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Behavioral Segmentation for Improved Mobile Banking Product Uptake in Underserved Markets

Okeoghene Elebe Chikaome Chimara Imediegwu

Subject area: Science,Engineering and Technology  ·  Area of research: Mobile Banking Product

Abstract

In underserved markets, the expansion of mobile banking services presents a transformative opportunity to advance financial inclusion. However, adoption remains uneven due to heterogeneity in user behaviors, preferences, and trust levels. This review paper explores the role of behavioral segmentation as a strategic framework for increasing mobile banking product uptake among financially underserved populations. Drawing on interdisciplinary insights from behavioral economics, data analytics, and digital finance, the paper categorizes key behavioral segments based on variables such as transaction frequency, digital literacy, risk aversion, and socio-cultural norms. It also examines successful case studies where segmentation-driven design has improved customer acquisition and retention in emerging economies. Further, the paper highlights ethical considerations, data privacy concerns, and infrastructural limitations that shape implementation outcomes. By synthesizing recent literature and practical applications, this review advocates for a context-sensitive, behaviorally informed approach to mobile banking innovation. It concludes with strategic recommendations for financial institutions, fintechs, and policymakers to deploy behavioral segmentation as a lever for equitable and sustainable digital financial inclusion.

Keywords

Behavioral Segmentation, Mobile Banking, Financial Inclusion, Underserved Markets, Consumer Behavior, Digital Financial Services.

References

[1] Abiola Olayinka Adams, Nwani, S., Abiola-Adams, O., Otokiti, B.O. & Ogeawuchi, J.C., 2020.Building Operational Readiness Assessment Models for Micro, Small, and Medium Enterprises Seeking Government-Backed Financing. Journal of Frontiers in Multidisciplinary Research, 1(1), pp.38-43. DOI: 10.54660/IJFMR.2020.1.1.38-43.

[2] Adenuga, T., Ayobami, A.T. & Okolo, F.C., 2019. Laying the Groundwork for Predictive Workforce Planning Through Strategic Data Analytics and Talent Modeling. IRE Journals, 3(3), pp.159–161. ISSN: 2456-8880.

[3] Adenuga, T., Ayobami, A.T. & Okolo, F.C., 2020. AI-Driven Workforce Forecasting for Peak Planning and Disruption Resilience in Global Logistics and Supply Networks. International Journal of Multidisciplinary Research and Growth Evaluation, 2(2), pp.71–87. Available at: https://doi.org/10.54660/.IJMRGE.2020.1.2.71-87.

[4] Adewoyin, M.A., Ogunnowo, E.O., Fiemotongha, J.E., Igunma, T.O. & Adeleke, A.K., 2020.A Conceptual Framework for Dynamic Mechanical Analysis in High-Performance Material Selection. IRE Journals, 4(5), pp.137–144.

[5] Adewoyin, M.A., Ogunnowo, E.O., Fiemotongha, J.E., Igunma, T.O. & Adeleke, A.K., 2020.Advances in Thermofluid Simulation for Heat Transfer Optimization in Compact Mechanical Devices. IRE Journals, 4(6), pp.116–124.

[6] Adewuyi, A., Oladuji, T.J., Ajuwon, A. & Nwangele, C.R. (2020) ‘A Conceptual Framework for Financial Inclusion in Emerging Economies: Leveraging AI to Expand Access to Credit’, IRE Journals, 4(1), pp. 222–236. ISSN: 2456-8880.

[7] Ajuwon, A., Onifade, O., Oladuji, T.J. & Akintobi, A.O. (2020) ‘Blockchain-Based Models for Credit and Loan System Automation in Financial Institutions’, IRE Journals, 3(10), pp. 364–381. ISSN: 2456-8880.

[8] Akinbola, O. A., Otokiti, B. O., Akinbola, O. S., & Sanni, S. A. (2020). Nexus of Born Global Entrepreneurship Firms and Economic Development in Nigeria. Ekonomicko-manazerske spektrum, 14(1), 52-64.

