Abstract:

Current study was carried out in order to highlight the most common challenges of adopting artificial intelligence within financial sector in 3rd world countries taking Jordan as an example. Challenges included (Limited Infrastructure, Lack of Technical Expertise, Language and Cultural Barriers, Cost and Affordability, Acceptance). Quantitative methodology was adopted, and a questionnaire was self-administered by (272) managers and leaders within the financial and banking sector, which includes (320) companies operating throughout the Kingdome Jordan as a 3rd world country. SPSS was used to screen and mitigate collected primary data. Results of study indicated that acceptance of the main hypothesis “Challenges in 3rd world countries may hinder the adoption of AI solutions in the financial sector” with R= 0.959 and a variance of (92%). Among the sub-variables chosen as controllers of study. It was seen that all of them played a role in hindering the applicability of AI in Jordanian financial sector. The highest in influence was (acceptance) with beta=0.612 being significant at 0.05 level. Study recommended giving priority to creating a strong data infrastructure in terms of collection and storage, and focusing on data exchange operations between different financial institutions. It is expected from current study to form as an indicator that explains any possible failure in adopting AI in finances. Interested parties may find in the current study as an approach to locate the weaknesses and work towards strengthening them.

Keywords:

Artificial Intelligence, Limited Infrastructure, Lack of Technical Expertise, Language and Cultural Barriers, Cost and Affordability, Acceptance, 3rd World Country, Disparities, Unequal Access.

How to Cite:

Murad Mohammad Alkaseasbeh. The Challenges of Applying Artificial Intelligence Solutions within 3rd World Countries Financial Sector. [ref]: vol.22.2024. available at: https://refpress.org/ref-vol22-a41/