Security and Intelligence

GraphPolaris approaches security and intelligence challenges by analyzing data insights and tracking potential risks in the ecosystem through visualizations, in order to provide next-best-actions based on mitigation and prediction scenarios.

Anomaly Detection and Intelligence

Graph databases can model relationships between various entities in the networked landscape, such as IP addresses, domains, users, devices, and malware. By integrating threat intelligence feeds, logs, and network traffic data into a graph database, organizations can identify patterns and anomalies indicative of cyber threats such as malware infections, phishing campaigns, and insider threats.

Fraud Detection and Prevention

GraphPolaris provides a deep understanding of the contextual relationships between policyholders, claims, and other entities involved in insurance transactions. With graph analytics, insurers and auditing bodies can effectively detect patterns in the networks indicative of fraudulent activities such as coordinated fraud rings, exaggerated claims, and identity theft.

Threat Exploration

GraphPolaris is able to mine large amounts of historical data on security events, threat intelligence reports, and attack tactics. By querying and exploring this data with graph analytics, security analysts can proactively search for indicators of compromise, new attack patterns, or emerging threat actors.

Fund Class Integration

Model relationships between traditional and alternative fund classes. By analyzing these interconnected datasets with graph analytics, fund managers can integrate alternative investments into their portfolios, identify opportunities for diversification, and enhance risk-adjusted returns. GraphPolaris can help visualize correlations between different asset classes, identify portfolio gaps, and optimize fund allocation and yield.