The Mobile Alternative to Banking: Patterns of Financial Transactions in Emerging Countries
<|begin_of_text|><|start_header_id|>system<|end_header_id|> You are a research archivist expert in dataset metadata. Answer the question truthfully.  <|eot_id|><|start_header_id|>user<|end_header_id|> Here is the Description of a dataset. Description:'This paper explores patterns of financial transactions at the individual level in order to establish the effects of mobile money’s usage in a variety of country case examples. Data from the Financial Inclusion Insights program was analyzed for Bangladesh, India, Kenya, Nigeria, Pakistan, Tanzania, and Uganda, to establish differences between individuals who use mobile money services and their non-user counterparts. This analysis builds on previous research into the household level effects of the widely popular M-PESA services in Kenya to see if financial transaction patterns can be replicated in other country data. Contrary to previous literature, m-money usership was not a consistent predictor of transaction frequency and transaction distance for the country cases where data was available. To examine m-money’s potential as a complement' . Please return only a json list of at most 3 Keywords corresponding to the Description:.<|eot_id|><|start_header_id|>assistant<|end_header_id|> {"Answer" : ["Banks and banking, Mobile -- Africa","Banks and banking -- Technological innovations -- Africa"]} <|eot_id|>
 Here is the Description of a dataset. Description:'This paper explores patterns of financial transactions at the individual level in order to establish the effects of mobile money’s usage in a variety of country case examples. Data from the Financial Inclusion Insights program was analyzed for Bangladesh, India, Kenya, Nigeria, Pakistan, Tanzania, and Uganda, to establish differences between individuals who use mobile money services and their non-user counterparts. This analysis builds on previous research into the household level effects of the widely popular M-PESA services in Kenya to see if financial transaction patterns can be replicated in other country data. Contrary to previous literature, m-money usership was not a consistent predictor of transaction frequency and transaction distance for the country cases where data was available. To examine m-money’s potential as a complement' . Please return only a json list of at most 3 Keywords corresponding to the Description:.
This paper explores patterns of financial transactions at the individual level in order to establish the effects of mobile money’s usage in a variety of country case examples. Data from the Financial Inclusion Insights program was analyzed for Bangladesh, India, Kenya, Nigeria, Pakistan, Tanzania, and Uganda, to establish differences between individuals who use mobile money services and their non-user counterparts. This analysis builds on previous research into the household level effects of the widely popular M-PESA services in Kenya to see if financial transaction patterns can be replicated in other country data. Contrary to previous literature, m-money usership was not a consistent predictor of transaction frequency and transaction distance for the country cases where data was available. To examine m-money’s potential as a complement
Banks and banking, Mobile -- Africa; Banks and banking -- Technological innovations -- Africa