Abstract
We use data from a leading Korean Fintech to study the use of a financial technology for remittance payments. Low-income workers in our sample improve the timing of the exchange rate applied to their remittance transactions by 1.7% through learning to take advantage of a cancellation feature. Using referral information to identify social networks, we find that workers improve the timing of payments by 2.3% if the feature is used more by other members of their social network. Overall, we find that users gain both from personal learning-by-doing as well as from the experience of their social networks.
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