Publication Type

Journal Article

Version

publishedVersion

Publication Date

4-2020

Abstract

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.

Keywords

Artificial intelligence, Bayesian, Explainable-AI, Financial technology, Fintech, Human-centric, Human-in-the-loop, Marketing, Predictive modeling, AI for good, AI-Thinking

Discipline

Artificial Intelligence and Robotics | Finance and Financial Management | Technology and Innovation

Publication

Big Data and Cognitive Computing

Volume

4

Issue

2

First Page

1

Last Page

21

ISSN

2504-2289

Identifier

10.3390/bdcc4020008

Publisher

MDPI

Embargo Period

5-24-2021

Copyright Owner and License

Authors

Creative Commons License

Creative Commons Attribution 4.0 International License
This work is licensed under a Creative Commons Attribution 4.0 International License.

Additional URL

https://doi.org/10.3390/bdcc4020008

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