Research on Artificial Intelligence (AI) in finance has been growing significantly alongside its increasing implementation in the financial sector. This development raises questions about the specific financial areas and AI technology applications that are most frequently explored as research topics within AI in finance. This study aims to address these questions by employing a systematic literature review (SLR) method, analyzing journal articles indexed in Scopus (Q1–Q4) and published between 2020 and 2024. A search conducted using Publish or Perish on the Scopus database identified 496 records, which were subsequently filtered to 94 articles using the PRISMA protocol. The selected articles were examined through bibliometric analysis using VOSviewer, followed by content analysis. The findings reveal that fintech and risk management are the most frequently discussed financial areas in AI in finance research. Moreover, machine learning emerges as the most commonly addressed AI technology application in this domain. Notably, the combination of machine learning and risk management stands out as the most prominent research topic.

The purpose of this research is to determine strategies for addressing the delays in the arrival and departure times of KM Umsini and KM Dobonsolo owned by PT. Pelni (Persero) at the Port of Makassar based on SWOT analysis recommendations. The data processed includes qualitative data on estimated arrival times compared to the actual arrival times of the vessels, as well as estimated departure times compared to the actual departure times. The results show that the average delay in the arrival of KM Dobonsolo is 1 hour and 18 minutes, while the average delay in departure is 2 hours and 5 minutes. The average delay in the arrival of KM Umsini is 3 hours and 8 minutes, and the average delay in departure is 3 hours and 12 minutes. The strategies implemented to improve the factors affecting the punctuality of the vessels' arrival and departure times include the Embarkation/Debarkation Service Process, the Loading/Unloading Process, the Freshwater Bunkering Process, the Fuel Bunkering Process, and the delays in the IT system facilitated by Inapornet in handling Clearance Documents.