Network Intelligence for Financial Services

Financial services networks have demanding requirements that combine consumer-facing reliability (digital banking, payments, claims processing) with infrastructure-grade latency sensitivity (trading systems, market data, execution paths). Kentik supports financial services by unifying traffic analytics, BGP routing context, synthetic transaction monitoring, device telemetry, and cloud flow data in one platform — providing the comprehensive visibility teams need to detect performance issues before they affect transactions. AI-driven investigation through Kentik AI Advisor accelerates root cause analysis during incidents, while DDoS detection and compliance reporting capabilities address the security and regulatory requirements unique to financial environments.

Synthetic transaction monitoring for financial services requires capabilities beyond generic web monitoring: tests that emulate real transaction flows (multi-step workflows, API call chains, authenticated sessions), measurement from network vantage points relevant to the business (specific data centers, branch networks, trading venues, customer geographies), correlation with underlying network telemetry to attribute issues to specific causes, and the ability to validate critical paths continuously rather than only during periodic audits. Kentik supports these requirements with synthetic agents that run from globally distributed locations and customer-deployed positions, transaction tests that capture multi-step workflows, and tight integration with flow analytics and BGP context so synthetic test failures can be traced to their underlying network causes.

Ultra-low-latency trading requires network monitoring that operates at the same speeds and precision as the trading systems themselves: sub-millisecond timing measurement, high-frequency device telemetry, microburst detection that catches sub-second congestion events, and correlation between network behavior and trade execution quality. Kentik supports this through gNMI streaming telemetry at native subscription rates, flow analytics enriched with timing precision, and synthetic tests that measure round-trip latency from trading infrastructure to exchanges and market data sources. Trading operations teams use this to detect path degradation that affects execution quality, validate that critical trading paths remain optimal, and identify when changes to peering, transit, or carrier services begin to affect performance.

Lateral movement and unexpected east-west traffic patterns are key indicators of security compromise in financial environments — especially across the segmentation boundaries that compliance frameworks (PCI DSS, SOX, GLBA) require to be enforced. Kentik supports detection by capturing east-west flow data across data center, cloud, and Kubernetes environments, enriching each record with workload and business-context tags, and surfacing anomalous communication patterns (workloads communicating with services they don’t normally reach, traffic crossing segmentation boundaries it shouldn’t, unusual protocol usage between hosts). Security teams use this to detect suspicious activity early, validate that segmentation policies are actually enforced, and produce forensic evidence during incident response.

Financial compliance reporting requires evidence of traffic patterns, access controls, and forensic reconstruction capability across timeframes that often exceed standard log retention. Kentik supports this with full-fidelity flow retention (120 days standard, with extended retention available for specific compliance regimes), enriched flow records including geographic, AS path, security, and business context, customizable dashboards and exportable reports for auditors, and APIs for compliance tooling integration. The platform supports common financial frameworks (PCI DSS, SOX, GLBA, GDPR) through evidence that flow data exists to verify network access patterns, segmentation enforcement, and security control effectiveness over compliance-relevant time periods.

egmentation compliance in hybrid financial environments requires consistent visibility into traffic between zones regardless of where they exist — on-premises VLANs, AWS VPCs, Azure VNets, GCP VPCs, or Kubernetes namespaces. Kentik provides this unified view by ingesting flow data from all of these environments into a single platform and tagging each flow with the zone, application, and business context it belongs to. Financial compliance teams verify that segmentation between trading, retail banking, payments, and corporate networks is enforced consistently; surface violations across environment boundaries; and produce audit-ready reports showing which traffic crossed segmentation boundaries during any given period.

DDoS attacks against financial services target high-value endpoints — online banking portals, mobile banking APIs, trading systems, payment processors — and any disruption directly affects revenue and customer trust. Kentik supports DDoS protection through real-time detection using flow analytics across on-premises and cloud environments, configurable attack-profile algorithms that minimize false positives during high-volume legitimate periods (trading session opens, payday processing, seasonal payment surges), and automated mitigation through BGP Flowspec, RTBH, or third-party scrubbing services (Cloudflare, Radware, A10). Full-fidelity flow retention supports post-event forensics for regulatory reporting and threat intelligence development.

Financial services networks depend on numerous third-party providers — market data vendors, SWIFT/payment networks, cloud providers, CDN providers, transit carriers, and SaaS applications — and outages or degradations at any of them can affect business operations. Kentik supports third-party dependency monitoring through synthetic tests that measure performance to specific third-party endpoints, BGP and AS path analytics that reveal routing changes affecting third-party reachability, and flow data that quantifies traffic to and from each third party over time. Teams use this combination to detect emerging third-party performance issues early, validate that contractual SLAs are being met, and produce evidence during disputes about which side of the relationship caused a given incident.