Money, the medium of exchange has seen significant transformation over centuries. In the last few hundred years, money has been regulated by banks. Such regulation of the flow of money in itself has become a money making venture becoming the main stay of several kinds of institutions including banking institutions. The paper focuses on the emerging trend of the use of mobile devices to facilitate the payment of goods and services. This is essentially, using a mobile phone to perform some of the duties of traditional banks. This fast paced substitution of the mobile phone with traditional banking is sometimes viewed as a threat to the existence of banks in Ghana. The paper finds, through the use of empirical data and interviews, that although, banks may lose minimally in the short term, mobile money is actually more complementary and will only fast track the achievement of the goal of a cashless economy.

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Cloud computing is a new archetype that provides dynamic computing services to cloud users through the support of datacenters that employs the services of datacenter brokers which discover resources and assign them Virtually. The focus of this research is to efficiently optimize resource allocation in the cloud by exploiting the Max-Min scheduling algorithm and enhancing it to increase efficiency in terms of completion time (makespan). This is key to enhancing the performance of cloud scheduling and narrowing the performance gap between cloud service providers and cloud resources consumers/users. The current Max-Min algorithm selects tasks with maximum execution time on a faster available machine or resource that is capable of giving minimum completion time. The concern of this algorithm is to give priority to tasks with maximum execution time first before assigning those with the minimum execution time for the purpose of minimizing makespan. The drawback of this algorithm is that, the execution of tasks with maximum execution time first may increase the makespan, and leads to a delay in executing tasks with minimum execution time if the number of tasks with maximum execution time exceeds that of tasks with minimum execution time, hence the need to improve it to mitigate the delay in executing tasks with minimum execution time. CloudSim is used to compare the effectiveness of the improved Max-Min algorithm with the traditional one. The experimented results show that the improved algorithm is efficient and can produce better makespan than Max-Min and DataAware.