BANKING AND FINANCE
Real-time intelligence for comprehensive
insights and security
Real-time, actionable intelligence to ensure peak platform performance, reliability, and security.
Deliver a world-class customer experience
Mitigate incidents. Ensure security and performance
LOGIQ.AI allows FINANCIAL INSTITUTIONS to run IT and cloud infrastructures with confidence, free from worries and anxieties of unexpected outages and security incidents.
Using InstaStore’s always-hot and indexed storage less architecture, volume and velocity of machine data and events can be collected, analyzed, and actioned on at scale. InstaStore guarantees the fastest response to compliance and regulatory requests besides providing multi-year trends and comparative analysis.
Scale, security, and agility are the tenets of the LOGIQ.AI architecture ensuring an always-on and secure experience for customers.
Hyperscale performance
A microservices and storage-less architecture equips the LOGIQ.AI platform to handle and provide compliance and control on huge volumes of data streaming in real-time into the platform.
Automated and intelligent pattern-recognition and anomaly detection with support for alerting and a variety of incident response options allow banking and FINANCIAL INSTITUTIONS to serve up best-in-class customer experiences.
Making compliance a breeze
LOGIQ.AI’s built-in InstaStore provides long term data retention to the most extreme compliance environments so legal teams can meet stringent compliance standards like PCI/DSS, SOC2, and GDPR. The use of Object storage for InstaStore means that firms can also achieve many FINRA compliance requirements for data retention, archival and immutability.
The Observability data pipeline control provides 1-Click privacy controls to manage PII information that is detected in data streams. PII data so often leaks through the cracks from within logs can be identified in real-time and masked among other actions before they rest in the company’s data stores. This can not only protect your financial data, but also eliminate the significant amount of time and resources that would otherwise be needed to fix software systems at the source.
