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Artificial Intelligence-Enhanced Predictive Insights for Advancing Financial Inclusion: A Human-Centric AI-Thinking Approach

1
National Institute of Education, Nanyang Technological University, Singapore 639798, Singapore
2
Centre for Management Practice, Singapore Management University, Singapore 188065, Singapore
3
Nanyang Business School, Nanyang Technological University, Singapore 639798, Singapore
4
Faculty of Education, Monash University, VIC 3800, Australia
*
Authors to whom correspondence should be addressed.
Big Data Cogn. Comput. 2020, 4(2), 8; https://doi.org/10.3390/bdcc4020008
Received: 9 March 2020 / Revised: 11 April 2020 / Accepted: 22 April 2020 / Published: 27 April 2020
According to the World Bank, a key factor to poverty reduction and improving prosperity is financial inclusion. Financial service providers (FSPs) offering financially-inclusive solutions need to understand how to approach the underserved successfully. The application of artificial intelligence (AI) on legacy data can help FSPs to anticipate how prospective customers may respond when they are approached. However, it remains challenging for FSPs who are not well-versed in computer programming to implement AI projects. This paper proffers a no-coding human-centric AI-based approach to simulate the possible dynamics between the financial profiles of prospective customers collected from 45,211 contact encounters and predict their intentions toward the financial products being offered. This approach contributes to the literature by illustrating how AI for social good can also be accessible for people who are not well-versed in computer science. A rudimentary AI-based predictive modeling approach that does not require programming skills will be illustrated in this paper. In these AI-generated multi-criteria optimizations, analysts in FSPs can simulate scenarios to better understand their prospective customers. In conjunction with the usage of AI, this paper also suggests how AI-Thinking could be utilized as a cognitive scaffold for educing (drawing out) actionable insights to advance financial inclusion. View Full-Text
Keywords: artificial intelligence; fintech; financial technology; marketing; Bayesian; predictive modeling; human-centric; human-in-the-loop; AI-Thinking; explainable-AI; AI for good artificial intelligence; fintech; financial technology; marketing; Bayesian; predictive modeling; human-centric; human-in-the-loop; AI-Thinking; explainable-AI; AI for good
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MDPI and ACS Style

How, M.-L.; Cheah, S.-M.; Khor, A.C.; Chan, Y.J. Artificial Intelligence-Enhanced Predictive Insights for Advancing Financial Inclusion: A Human-Centric AI-Thinking Approach. Big Data Cogn. Comput. 2020, 4, 8. https://doi.org/10.3390/bdcc4020008

AMA Style

How M-L, Cheah S-M, Khor AC, Chan YJ. Artificial Intelligence-Enhanced Predictive Insights for Advancing Financial Inclusion: A Human-Centric AI-Thinking Approach. Big Data and Cognitive Computing. 2020; 4(2):8. https://doi.org/10.3390/bdcc4020008

Chicago/Turabian Style

How, Meng-Leong; Cheah, Sin-Mei; Khor, Aik C.; Chan, Yong J. 2020. "Artificial Intelligence-Enhanced Predictive Insights for Advancing Financial Inclusion: A Human-Centric AI-Thinking Approach" Big Data Cogn. Comput. 4, no. 2: 8. https://doi.org/10.3390/bdcc4020008

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