Digital banking and other online-based financial services have nevertheless emerged to bring the most expensive and easy to use services to users globally. However, with the evolution of digital processing it has resulted in increased risks such as fraud, money laundering and identity theft hence requiring enhanced methods of fraud detection.

Digital banking and other online-based financial services have nevertheless emerged to bring the most expensive and easy to use services to users globally. However, with the evolution of digital processing it has resulted in increased risks such as fraud, money laundering and identity theft hence requiring enhanced methods of fraud detection.

The incorporation of the Internet of Things (IoT) and robotics is changing the construction of smart environments, from homes to industrial structures. This article discusses the architecture of IoT devices and robots by disseminating the main aspects of the software permitting the organization of the IoT and the use of robotic systems, specifically communication methods, data administration, and control schemes.

The combination of Artificial Intelligence (AI) and Machine Learning (ML) with Universal Verification Methodology (UVM) has been thought to revolutionalize semiconductor design, making the process more efficient and accurate as possible. AI and ML strategies are most effective in applications requiring the automated confirmation of time-taking processes that were previously blended with human errors.

Thus, the purpose of this paper is to review the literature regarding the effectiveness of using Predictive Analytics in the healthcare context particularly concerning the prevention of hospital readmissions. The author presents the problems of readmissions and introduces the potential use of predictive analytics in this issue in the introduction. Hence, the survey in the existing literature recognizes and reviews the literature on the status of the research and case studies endorsing the utilization of predictive models in the healthcare sector.

Based on the discussion of generative AI and other successful neoteny complex AI applications such as large language models and synthesis of images and other forms of AI-generated creativity, the efficiency of an application depends much on data management systems. Most of these applications are computationally intensive. Hence, the serving layer being required to have high I/O and response rates, in essence, being real-time.

Efficient IT incident resolution is essential for maintaining operational continuity and customer satisfaction in modern businesses. Despite the advancements in IT service management, many organizations still face challenges in resolving incidents promptly. This study explores the impact of automated scheduling and meeting coordination on the efficiency of IT incident resolution. Leveraging a mixed-methods approach, data was collected from 250 IT professionals across various industries using structured questionnaires and in-depth interviews.

By analyzing the actual security processes and security tasks, it can be concluded that large insurance and healthcare organizations face challenges in their daily work due to the amount of data and the level of cyber threat. Security automation can be described as a modern technology solution that is based on the use of artificial intelligence to enhance measures of security available in an organization. Therefore, the purpose of this paper is to consider employing AI in the automation of the security process in these industries, the benefits and drawbacks associated with its use, and the suggested method to adopt AI.

The advancement of technologies on the web and the constant need for modern applications in today’s world made the architects go with the microservices architecture. This architectural style is about decomposing monumental applications into a set of microservices that can be developed, deployed, and scaled separately. Microservices architecture is very beneficial for different SOAs, as it provides better scalability, fault tolerance, and maintainability. However, it is also associated with problems like inter-service communication, consistently replicated data and service discovery.

Optical Character Recognition (OCR) is a transformative technology that converts various document types, including scanned paper documents, PDFs, and images from digital cameras, into editable and searchable data. This research paper delves into OCR technology, focusing on its application within SAP ERP systems. It examines the significant benefits OCR offers, such as enhancing efficiency, accuracy, and reducing costs by automating data extraction and document processing. The paper also reviews current OCR products in the market, evaluating their advantages and limitations.

AI has developed at a very fast pace and has impacted different sectors, including the financial services sector. AI in AWS has been seen as a revolutionary approach in the field of risk modelling and investment planning, giving heretofore inaccessible information and prognosis. The paper also aims to find out how AWS AI can be implemented in financial services, especially in risk management and investments.

Pharmaceutical industry is embracing Artificial Intelligence (AI) to change how drugs are developed, patient treatments tailored, and clinical trials conducted. However, there are a few issues when it comes to the integration of AI, such as patient safety, privacy and ethnic bias in AI. The purpose of this paper is to discuss the ethical aspects of applying artificial intelligence solutions in the sphere of pharmaceuticals with a strong emphasis on the tension between innovation and health risk.

Contract Management in the Medical Devices field is a very tightly controlled and intricate area that often suffers from inefficiencies and compliance issues. This paper explores how lean methodologies such as Value Stream Mapping can streamline contract workflows, enhance operational efficiency, and ensure regulatory adherence. When bottlenecks are identified, redundancies are eliminated and processes are optimized, organizations can shorten cycle time, increase accuracy, and improve the interaction between all parties.

This article is written to understand the utilization of Artificial Intelligence (AI) with the SAP FI and CO module named FICO for predictive accounting. SAP FICO, coupled with the application interface of Artificial Intelligence, including Machine Learning (ML) and Natural Language Processing (NLP), enables the capacity to consider future financial scenarios in financial planning. Some advantages of predictive accounting include forecasting cash flows, better planning of account budgets, and managing risks. Hence, the paper focuses on cooperation between AI and SAP FICO, using different methodologies, frameworks, and practical cases for their application.

The Organization Control (SOC) Audit is vital in the database domain, as it safeguards and guarantees the privacy of customer data. Encrypting such data is essential for ensuring an organization's security and integrity. This audit process plays a crucial role in enhancing trust and accountability in managing sensitive information, ultimately protecting the organization and its customers.