Senior Fellow Alan Gelb and Policy Analyst Julia Clark are cited in a Financial Times article on biometric ID systems.
Anti-poverty programmes in India have benefited from an iris-scanning ID system that dramatically reduced fraudulent duplicate payouts.
Imagine you’re a government minister in a developing country, with responsibility for improving the lives of the poorest 20 per cent of the population. Given a blank slate, it’s not hard to make a list: get everybody a basic bank account; pay a small cash sum to the poorest households; enrol every poor child in primary school, using sticks or carrots to make sure the children show up; provide handouts of cash or food to those hit by natural disasters; provide free basic healthcare and vaccinations. Such a list is ambitious, but not because it’s too expensive. The real constraint is that to implement any of these policies, you need to be able to identify your own citizens.
A state that can cheaply and reliably identify individual citizens can also provide services that would be hard to imagine without a universal identification (UID) system.
You can get a sense of the opportunities available from the iris-scanning ID system introduced by the state of Andhra Pradesh in 2008 after a botched effort in 2005. The system dramatically reduced fraudulent duplicate payouts. Frances Zelazny of the Center for Global Development estimates that the system paid for itself within one month.
Alan Gelb and Julia Clark, also researchers at the Center for Global Development, draw a distinction between “functional” and “foundational” ID systems. Functional systems are set up to support a particular policy – child benefit, perhaps, or flood relief. Foundational systems are designed to support any and all policies requiring unique identification.