Assessing Agricultural Health through FinTech Data - An Analytical Approach

Authors

  • Kahtan Abedalrhman Kanzi Business Consultant, Al-Khobar, Saudi Arabia

DOI:

https://doi.org/10.5281/zenodo.14523484

Keywords:

fintech, agricultural sector, financial inclusion, digital finance, data analytics

Abstract

The agricultural sector plays a crucial role in the economic development of many countries, particularly those with large rural populations. However, traditional methods of assessing the health of the agricultural sector can be limited in scope and timeliness. The rapid advancements in financial technology have transformed the way financial services are delivered, particularly in rural areas. FinTech solutions, such as digital payments, lending, and insurance, can provide valuable insights into the financial activities and challenges faced by farmers and agricultural enterprises.This paper explores the transformative potential of FinTech in the agricultural sector, examining its impact on financial inclusion, resilience, and efficiency. By integrating quantitative FinTech data with qualitative insights from stakeholders, the study provides a comprehensive assessment of the sector's health. Findings indicate that FinTech complements traditional agricultural data, offering a dynamic view of financial activities and performance.  Increased FinTech adoption in rural areas can drive financial inclusion, improve credit access, and foster innovation. However, challenges such as digital literacy, infrastructure gaps, and regulatory frameworks need to be addressed.  The study emphasizes the importance of investments in digital infrastructure, capacity building, and collaboration between FinTech and agricultural sectors.These insights have implications for policymakers, financial institutions, and agricultural stakeholders, enabling data-driven decision-making, targeted interventions, and the promotion of sustainable agricultural development.

Downloads

Download data is not yet available.

References

Agricultural insurance for smallholder farmers. (2023). Available at: https://www.gsma.com/mobilefordevelopment/wp-content/uploads/2020/05/Agricultural_Insurance_for_Smallholder_Farmers_Digital_Innovations_for_Scale.pdf. (Accessed: November 18, 2024).

Evidence on mobile instant credit. (2024). Available at: https://cega.berkeley.edu/mobile-instant-credit/. (Accessed: November 18, 2024).

Parametric insurance to build financial resilience. (2024). Available at: https://irff.undp.org/publications/parametric-insurance-build-financial-resilience. (Accessed: November 18, 2024).

Understanding farm diversity: Insights from the agricultural resource management survey. (2024). Available at: https://www.ers.usda.gov/amber-waves/2024/may/understanding-farm-diversity-insights-from-the-agricultural-resource-management-survey/. (Accessed: November 18, 2024).

Akhter, F., Waqas, M., & Sohaib, S. (2022). Factors affecting the adoption of fintech services for bank clients. Journal of Social Sciences and Humanities, 45. doi:10.46568/jssh. v61i1.597.

Alonso, R.S. et al. (2019). An intelligent Edge-IoT platform for monitoring livestock and crops in a dairy farming scenario. Ad Hoc Networks, 102047. doi:10.1016/j.adhoc.2019.102047.

Barbu, C.M. et al. (2021). Customer experience in Fintech. Journal of Theoretical and Applied Electronic Commerce Research, 1415. doi:10.3390/jtaer16050080.

Dhanasekaran, B. (2022). Financial empowerment of farmers through agricultural credit by commercial banks: A descriptive analysis. Jurnal Ilmu Sosial Manajemen Akuntansi Dan Bisnis, 40. doi:10.47747/jismab. v3i1.661.

Farooq, M.S. et al. (2022). A survey on the role of IoT in agriculture for the implementation of smart livestock environment. IEEE Access, 9483. doi:10.1109/access.2022.3142848.

Finger, R. (2023). Digital innovations for sustainable and resilient agricultural systems. European Review of Agricultural Economics, 1277. doi:10.1093/erae/jbad021.

Giudici, P. (2018). Fintech risk management: A research challenge for artificial intelligence in finance. Frontiers in Artificial Intelligence. doi:10.3389/frai.2018.00001.

