Investing in Equitable AI for Inclusive Finance

While there are certainly arguments for the use of AI, the deployment of AI also comes with a bevy of risks. One prominent risk is inequitable outcomes for marginalized consumers. For women, harmful outcomes of AI include lower quality of service, unfair allocation of opportunities and reinforcement of existing stereotypes. In financial services, gender-biased AI has resulted in credit discrimination, differential pricing of goods and services and reduced choice. When applied at scale, the harms caused by AI counter the financial inclusion goals on which many impact investors and their portfolio companies focus. AI gender bias also has business, regulatory and reputational repercussions.

This publication gives an overview of the use cases of AI in inclusive finance and some of the drivers of harmful AI bias towards women. It also presents a snapshot of the state of practice in bias identification and mitigation and then provides a user-friendly checklist with an actionable set of questions to help impact investors understand the use of AI among their investee companies.