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In the article “Operational Risk Management in the Financial Sector”, methodologies and technological innovation trends for managing financial operational risks were discussed. In this article, we will explore the operational Regtech solution offered by Revelis and its related use cases. Revelis’s approach to operational risk controls The Regtech solution by Revelis adopts an approach to…
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Operational risk management is a strategic factor in the financial sector. Operational Risk is defined as the likelihood that financial activities will experience value fluctuations due to unforeseen factors that arise during the regular operations of a bank. Generally, operational risks include: Permanent controls are a fundamental component of the operational risk management system within…
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For modern companies, having a Warehouse Management System (WMS) to handle inventory and track goods is crucial for operational efficiency, responsiveness to market demands, improving delivery accuracy, and reducing downtime. In a competitive environment, goods traceability enables more effective planning, optimizes logistics, and enhances customer service, making it essential for business success. A WMS: why…
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Data analytics is the process of examining and interpreting large amounts of data to extract useful information and support strategic decisions. This process includes collecting data from different sources, cleaning it to eliminate errors or inconsistencies, and transforming it into a more usable format. Subsequently, analytical techniques such as statistical models and machine learning algorithms…
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Risk analysis is now a fundamental step for banks, insurance companies, and financial brokers due to the increasing complexity and rapid evolution of regulations in the financial context. It also represents a significant competitive advantage for these institutions, made possible by Artificial Intelligence (AI) techniques and Big Data Analytics. Compliance and risk management have become…
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Among the various branches of artificial intelligence, Natural Language Processing (NLP) plays an increasingly important role, especially in recent years. This discipline focuses on the interaction between computers and human language, enabling machines to understand, interpret, and generate text in a way similar to how humans do. Initially, before the advent of Machine Learning techniques,…
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In the landscape of modern industry, IoT Intelligence represents a fundamental approach for companies looking to enhance and manage their production processes. One of the most significant challenges for businesses is fully leveraging the potential of the Internet of Things (IoT) to gain tangible competitive advantages. This entails effectively integrating sensors, devices, and digital platforms…
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Computer vision, or artificial vision, is a field of AI that studies algorithms and techniques to enable computers to extract information from images, videos, and other types of data, in order to extract specific semantic information. In particular, computer vision finds a concrete and increasingly widespread application in predictive maintenance, where systems are monitored through…
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