Building Gender-Sensitive Infrastructure for Digital Payment Fraud Prevention

Описание: While it is widely acknowledged that women are often more vulnerable to scams and fraud, there is a significant lack of gender-disaggregated data to substantiate this claim. The absence of detailed data about how fraud affects different genders obscures our understanding of its real impact, limiting the ability of governments, financial institutions, and fraud prevention agencies to tailor their interventions effectively.

Many fraud detection and prevention algorithms used by financial institutions are built without considering gender-specific patterns of behavior. Integrating gender-disaggregated data could lead to more sophisticated detection systems that identify and block fraud attempts targeting specific groups. Without interventions, fraud will continue to disproportionately affect women which may compound existing financial inequalities. Without substantive data, financial support systems, recovery mechanisms, and protective measures will continue to overlook this disparity. Addressing these gaps could significantly reduce economic inequality across genders and empower women to protect themselves against fraud to help create a safer financial ecosystem for all.

This panel explored the specific infrastructure needed to support women in the digital payment ecosystem, focusing on fraud prevention, financial inclusion, accessibility and usage. In particular, the importance of collecting accurate gender-disaggregated data and the challenges around collection.