There’s a reason the financial services sector is considered part of the critical national infrastructure. Every day, people depend on their banks for transactions that feed them and keep them housed. Even a brief disruption to those financial services has ramifications that ripple throughout society and the economy, impacting people, businesses, government, trade, and commerce. That’s why keeping systems running smoothly is critical to any financial institution.
These challenges grow exponentially each year as financial services companies continue to innovate. More functionality means more system complexity and a larger attack surface, which makes systems more difficult to monitor from end to end. This has grave implications for reliability, compliance, security and overall resilience.
AI and machine learning are crucial for detecting sophisticated attacks and maintaining the integrity of financial systems because the sheer volume of data flowing through these systems makes it difficult to manually monitor them for security and optimal performance. Traditionally, IT teams have had to rely on reactive firefighting rather than proactive solutions to infrastructure issues.
More complexity means more difficulty managing system performance and maintaining uptime—and with that, security, compliance and observability teams are tasked with proactively securing a larger number of potential gaps that internal and external threat actors can slip through.
Enter AI
The solution to these challenges lies in artificial intelligence (AI). This technology is becoming central to modern security and observability tools that help financial companies to monitor their systems and the processes that they support from end to end. This discipline, known as AIOps, offers powerful automation capabilities that allow human teams to cope with a rising tide of system telemetry.
That’s why nearly all respondents (97%) in @Splunk’s 2024 State of Observability Report said they are currently using AI/ML-powered systems to enhance observability operations — a significant jump from 2023, when 66% reported adoption.
Splunk now uses generative AI, an advanced branch of artificial intelligence, to empower users in security and observability roles. The Observability Cloud and Security platforms now include generative AI-powered assistants that enhance IT visibility to make threat detection more proactive. These tools sift through vast amounts of data, automatically identifying anomalies and potential threats that human teams might miss.
Administrators can also use generative AI to interact with data more easily thanks to the Splunk AI Assistant for SPL. This uses generative AI to translate natural language queries into Splunk Processing Language, the underlying syntax for interacting with Splunk machine data.
Splunk has also built generative AI into its IT Service Intelligence (ITSI) to make life easier for administrators. An AI-powered Configuration Assistant makes it easier to set up the product using natural language interactions, making financial services companies productive more quickly. Another tool in the product, Drift Detection for KPIs, watches key metrics to ensure that they are not drifting outside accepted norms, giving financial services companies ample time to find and correct the underlying cause. A complementary feature, entity-level Adaptive Thresholds, prevents false positives from triggering false alerts that would distract employees.
Why financial services firms need Splunk’s AI
Splunk generative AI capabilities offer several key benefits for financial services firms. Chat-like AI interfaces enable new team members to get up to speed more quickly in understanding Splunk’s capabilities and documentation while allowing them to explore data iteratively, leading to deeper insights. Fast SPL query generation enables analysts to create dashboards and troubleshoot issues more quickly while translating complex code into natural language also helps team members to understand and modify existing queries, building on each others’ work.
A small investment in an AI-powered observability platform yields big benefits in an era where technology infrastructure is both a critical asset and a potential point of failure. This powerful technology gets financial services companies ahead of the curve, preparing them for IT infrastructure and cybersecurity problems so that they can eliminate them quickly without disrupting their all-important operations.