The effect of financial development and legal institutions on financial inclusion in Sub-Saharan Africa by Mohammed Gbanja Abdulai, Haruna Issahaku

“…Implications: Open innovation in the financial sector, particularly in mobile payments, can benefit from the positive impact of financial development on inclusion. …”
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The association between the diversity of online activities on smartphones and cognitive function among middle-aged and elderly Chinese adults by Qian Chen, Haoqiang Ji, Qingxin Shang

“…Moreover, some online activities, such as watching news (β:0.5, 95% CI:0.2–0.8), posting moments (β:0.4, 95% CI:0.2–0.7) playing games (β:0.3, 95% CI:0.03–0.6) and making mobile payments (β:0.3, 95% CI:0.1–0.5) were independently associated with good cognitive function. …”
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The Nexus between Formal Credit and E-Commerce Utilization of Entrepreneurial Farmers in Rural China: A Mediation Analysis by Shaoxiong Yang, Huiling Wang, Zhengxiao Wang, Mansoor Ahmed Koondhar, Linxue Ji, Rong Kong

“…Some groups perform significantly in the heterogeneity analysis, the most noteworthy of which are entrepreneurial farmers who are younger, belong to new type of agricultural business entities and use mobile payments. Their e-commerce utilization, including online purchases and sales, are impacted most by formal credit. …”
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A Design of Cloud-Based Billing and Monitoring System for an Electric Company by John Benedic R. Enriquez

“…It was recommended that mobile payments (e.g., PayPal and credit cards) be included in future researches. …”
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Household usage of financial services around the world and Ukraine by Shapoval Yu. I.

“…The ways of increasing the use of financial services are identified, such as mobile payments, digitalisation of private and public payments, and an increase in financial literacy.…”
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Characterizing Mobile Money Phishing Using Reinforcement Learning by Alima Nzeket Njoya, Vanelle Laure Tchaya Ngongag, Franklin Tchakounte, Marcellin Atemkeng, Claude Fachkha

“…Finally, we found that some deep reinforcement algorithms, such as Deep Sarsa and <inline-formula> <tex-math notation="LaTeX">$A2C$ </tex-math></inline-formula>, can improve the characterization of scammer-victim interactions during mobile payments.…”
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RingAuth dataset by Sturgess, J

“…The data contains data from users (n=21) as they performed five types of gesture: tap gestures as users performed mobile payments on a number of point-of-sale terminals with (i) the smart ring and (ii) the smartwatch, and knock gestures as users knocked on the door in patterns of (iii) 3 knocks at a time, (iv) 5 knocks at a time, and (v) secret knocks chosen by the user. …”