VCasalo Luis

Cloud computing has provided many opportunities to businesses and individuals. It enables global and on demand network access to a shared pool of resources with minimal management effort. However, this bliss has become a problem for latency-sensitive applications. To improve efficiency of cloud and to reduce the amount of data that needs to be transported to the cloud for data processing, analysis and storage, a new network architect technology 'Fog Computing' has been introduced. In fog computing, small applications and resources are processed at the edge of the cloud, rather than processing entire applications on the cloud.

Indian banking and digital banking system are connected and it is continuously evolving. Today with the introduction of cashless economy, central identity service Aadhaar, Payment infrastructure revamp with UPI, Telecom providers acting as banks, payments bank like PayTM, emergence of FinTechs(Financial Technologies) and introduction of private agencies to deal with digital payments have given a new horizon to digital banking services. The importance of Cloud banking, Big Data Analytics and Artificial intelligence is increasing day by day.

cloud computing is a general term used to depict another class of system based computing that happens over the web. The essential advantage of moving to Clouds is application versatility. Cloud computing is extremely advantageous for the application which are sharing their resources on various hubs. Scheduling the errand is a significant testing in cloud condition. Typically undertakings are planned by client prerequisites. New scheduling techniques should be proposed to defeat the issues proposed by organize properties amongst client and resources. New scheduling systems may utilize a portion of the customary scheduling ideas to consolidate them with some system mindful procedures to give answers for better and more effective employment scheduling. Scheduling technique is the key innovation in cloud computing. This paper gives the study on scheduling calculations. There working regarding the resource sharing. We systemize the scheduling issue in cloud computing, and present a cloud scheduling pecking order.

Purpose – Considering the increasing impact of Artificial Intelligence (AI) on financial technology (FinTech), the purpose of this paper is to propose a research framework to better understand robo-advisor adoption by a wide range of potential customers. It also predicts that personal and sociodemographic variables ( familiarity with robots, age, gender and country) moderate the main relationships. Design/methodology/approach – Data from a web survey of 765 North American, British and Portuguese potential users of robo-advisor services confirm the validity of the measurement scales and provide the input for structural equation modeling and multisample analyses of the hypotheses. Findings – Consumers’ attitudes toward robo-advisors, together with mass media and interpersonal subjective norms, are found to be the key determinants of adoption. The influences of perceived usefulness and attitude are slightly higher for users with a higher level of familiarity with robots; in turn, subjective norms are significantly more relevant for users with a lower familiarity and for customers from Anglo-Saxon countries. Practical implications – Banks and other firms in the finance industry should design robo-advisors to be used by a wide spectrum of consumers. Marketing tactics applied should consider the customer’s level of familiarity with robots. Originality/value – This research identifies the key drivers of robo-advisor adoption and the moderating effect of personal and sociodemographic variables. It contributes to understanding consumers’ perceptions regarding the introduction of AI in FinTech.