[9] Akpe, O. E. E., Mgbame, A. C., Ogbuefi, E., Abayomi, A. A., & Adeyelu, O. O. (2020). Bridging the business intelligence gap in small enterprises: A conceptual framework for scalable adoption. IRE Journals, 4(2), 159–161.

[10] Akpe, O.E., Mgbame, A.C., Ogbuefi, E., Abayomi, A.A. & Adeyelu, O.O., 2020.Barriers and Enablers of BI Tool Implementation in Underserved SME Communities. IRE Journals, 3(7), pp.211-220. DOI: .

[11] Akpe, O.E., Mgbame, A.C., Ogbuefi, E., Abayomi, A.A. & Adeyelu, O.O., 2020. Bridging the Business Intelligence Gap in Small Enterprises: A Conceptual Framework for Scalable Adoption. IRE Journals, 4(2), pp.159-168. DOI:

[12] Akpe, O.E., Ogeawuchi, J.C., Abayomi, A.A., Agboola, O.A. & Ogbuefis, E. (2020) 'A Conceptual Framework for Strategic Business Planning in Digitally Transformed Organizations', IRE Journals, 4(4), pp. 207-214.

[13] Ashiedu, B.I., Ogbuefi, E., Nwabekee, U.S., Ogeawuchi, J.C. & Abayomis, A.A. (2020) 'Developing Financial Due Diligence Frameworks for Mergers and Acquisitions in Emerging Telecom Markets', IRE Journals, 4(1), pp. 1-8.

[14] Fagbore, O.O., Ogeawuchi, J.C., Ilori, O., Isibor, N.J., Odetunde, A. & Adekunle, B.I. (2020) 'Developing a Conceptual Framework for Financial Data Validation in Private Equity Fund Operations', IRE Journals, 4(5), pp. 1-136.

[15] Mgbame, A. C., Akpe, O. E. E., Abayomi, A. A., Ogbuefi, E., & Adeyelu, O. O. (2020). Barriers and enablers of BI tool implementation in underserved SME communities. IRE Journals, 3(7), 211–213.

[16] Nwani, S., Abiola-Adams, O., Otokiti, B.O. & Ogeawuchi, J.C., 2020.Designing Inclusive and Scalable Credit Delivery Systems Using AI-Powered Lending Models for Underserved Markets. IRE Journals, 4(1), pp.212-214. DOI: 10.34293 /irejournals.v 4i1.1708888.

[17] ODOFIN, O. T., ABAYOMI, A. A., & CHUKWUEMEKE, A. (2020). Developing Microservices Architecture Models for Modularization and Scalability in Enterprise Systems.

[18] Odofin, O.T., Agboola, O.A., Ogbuefi, E., Ogeawuchi, J.C., Adanigbo, O.S. & Gbenle, T.P. (2020) 'Conceptual Framework for Unified Payment Integration in Multi-Bank Financial Ecosystems', IRE Journals, 3(12), pp. 1-13.

[19] Ogunnowo, E.O., Adewoyin, M.A., Fiemotongha, J.E., Igunma, T.O. & Adeleke, A.K., 2020.Systematic Review of Non-Destructive Testing Methods for Predictive Failure Analysis in Mechanical Systems. IRE Journals, 4(4), pp.207–215.

[20] Olufemi-Phillips, A. Q., Ofodile, O. C., Toromade, A. S., Eyo-Udo, N. L., & Adewale, T. T. (2020). Optimizing FMCG supply chain management with IoT and cloud computing integration. International Journal of Managemeijignt & Entrepreneurship Research, 6(11), 1-15.

[21] Omisola, J. O., Etukudoh, E. A., Okenwa, O. K., & Tokunbo, G. I. (2020). Innovating Project Delivery and Piping Design for Sustainability in the Oil and Gas Industry: A Conceptual Framework. perception, 24, 28-35.

