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Algorand's HesabPay Supports Over 600,000 Refugee Returnees in Afghanistan Since Council's Berlin Meeting
The Algorand Foundation today shared new progress from its Humanitarian Payments Council, marking a shift from pilot projects to institutional-scale deployments. Convening today in Washington, D.C. to build on the foundations laid during their September meeting in Berlin, Council members are highlighting a major expansion of blockchain-backed aid delivery in high-stakes environments. Most notably, according to UNHCR, the UN Refugee Agency, it has scaled its use of reloadable cards through HesabPay, the Algorand-powered payments platform, to support more than 625,000 refugee returnees and over 17,500 internally displaced people in Afghanistan, with more than $35 million in assistance. This operational milestone reflects the network's ability to support large-scale aid disbursement in a live deployment and provide secure, immediate financial empowerment in regions where traditional banking infrastructure is absent or limited. submitted by /u/semanticweb [link] [Kommentare] reddit.com · reddit.com ↗
The Algorand Foundation today shared new progress from its Humanitarian Payments Council, marking a shift from pilot projects to institutional-scale deployments. Convening today in Washington, D.C. to build on the foundations laid during their September meeting in Berlin, Council members are highlighting a major expansion of blockchain-backed aid delivery in high-stakes environments. Most notably, according to UNHCR, the UN Refugee Agency, it has scaled its use of reloadable cards through HesabPay, the Algorand-powered payments platform, to support more than 625,000 refugee returnees and over 17,500 internally displaced people in Afghanistan, with more than $35 million in assistance. This operational milestone reflects the network's ability to support large-scale aid disbursement in a live deployment and provide secure, immediate financial empowerment in regions where traditional banking infrastructure is absent or limited. submitted by /u/semanticweb [link] [Kommentare]
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