Assessing Incentives to Increase Digital Payment Acceptance and Usage : A Machine Learning Approach
An important step to achieve greater financial inclusion is to increase the acceptance and usage of digital payments. Although consumer adoption of digital payments has improved dramatically globally, the acceptance and usage of digital payments fo...
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| Format: | Working Paper |
| Language: | English |
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World Bank, Washington, DC
2022
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| Online Access: | http://documents.worldbank.org/curated/en/099835305172210068/P16477006919c50ff0b5c803899c587e8ee http://hdl.handle.net/10986/37487 |
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okr-10986-374872022-06-01T05:10:32Z Assessing Incentives to Increase Digital Payment Acceptance and Usage : A Machine Learning Approach Allen, Jeff Carbo Valverde, Santiago Chakravorti, Sujit Rodriguez-Fernandez, Francisco Pinar Ardic, Oya DIGITAL PAYMENT FINANCIAL INCLUSION ACCEPTANCE OF DIGITAL PAYMENT CONSUMER PAYMENTS INCENTIVES FINANCIAL REGULATION MACHINE LEARNING PAYMENT SYSTEMS DEVELOPMENT GROUP SHADOW ECONOMY MICRO RETAILER SMALL RETAILER MEDIUM RETAILER RETAIL TAX POLICY MOBILE PAYMENT APP An important step to achieve greater financial inclusion is to increase the acceptance and usage of digital payments. Although consumer adoption of digital payments has improved dramatically globally, the acceptance and usage of digital payments for micro, small, and medium-sized retailers (MSMRs) remain challenging. Using random forest estimation, The authors identify 14 key predictors out of 190 variables with the largest predictive power for MSMR adoption and usage of digital payments. Using conditional inference trees, they study the importance of sequencing and interactions of various factors such as public policy initiatives, technological advancements, and private sector incentives. The authors find that in countries with low point of sale (POS) terminal adoption, killer applications such as mobile phone payment apps increase the likelihood of P2B digital transactions. They also find the likelihood of digital P2B payments at MSMRs increases when MSMRs pay their employees and suppliers digitally. The level of ownership of basic financial accounts by consumers and the size of the shadow economy are also important predictors of greater adoption and usage of digital payments. Using causal forest estimation, they find a positive and economically significant marginal effect for merchant and consumer fiscal incentives on POS terminal adoption on average. When countries implement financial inclusion initiatives, POS terminal adoption increases significantly and MSMRs’ share of person-to-business (P2B) digital payments also increases. Merchant and consumer fiscal incentives also increase MSMRs’ share of P2B electronic payments. 2022-05-31T16:45:15Z 2022-05-31T16:45:15Z 2022-01-18 Working Paper http://documents.worldbank.org/curated/en/099835305172210068/P16477006919c50ff0b5c803899c587e8ee http://hdl.handle.net/10986/37487 English CC BY 3.0 IGO http://creativecommons.org/licenses/by/3.0/igo World Bank World Bank, Washington, DC Working Paper Publications & Research |
| repository_type |
Digital Repository |
| institution_category |
Foreign Institution |
| institution |
Digital Repositories |
| building |
World Bank Open Knowledge Repository |
| collection |
World Bank |
| language |
English |
| topic |
DIGITAL PAYMENT FINANCIAL INCLUSION ACCEPTANCE OF DIGITAL PAYMENT CONSUMER PAYMENTS INCENTIVES FINANCIAL REGULATION MACHINE LEARNING PAYMENT SYSTEMS DEVELOPMENT GROUP SHADOW ECONOMY MICRO RETAILER SMALL RETAILER MEDIUM RETAILER RETAIL TAX POLICY MOBILE PAYMENT APP |
| spellingShingle |
DIGITAL PAYMENT FINANCIAL INCLUSION ACCEPTANCE OF DIGITAL PAYMENT CONSUMER PAYMENTS INCENTIVES FINANCIAL REGULATION MACHINE LEARNING PAYMENT SYSTEMS DEVELOPMENT GROUP SHADOW ECONOMY MICRO RETAILER SMALL RETAILER MEDIUM RETAILER RETAIL TAX POLICY MOBILE PAYMENT APP Allen, Jeff Carbo Valverde, Santiago Chakravorti, Sujit Rodriguez-Fernandez, Francisco Pinar Ardic, Oya Assessing Incentives to Increase Digital Payment Acceptance and Usage : A Machine Learning Approach |
| description |
An important step to achieve greater
financial inclusion is to increase the acceptance and usage
of digital payments. Although consumer adoption of digital
payments has improved dramatically globally, the acceptance
and usage of digital payments for micro, small, and
medium-sized retailers (MSMRs) remain challenging. Using
random forest estimation, The authors identify 14 key
predictors out of 190 variables with the largest predictive
power for MSMR adoption and usage of digital payments. Using
conditional inference trees, they study the importance of
sequencing and interactions of various factors such as
public policy initiatives, technological advancements, and
private sector incentives. The authors find that in
countries with low point of sale (POS) terminal adoption,
killer applications such as mobile phone payment apps
increase the likelihood of P2B digital transactions. They
also find the likelihood of digital P2B payments at MSMRs
increases when MSMRs pay their employees and suppliers
digitally. The level of ownership of basic financial
accounts by consumers and the size of the shadow economy are
also important predictors of greater adoption and usage of
digital payments. Using causal forest estimation, they find
a positive and economically significant marginal effect for
merchant and consumer fiscal incentives on POS terminal
adoption on average. When countries implement financial
inclusion initiatives, POS terminal adoption increases
significantly and MSMRs’ share of person-to-business (P2B)
digital payments also increases. Merchant and consumer
fiscal incentives also increase MSMRs’ share of P2B
electronic payments. |
| format |
Working Paper |
| author |
Allen, Jeff Carbo Valverde, Santiago Chakravorti, Sujit Rodriguez-Fernandez, Francisco Pinar Ardic, Oya |
| author_facet |
Allen, Jeff Carbo Valverde, Santiago Chakravorti, Sujit Rodriguez-Fernandez, Francisco Pinar Ardic, Oya |
| author_sort |
Allen, Jeff |
| title |
Assessing Incentives to Increase Digital Payment Acceptance and Usage : A Machine Learning Approach |
| title_short |
Assessing Incentives to Increase Digital Payment Acceptance and Usage : A Machine Learning Approach |
| title_full |
Assessing Incentives to Increase Digital Payment Acceptance and Usage : A Machine Learning Approach |
| title_fullStr |
Assessing Incentives to Increase Digital Payment Acceptance and Usage : A Machine Learning Approach |
| title_full_unstemmed |
Assessing Incentives to Increase Digital Payment Acceptance and Usage : A Machine Learning Approach |
| title_sort |
assessing incentives to increase digital payment acceptance and usage : a machine learning approach |
| publisher |
World Bank, Washington, DC |
| publishDate |
2022 |
| url |
http://documents.worldbank.org/curated/en/099835305172210068/P16477006919c50ff0b5c803899c587e8ee http://hdl.handle.net/10986/37487 |
| _version_ |
1764487303306149888 |