Banks, insurance companies, and financial institutions have a common urgency to face: fraud. From money laundering to insurance fraud to bank fraud, each of these organizations is required to detect, sometimes complex, fraud schemes. The data visualized often combine customer information, claims details, financial records, watch-listed individuals or organizations. For them, graph visualization is a good way to detect suspicious connections or patterns. It’s also an intuitive way to investigate fraud rings and criminals networks ramifications.
Today you’ll find cyber, or IT, security in many large organizations, financial institutions, and security consultancy services. Organizations need to protect themselves from vulnerabilities like zero-day vulnerabilities and DDoS or phishing attacks. They collect data from servers, routers or application logs and network status in order to detect suspicious activity. Graph visualization is a great tool to digest this data and detect suspicious patterns in a glimpse. It makes the finding of compromised elements easier thanks to the visual exploration of connections.
Almost every government has its intelligence agency. To support law enforcement, national security or military objectives, these organizations collect and analyze data from various sources. The detection and identification of terrorist networks, for instance, became a crucial objective in the past decades. Visualizing connections between people, emails, transactions or phone records is a key to ease such investigations.
IT operations management
The field of IT operations management keeps growing with our increasing reliance on computer systems, networks and the growth of the Internet of Things. But because of the growing complexity of infrastructures, managing networks is often a challenge. Graph visualization allows IT managers to visualize dependencies between their assets (servers, switches, routers, applications, etc). It’s an intuitive way to perform impact or root cause analysis.
Numerous mature organizations implement enterprise architecture management. It consists of synchronizing business and IT data. The goal is to analyze, plan and transform the business processes, applications, data and infrastructure to maintain the organization ability to change and innovate. With graph visualization, enterprise architects can visualize the organization assets and their dependencies. It helps to conduct impact analysis, obtain insights on the current situation (as-is) and plan the right actions.
Protein interactions, drug compositions, disease networks: for life science data analysis almost everything is about connections and dependencies. However, the large amount of data often makes it difficult for researchers to identify insights and look for dependencies. Graph visualization makes large amounts of data more accessible and easier to read. It has many different applications, from linking drugs with adverse events and diseases with phenotypes to visualizing network or understand how diseases spread.