The data democratization in relationship-oriented data analysis, which is the latest approach in data analytics, enables business users to access data and capture insights from connected data.
Category: Relationship Oriented Data Analysis
When the data is analyzed adequately, it is the most valuable guide for many fields. The power of data analysis comes into play to obtain actionable intelligence for crime detection as well.
The e-commerce sector is growing rapidly with the wide spreading of online marketplaces. Unfortunately, this makes the industry the target of fraudsters. In this article, we discuss e-commerce fraud methods and how to detect them with Datactive.
Money launderers can hide well to depict their transactions as legal. However, Datactive reveals hidden connections and patterns in data instantly, so crime rings are no longer invisible.
Many organizations take advantage of artificial intelligence and machine learning solutions. In this article, we discuss how graph technology empowers machine learning processes.
If financial crime organizations are not detected, they cost serious reputational damage and sanctions. The solution is a comprehensive crime intelligence system.
We discuss the concept of data democratization, which we mentioned briefly in “ Data Science Trends We Will Hear Frequently in 2021”.
The 360-degree data view is crucial for effective data analytics to see all details, reach information and insights, and discover potential.
We know the importance of making data-driven decisions in today’s business life*. However, using time in the most effective way while making these decisions is also crucial for the agility of institutions. This is where real-time data analytics comes into play.
Financial crime intelligence systems differ from rule-based transaction monitoring systems, which monitor the transaction and cancel the transaction if fraud is suspected. In this article, we will examine the differences between them.