This research paper delves into the intricate landscape of
financial resilience within Tanzanian microcredit institutions, focusing on
predictive methodologies and the integration of Artificial Intelligence (AI)
for enhanced forecasting accuracy. Through an exhaustive exploration of traditional
practices and emerging AI-driven solutions, this study examines the evolving
strategies and limitations encountered in predicting financial trends within
this dynamic sector. Employing a mixed-methods approach encompassing diverse
case studies across key Tanzanian regions - Dar-es-Salaam, Arusha, and
Kilimanjaro - the research garnered insights into localized complexities,
historical evolution, and direct impact on bolstering financial resilience.
Findings underscored the multifaceted objectives pursued by microcredit
institutions in trend projection, emphasizing the primary goals of optimizing
investment strategies, managing liquidity effectively, and planning for
sustainable growth and expansion. While traditional methodologies demonstrated
some efficacy, challenges in data quality, interpretation, and predictive
analytics expertise emerged as impediments to accurate trend projection.
Proposed AI-based solutions offered promising outcomes, with anticipated
benefits including improved prediction accuracy, enhanced decision-making, and
potential cost savings. However, concerns regarding data security, expertise,
and implementation costs pose notable challenges to widespread AI integration.
Therefore, the research advocates for the integration of AI technologies to
fortify predictive capacities within Tanzanian microcredit institutions. It
emphasizes the imperative nature of investing in resources and expertise to
leverage AI potential for sustainable growth and heightened forecasting
accuracy in this rapidly evolving financial landscape. This study contributes
essential insights into the challenges, opportunities, and potential pathways
for leveraging advanced technologies in enhancing financial resilience within
microcredit institutions, fostering a more sustainable and prosperous future
for Tanzania microcredit sector.
Author(s) Details:
Mwapashua H. Fujo,
Moshi Co-Operative University (MoCU), Tanzania.
Samwel Katwale,
Moshi
Co-Operative University (MoCU), Tanzania.
Mussa Ally Dida,
School of Computational and Communication Science and Engineering,
Nelson Mandela African Institution of Science and Technology (NM-AIST), Arusha,
Tanzania.
Please see the link here: https://stm.bookpi.org/AOBMER-V9/article/view/13431
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