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Financial Risk Management with Log Analytics

Risk Mitigation. Regulatory Compliance. Agility.

financial-risk-management-log-analytics.jpgBanks use regular financial risk model calculations across all of their lines of business to determine their overall risk profile. Banks’ IT teams run these calculations continuously to ensure that they comply with rules and that liquidity and cash balances are adequate. 


  • Without the ability to monitor and analyze log data in real-time, banks’ IT staff might spend hours poring over log files to trace problems. Job failure detection in this sense is manual and reactive and it can take hours just to isolate the problem in the log entries. 
  • IT staff in development and QA might also find code development and improvement difficult, as many developers might not be able to access the servers where the logs reside. 
  • An application job failure can trigger minimum capital reserve requirements (potentially impacting banking operations and profits), draw the scrutiny of regulators, and leave the bank blind to the level of risk exposure. 


In order to sufficiently analyze and monitor application performance in real-time and ensure a near 100% service level requirement, banks can depend on log analytics solutions. A popular log analytics platform that handles huge data sets and enables cost-savings while maintaining performance, security, and alerting is the open source Elastic Stack (Elasticsearch, Logstash, Kibana, and Beats).  

Regularly working with financial services customers, we bring our expertise to help your organization conduct risk management more effectively using log analytics. Our approach combines the benefits of search engines and big data to process logs, run powerful computations, and provide trend visualization in real-time.

  • Design and implementation - building a log analytics framework for your risk management requirements, compliance policies, and technology preferences.
  • Consulting - helping you select the right deployment strategy for scalability, flexibility, and high ROI.
  • Fine-tuning - responsive to changes in your bank’s requirements, customer expectations, regulations, or other market conditions.
  • Managed services and hosting support - ensuring your application is well-maintained for peak performance.


Financial risk management using log analytics can help banks:

  • Aggregate log data from all of their servers for analysis and alerting 
  • Reduce the time required to identify root causes of problems and allow IT teams to monitor their systems proactively
  • Reduce failure rate of risk calculation jobs, improving code debugs, confidence, and support for Federal Reserve Stress-tests
  • Reduce or eliminate “minimum capital reserve” requirements triggered when risk calculations fail
  • Meet Federal Reserve requirements 

Contact us to learn more about how we can help you design and implement an agile log analytics solution that supports risk management.