Women's World Banking Blog

Algorithmic Bias

Explore the latest global and regional insights from Women’s World Banking’s work in policy, leadership, women’s entrepreneurship, gender lens investing, and more.

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Research & Perspectives

Beyond Biases: Five Insights on Enhancing Credit Fairness with Reject Inference Techniques

Women’s World Banking is explaining the Five Insights on Enhancing Credit Fairness. One of the least expensive ways financial institutions can increase their credit portfolio profitability is by improving the accuracy of their approval mechanisms. “Reject inference” techniques help financial institutions to do just that, with implications for offering credit

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Research & Perspectives

Algorithmic Bias, Financial Inclusion, and Gender

By Sonja Kelly, Director of Research and Advocacy, and Mehrdad Mirpourian, Senior Data Analyst The discussion around artificial intelligence (AI) as a driving force for the economy and society has become increasingly popular, as evidenced by more than two dozen AI-focused sessions at the 2024 World Economic Forum in Davos.

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Event

Women’s World Banking Hosts Panel to Explore AI’s Role in Developing Gender Sensitive Financial Solutions

On September 8, 2021, Women’s World Banking hosted a virtual panel discussion on “Using AI to Develop Gender Sensitive Solutions” as part of its Making Finance Work for Women Thought Leadership Series. Moderated by Janet Truncale, Vice Chair and Regional Managing Partner of EY’s Americas Financial Services Organization, the panel included

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Research & Perspectives

Help Wanted: A Global Push Toward Algorithmic Fairness

A Q & A with Sonja Kelly of Women’s World Banking and Alex Rizzi of CFI, building on Women’s World Banking’s report and CFI’s report on algorithmic bias It seems conversations around biased AI have been around for some time. Is it too late to address this? Alex: It’s just

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Research & Perspectives

Report: Algorithmic Bias, Financial Inclusion, and Gender: A primer on opening up new credit to women in emerging economies

Artificial intelligence and machine learning are changing financial services offerings to customers across the globe. Historically, women have been the victims of unconscious bias in lending decisions. Algorithm-enabled credit decisions have the potential to create a level playing field for female customers worldwide—but only if we find and mitigate biases

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