Leveraging AIOps in the Financial Sector


When was the last time you walked into a bank to withdraw money? And how often do you swing your checkbook? These once routine manual processes are now mostly digital, even leading some financial giants to proclaiming themselves technology companies.

While many keep pace with consumer demands for digital services, few organizations are implementing the advanced automated technologies that will help them stay competitive in today’s digital age. Just over half (57%) of banks and credit unions started their digital transformation before this year, according to Cornerstone Advisors “What’s going on in the banking industry 2021?”. And the survey indicates that only 14% of financial institutions (which are at least halfway through their digital transformations) have implemented machine learning tools.

But what does machine learning have to do with the financial industry?

Benefits of AIOps in the financial sector

AIOps, or Artificial Intelligence for IT Operations, uses big data analytics, machine learning, and automation to simplify the way IT operations teams support and manage modern, decentralized IT environments. By automating mundane tasks, providing actionable information, and predicting outages, AIOps tools help increase system performance and availability.

In an industry where IT is no longer a support function but the foundation of service delivery, service assurance is at the heart of a company’s success. And, in today’s complex IT architectures, AIOps tools are the only path to continuous service assurance.

Let’s take a look at some of the innovative ways AIOps can help financial institutions compete in today’s digital economy:

1. Provide a superior customer experience. “Customer experience” was once synonymous with “customer service”, but that definition has changed with the move to digital financial services. Today, technology is the backbone of the customer journey, and the number of system errors and the amount of downtime shape the overall customer experience. AIOps tools help IT teams mitigate issues impacting services by identifying incidents and providing actionable insights for rapid solutions. This reduced downtime is critical in the financial industry as there could be serious repercussions for customers who cannot access their bank accounts online.

2. Optimize operational efficiency. Streamlining internal operations is essential as the world’s largest companies like Amazon, Google and Facebook find their way into the financial services game. AIOps can help traditional players stay competitive by tightening their belts. With a properly orchestrated system, AIOps can detect anomalies that intercept money laundering and other fraudulent activity. And these tools can automate low-level IT teams’ tasks, freeing up time to focus on high-value tasks such as innovating new technologies that deliver real business value.

3. Mitigate Growing Cyber ​​Attacks. As financial firms manage sensitive customer information, malicious actors will continue to target these firms with growing and increasingly sophisticated cyber attacks. And the stakes are high – companies that experience breaches face plummeting stock prices, fleeing customers, significant monetary losses, and even lawsuits. AIOps is moving into the cybersecurity space as these tools can help provide 24/7 monitoring of ever-complex financial systems, detect signs of a cyber attack (rather than an ordinary IT problem) and to trigger a defense process. the system against bad actors.

Use case: a financial company adopts the AIOps

My business Helped a $ 100 billion global financial institution inundated with alerts decommission its legacy platform and operate an advanced event management tool AIOps. Before the company implemented AIOps and the old monitoring platform detected an incident, operations support hosted heavy yard calls that could include up to 100 employees. The teams participating in these calls did not have a single source of truth or machine learning capabilities, so they would be examining their own disparate monitoring tools and siled data. These disjointed tools, manual processes, and data silos resulted in slow Mean Time to Resolution (MTTR) and the business lost significant revenue.

When our team set up AIOps capabilities, the financial institution reduced its MTTR by 40% in the first six months, which means greater availability of services to customers and more revenue for the business. AIOps is only scratching the surface of optimizing operational efficiency, but has already reduced the company’s tool footprint by more than 50%, saving millions of dollars in license fees and lowering costs. maintenance and operation of these tools.

With rising customer expectations, fierce competition and growing concerns about cybersecurity, companies in the financial sector need to focus more on advancing their digital transformations and invest in automated technologies like AIOps. These tools will provide a competitive advantage to delight customers, streamline internal processes and fight cyberattacks.


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