Jagtiani, J., & John, K. (2018). Fintech: The impact on consumers and regulatory responses. Journal of Economics and Business, 1. doi:10.1016/j.jeconbus.2018.11.002.

Kumar, A., Sharma, S., & Mahdavi, M. (2021). Machine Learning (ML) technologies for digital credit scoring in rural finance: A literature review. Risks, 192. doi:10.3390/risks9110192.

Kumar, L. et al. (2021). Internet Of Things (IOT) for smart precision farming and agricultural systems productivity: A review. International Journal of Engineering Applied Sciences and Technology. doi:10.33564/ijeast.2021.v05i09.022.

Kurucz, A., Sitompul, F.R., & Süle, E. (2021). Digitalization of agri-food supply chains: Facts and promises of blockchain technology. doi:10.18690/978-961-286-538-2.3.

Mittal, P., & Gupta, S. (2023). FinTech and digital finance: Foes or friends after COVID-19 pandemic?. Business Management and Economics Research, 13. doi:10.32861/bmer.91.13.21.

Mori, M. (2019). Modern finance: A catalyst for truly modern agriculture. Review on Agriculture and Rural Development, 5. doi:10.14232/rard.2018.1-2.5-10.

Ngo, V.M., Le‐Khac, N., & Kechadi, T. (2018). An efficient data warehouse for crop yield prediction. arXiv (Cornell University) [Preprint]. Cornell University. doi:10.48550/arXiv.1807.

Pandia, S. et al. (2019). Digitalisation in agriculture: Roads ahead. International Journal of Current Microbiology and Applied Sciences, 1841. doi:10.20546/ijcmas.2019.812.219.

Rahayu, E., & Rahadi, R.A. (2023). Exploring investor behavior and decision making in alternative investments. Zenodo (CERN European Organization for Nuclear Research) [Preprint]. European Organization for Nuclear Research. doi:10.5281/zenodo.8131692.

Sharma, A. et al. (2020). Financial Technology (Fin-Tech): Revolutionizing the Indian agrarian sector. International Journal of Innovative Technology and Exploring Engineering, 1. doi:10.35940/ijitee.l1001.10812s319.

Singh, S., Sahni, M.M., & Kovid, R.K. (2020). What drives FinTech adoption? A multi-method evaluation using an adapted technology acceptance model. Management Decision, 1675. doi:10.1108/md-09-2019-1318.

Soutter, L., Ferguson, K., & Neubert, M. (2019). Digital payments: Impact factors and mass adoption in sub-Saharan Africa. Technology Innovation Management Review, 41. doi:10.22215/timreview/1254.

Wabwire, J.M. (2019). Technological factors and utilization of formal financial services by smallholder farmers in Kenya. International Journal of Finance and Banking Research, 55. doi:10.11648/j.ijfbr.20190503.13.

Zhang, L., & Lin, N. (2019). Promoting of development with the assistance of financial technology. Proceedings of the 2019 3rd International Conference on Education, Economics and Management Research (ICEEMR 2019) [Preprint]. doi:10.2991/assehr.k.191221.053.

Zhao, N., & Yao, F. (2022). Innovative mechanism of rural finance: Risk assessment methods and impact factors of agricultural loans based on personal emotion and artificial intelligence. Journal of Environmental and Public Health. doi:10.1155/2022/1126489.

Халатур, С. et al. (2023). Financial security as a component of ensuring innovative development of agricultural production. Financial and Credit Activity Problems of Theory and Practice. University of Banking of the National Bank of Ukraine, pp. 341. doi:10.55643/fcaptp.3.50.2023.4050.

Downloads

Published

2024-11-30

How to Cite

Abedalrhman, K. (2024). Assessing Agricultural Health through FinTech Data - An Analytical Approach. Applied Science and Biotechnology Journal for Advanced Research, 3(6), 22–39. https://doi.org/10.5281/zenodo.14523484