[22] Omisola, J. O., Etukudoh, E. A., Okenwa, O. K., & Tokunbo, G. I. (2020). Geosteering Real-Time Geosteering Optimization Using Deep Learning Algorithms Integration of Deep Reinforcement Learning in Real-time Well Trajectory Adjustment to Maximize. Unknown Journal.

[23] Osho, G. O., Omisola, J. O., & Shiyanbola, J. O. (2020). A Conceptual Framework for AI-Driven Predictive Optimization in Industrial Engineering: Leveraging Machine Learning for Smart Manufacturing Decisions. Unknown Journal.

[24] Osho, G. O., Omisola, J. O., & Shiyanbola, J. O. (2020). An Integrated AI-Power BI Model for Real-Time Supply Chain Visibility and Forecasting: A Data-Intelligence Approach to Operational Excellence. Unknown Journal.

[25] Oyedokun, O.O., 2019.Green Human Resource Management Practices (GHRM) and Its Effect on Sustainable Competitive Edge in the Nigerian Manufacturing Industry: A Study of Dangote Nigeria Plc. MBA Dissertation, Dublin Business School.

[26] Sharma, A., Adekunle, B.I., Ogeawuchi, J.C., Abayomi, A.A. & Onifade, O. (2019) 'IoT-enabled Predictive Maintenance for Mechanical Systems: Innovations in Real-time Monitoring and Operational Excellence', IRE Journals, 2(12), pp. 1-10.

How to cite this paper

Okeoghene Elebe, Chikaome Chimara Imediegwu "Behavioral Segmentation for Improved Mobile Banking Product Uptake in Underserved Markets" Iconic Research And Engineering Journals Volume 3 Issue 9 2020 Page 383-398
Okeoghene Elebe, Chikaome Chimara Imediegwu "Behavioral Segmentation for Improved Mobile Banking Product Uptake in Underserved Markets" Iconic Research And Engineering Journals, vol. 3, no. 9, Mar. 2020
Okeoghene Elebe, Chikaome Chimara Imediegwu (2020). Behavioral Segmentation for Improved Mobile Banking Product Uptake in Underserved Markets. Iconic Research And Engineering Journals, 3(9).
Okeoghene Elebe, Chikaome Chimara Imediegwu "Behavioral Segmentation for Improved Mobile Banking Product Uptake in Underserved Markets" Iconic Research And Engineering Journals, vol. 3, no. 9, Mar. 2020.
@article{1709611,
      author = {Okeoghene Elebe, Chikaome Chimara Imediegwu},
      title = {Behavioral Segmentation for Improved Mobile Banking Product Uptake in Underserved Markets},
      journal = {Iconic Research And Engineering Journals},
      year = {2020},
      volume = {3},
      number = {9},
      pages = {383-398},
      issn = {2456-8880},
      url = {https://www.irejournals.com/formatedpaper/1709611.pdf},
      abstract = {In underserved markets, the expansion of mobile banking services presents a transformative opportunity to advance financial inclusion. However, adoption remains uneven due to heterogeneity in user behaviors, preferences, and trust levels. This review paper explores the role of behavioral segmentation as a strategic framework for increasing mobile banking product uptake among financially underserved populations. Drawing on interdisciplinary insights from behavioral economics, data analytics, and digital finance, the paper categorizes key behavioral segments based on variables such as transaction frequency, digital literacy, risk aversion, and socio-cultural norms. It also examines successful case studies where segmentation-driven design has improved customer acquisition and retention in emerging economies. Further, the paper highlights ethical considerations, data privacy concerns, and infrastructural limitations that shape implementation outcomes. By synthesizing recent literature and practical applications, this review advocates for a context-sensitive, behaviorally informed approach to mobile banking innovation. It concludes with strategic recommendations for financial institutions, fintechs, and policymakers to deploy behavioral segmentation as a lever for equitable and sustainable digital financial inclusion.},
      keywords = {Behavioral Segmentation, Mobile Banking, Financial Inclusion, Underserved Markets, Consumer Behavior, Digital Financial Services.},
      month = {March},
  }