Cloud computing is a groundbreaking technique that provides a whole lot of facilities such as storage, memory, and CPU as well as facilities such as servers and web service. It allows businesses and individuals to subcontract their computing needs as well as trust a network provider with its data warehousing and processing. The fact remains that cloud computing is a resource-finite domain where cloud users contend for available resources to carry out desired tasks. Resource management (RM) is a process that deals with the procurement and release of resources. The management of cloud resources is desirable for improved usage and service delivery. In this paper, we reviewed various resource management techniques embraced in literature. We concentrated majorly on investigating game-theoretic submission for the management of required resources, as a potential solution in modeling the resource allocation, scheduling, provisioning, and load balancing problems in cloud computing. This paper presents a survey of several game-theoretic techniques implemented in cloud computing resource management. Based on this survey, we presented a guideline to aid the adoption and utilization of game-theoretic resource management strategy.

The world has gradually embraced Cryptocurrency at various levels of capacity and it is not governed or regulated by any Control system. It has over time been used by participants as a means to invest despite the volatility of the market. Though Government does not have the means to outright stop the virtual marketing deals of Cryptocurrency, recently Nigerian government called for deposit money banks to close all corresponding accounts which are perceived to be involved in Cryptocurrency trading. The Crypto market has evolved as the digital and internet world exponentially evolved. Sadly, Cryptocurrency has been misused by illegal participants and exploited wrongly which has caused a lot of worrisome issues around the world like loss of funds, hacking of financial databases, terrorist financing, and identity fraud. This paper aims to identify the methodology surrounding the world of Cryptocurrency and how advancement in technology through artificial intelligence can help solve ethical issues related to cryptocurrency trading. Based on these appraisals, we highlighted procedures to provide a safer, secure, and relatable market for every interested individual.

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With technology impacting several sectors, it can be imagined that the financial sector has a lot to benefit from the increasing level of technological innovations. These institutions take from the surplus of the economy and lend to the deficit sectors of the economy. Individuals and organizations obtain credit facilities from financial institutions to meet basic needs and boost their businesses. However, the stability of the economy is better guaranteed when borrowers pay back the loans availed to them rather than default. This study aims to identify the effectiveness of Random Forest in credit scoring using 32,581 observations. The study proved that Random Forest provides better output accuracy of 91% based on Gini Index for variable selection according to the level of importance when compared to Decision Tree with an output of 83%. It offers better credit scoring accuracy and credit rating as a result of its classification power. The objective of the study is to point out the random forest predictive strength using an unprocessed German credit dataset from Kaggle and to provide an explainable framework sufficient for Financial Institutions and banks to make decisions when granting loans to existing and new applicants.