For decades, aid organisations have struggled with a persistent problem: ensuring donations reach the people who need them most. Reports of fraud, inflated hospital bills and opaque operations have fuelled donor scepticism, particularly in low-income countries where oversight can be weak.

One organisation experimenting with a technology-driven response is Helpster Charity, a young nonprofit working across Africa and Asia to improve healthcare access for children and pregnant women. Its team has built a platform that combines artificial intelligence, medical oversight and data checks to flag inconsistencies in patient cases and reduce the risk of fraud.

“Early on, we discovered that some people were pretending to be poor,” said Kate Lysykh, CEO of Helpster. “Individuals were borrowing houses just to look eligible. We realised we couldn’t rely on goodwill alone.”

Helpster’s system reviews each case for risk and urgency, while volunteer doctors validate medical records remotely. Donors can track approved cases in real time, and in some situations, pay hospitals directly. The group also sets conditions with hospitals and partners to prevent inflated costs.

But such measures have not always been welcomed. In some communities, rejecting a leader’s recommendation or disputing a case can provoke backlash. “We’ve even faced demands for bribes just to get a case validated,” Ms. Lysykh said. “Our loyalty is to the people genuinely in need.”

Observers say the approach reflects a wider shift in philanthropy towards data-driven accountability. Whether such models can scale or withstand local pressures remains an open question. For now, Helpster is one of several groups testing how technology might rebuild trust in giving.