Getting visibility across data silos is problematic for most financial institutions. The vast array of legacy systems, enormous data volumes, shifting regulatory requirements, and new technologies has made the practice of observability increasingly harder for organizations. So how should technology leaders think about prioritizing their investments to improve team productivity, lower costs, and drive greater intelligence into their decision making?
In our latest financial services webinar, we discussed this topic and more with an esteemed panel of technology and business executives in financial services. The panel featured:
- Martin Moeller, Sr. Financial Services Industry Executive & Banking Lead Western Europe, Microsoft
- Thibaut Barrault, Monitoring Application Manager, Société Générale
- Stéphane Lopes, Technical Architect, Société Générale
- Francesco Di Stefano, Senior Solutions Architect, Elastic
The group had several excellent points and recommendations — here are just a few!
AI and ML are essential vehicles for success
Artificial intelligence (AI) and machine learning (ML) are hot topics across industries, but their value within financial services is still being recognized. Artificial intelligence can enable users to perform detections, improve forecasting, and make sense out of huge amounts of data. Out of the box tools provided by observability solutions can make predictions about future events and can often be integrated with other AI technologies. “Many of these features are provided automatically so that users don't need to be experts to be able to use these technologies,” says Di Stefano.
For the team at Société Générale, artificial intelligence is playing a critical role to help them optimize their IT environment. They are using “machine learning to anticipate issues, run analysis, and predict, for example, if they will be hitting certain thresholds across their IT ecosystem,” says Barrault. They are also seeing this technology being used widely to detect cyberattacks.
By coupling structured data with unstructured data, Moeller is also seeing customers realize increased value from AI, across new use cases. According to Moeller, “artificial intelligence enables users to understand data at a much much deeper level than humans can do, and across disparate environments.” Microsoft is seeing an explosion of artificial intelligence across areas such as security, intelligent process optimization, and market research.
Flexibility, scale, and economics are more critical than ever
One of the most critical components of a good observability platform is flexibility, according to Barrault. The platform needs to span across use cases and grow with the organization. It needs to have integrations with existing and future technology. A good observability platform should have a flexible architecture that enables the organization to tackle new business problems as they arise.
Scalability is also paramount in financial services. “I mean we are talking about an enormous amount of data especially when it comes to traces and metrics and application performance monitoring,” says Di Stefano. An observability solution must be able to scale quickly and seamlessly. That is why Société Générale has deployed Elastic as an “Observability as a Service” for the bank, enabling users to quickly and economically spin up solutions to help them monitor their ecosystem. This enables users to proactively detect issues with confidence, without the need to set up dedicated infrastructure. The service is now being used by over 2,000 users across 800+ applications at the bank.
As financial institutions look to preserve their IT budget, it's also critical to have visibility over resource allocation. Société Générale is assessing usage across applications to see where time is spent, as well as the cost and performance of those applications. By doing a complete assessment, this enables Société Générale to “identify where they can optimize costs and save resources,” says Lopes. By establishing best practices in how Société Générale analyzes this information, it helped the company’s business partners determine the relevant places for investment and prioritization.
The relationship between data sovereignty, compliance, and cloud
For financial services, compliance and regulatory considerations are always top of mind. Storing and securing vast quantities of sensitive information must be done in accordance with industry standards. “Regulations such as GDPR must come into consideration and it's critical to make sure the bank remains compliant as time goes on,” says Barrault. Organizations must consider solutions that enable them to store information in a cost-effective way, but without sacrificing performance — for example, retrieving this information securely shouldn’t be a headache for users.
There is great debate across the financial community about how and when to deploy applications and store data in the cloud. Moeller discussed several ways that Microsoft has been addressing the conversation with customers around the topic of data security and compliance. According to Moeller, not only is your data secure in the cloud, but cloud providers like Microsoft are investing heavily to ensure adherence to data sovereignty and regional compliance standards. Microsoft is continuing to open up new data centers across the globe and has conversations with regulators on a regular basis to maintain client trust at scale.
“Elastic provides a comprehensive solution for managing data in a controlled and secure manner. It gives financial institutions the ability to make informed decisions about where to store their data, based on its sensitivity and regulatory requirements. With our solution, sensitive and personal information can be kept on-premises to comply with strict regulations, while cost-effective and scalable cloud storage can be used for non-sensitive data that may be growing rapidly. This helps organizations maintain control over their data and ensure that personal and confidential information is properly protected,” says Di Stefano.
As FSIs continue to evolve their cloud strategy, it’s important to consider an observability platform that enables you to search and analyze information across on-prem, hybrid, and multi-cloud environments with the ability to shift the data to a different destination as it makes sense.
Joining forces for better client outcomes
As our panel discussed, any observability solution should be able to collect data across an enterprise and provide a central point of view. It should be loaded with outcome-driven features such as embedded artificial intelligence and machine learning to create value out of this data. But more importantly, it’s critical to work with partners that are investing in the space and have a pulse on the latest trends in the financial domain as a whole.
Elastic deployed on Azure offers this and more. By consuming services on the Azure marketplace, you are working with Microsoft — a longstanding leader in financial services that is at the forefront of market innovation. Leveraging services like Elastic on Azure enables FSIs to take advantage of economies of scale, while quickly spinning up new instances as innovation happens. Learn more about Microsoft and Elastic and how you can enable greater, proactive visibility across your IT ecosystem.