repeating things that students have not yet mastered). This could improve the quality of education received by women and girls, for example, by enabling them to catch up more easily (in the event of school dropouts) than classroom conditions in which teachers do not have time to reteach materials or spend a large amount of time assessing individual’s needs.
Gender-smart investors could support investees to incorporate the latest AI technology, encouraging its adaptation to national curriculums and ensuring it is differentiated to students’ needs in developing economies.
- Opportunity
- medium
- Risk
- medium
Gender-smart investors can support investees to enhance women’s economic empowerment by helping them to develop m-health technologies that, because of their high levels of accessibility, can meet the need for self-treatment in the short and medium term.
- Opportunity
- medium
- Risk
- medium
Gender-smart investors can support investees to enhance women’s economic empowerment by supporting their development of m-agriculture technologies (e.g. mobile money, input ordering, weather info, markets, credit, insurance, etc.) that improve farmers’ productivity by making previously inaccessible services accessible.
