This faiVLive focused on better understanding the emerging risks of AI-powered cyberattacks, and sought to catalyze informed collective action in the financial inclusion community.

This report aims to inform practitioners and policymakers about ways in which innovations in credit scoring can advance financial inclusion while ensuring fairness and protecting consumers. 

Recent news coverage of the new artificial intelligence (AI) model called Mythos has raised alarms in many circles about increasing cybersecurity risks, especially for the financial sector. What do financial inclusion practitioners need to know about Anthropic's AI model?

Mastercard and Crossmint's Lobster.cash announced that they are working together so consumers will soon be free to safely authorize AI agents to make purchases using their existing payment cards. 

This report assesses the impact of AI on the financial services industry, including fintechs and traditional financial institutions, from efficiency to productivity and profitability, as well as persistent organizational adoption and scaling challenges. It also highlights developing policy and regulatory approaches.

The results show that female applicants below the threshold are less likely to take out loans and receive smaller loan amounts than men. However, this gender bias disappears for applicants above the threshold.

This paper discusses the imperative for financial supervisory authorities to enhance their toolkit through the adoption of Artificial Intelligence in response to the growing digitalization of financial services.

In what ways do the underlying logics, design choices, and management decisions of ML-based alternative lending tools by fintechs embed or challenge gender biases, and how do these choices influence gender equity in access to finance? 

This paper draws on interview data with leaders, investors, and data scientists at fintech companies developing ML-based alternative lending apps in low- and middle-income countries to explore financial inclusion and gender implications.