The banks are known as monetary management institutions because they deal with money. There is a number of customers that a bank daily interacts with. In this technology era, when everything is moving to automation from the beginning step to final product manufacture, medical checkups, medical reports, and evaluation, the banking system is still working on the legacy system. Instead, with the participation and implementation of new Virtual Assistant-powered with AI and Machine Learning technology in the banking sector, the institutions are again using the legacy system or may be bound to use the legacy system. This research will help to elaborate and emphasize the impact of the implementation of automation, using artificial intelligence in the banking business process. This research will be based on the quantitative as well model base prof of system performance using different analytical tools like SPSS. This automation process will help the institutions to enhance profitability, performance, and reduce human dependency. In a nutshell, Virtual Assistants powered with Artificial Intelligence will improve the business process performance in every sector of business, especially the banking sector.
The availability of real-time data on the state of railway facilities and the state-of-the art technologies for data collection and analysis allow transition to the fourth generation maintenance. It is based on the prediction of the facility functional safety and dependability and the risk-oriented facility management. The article describes an approach to assessing the risks of hazardous facility failures using the latest digital data processing methods. The implementation of this approach will help set maintenance objectives and contribute to the efficient use of resources and the reduction of railway facility managers’ expenditures.
The availability of real-time data on the state of railway facilities and the state-of-the art technologies for data collection and analysis allow transition to the fourth generation maintenance. It is based on the prediction of the facility functional safety and dependability and the risk-oriented facility management. The article describes an approach to assessing the risks of hazardous facility failures using the latest digital data processing methods. The implementation of this approach will help set maintenance objectives and contribute to the efficient use of resources and the reduction of railway facility managers’ expenditures.
