Leveraging AIOps in the Finance Industry

When was the last time you walked into a bank to withdraw cash? How often does your checkbook balance? These once-routine manual processes are now primarily digital, even prompting some financial giants to advertise themselves as tech companies.

While many keep pace with consumers’ demands for digital services, few organizations are implementing advanced automated technologies that will help them stay competitive in today’s digital age. Slightly more than half of banks and credit unions (57%) had started their digital transformation before this year, according to Cornerstone Advisors’ What’s Happening in Banking 2021. 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 sector?

Benefits of AIOps in the financial sector

AIOps, or Artificial Intelligence for IT Operations, uses big data analytics, machine learning, and automation to simplify how IT operations teams support and manage modern and decentralized IT environments. By automating regular tasks, providing actionable insights, and anticipating outages, AIOps tools help increase system performance and uptime.

In an industry where information technology is no longer a support function but is the foundation on which to deliver services, service assurance is the foundation of a company’s success. And in today’s complex IT structures, AIOps tools are the only path toward ensuring continuous service.

Let’s dive into some of the innovative ways AIOps can help financial institutions compete in today’s digital economy:

1. Provide a superior customer experience. “Customer experience” used to be synonymous with “customer service,” but that definition has changed with the shift towards digital financial services. Today, technology is the backbone of the customer journey, and the number of system errors and the amount of downtime makes up the entire customer experience. AIOps tools help IT teams mitigate issues affecting service by identifying incidents and providing actionable insights for quick fixes. Reducing downtime is critical in the financial sector as there can be serious repercussions for customers who cannot access their online bank accounts.

2. Improve operational efficiency. Streamlining internal operations is critical given that the world’s largest companies such as Amazon, Google, and Facebook are sneaking into the financial services game. AIOps can help traditional players stay competitive by tightening their belts. With a properly structured system, AIOps can detect anomalies that detect money laundering and other fraudulent activities. These tools can automate low-level tasks for IT teams, freeing up time to focus on high-value tasks such as creating new technologies that deliver real business value.

3. Mitigating the increasing cyber attacks. As financial institutions manage sensitive customer information, malicious actors will continue to target these companies with increasingly sophisticated and increasingly sophisticated cyberattacks. And the stakes are high – companies exposed to abuse face falling stock prices, customer flight, significant financial losses and even legal action. AIOps are moving into the cybersecurity realm where these tools can help provide 24/7 monitoring of constantly complex financial systems, detect signs of a cyber attack (instead of a normal IT problem), and launch a process to defend the system against malicious actors.

Use case: a financial company that embraces AIOps

My company helped a $100 billion global financial institution mired in alerts shut down its legacy platform and harness an advanced event management tool AIOps. Before the company implemented AIOps and the legacy monitoring platform discovered an accident, Operations Support was hosting non-process triage calls that could involve up to 100 employees. The teams working on these calls lacked a single source of truth or machine learning capabilities, so they were looking at their own disparate monitoring tools and isolated data. These disjointed tools, manual processes, and data warehouses caused slow mean time to resolution (MTTR), and the company lost significant revenue.

When our team implemented AIOps capabilities, the financial institution reduced its MTTR by 40% in the first six months, which means greater availability of customer-facing services and more revenue for the business. AIOps are scratching the surface of improving operational efficiency but have already reduced the impact of the company’s tools by more than 50%, saving millions of dollars in licensing fees and lowering the cost of maintenance and operation of these tools.

With increasing customer expectations, fierce competition, and growing cybersecurity concerns, companies in the financial sector need to increase interest in developing their digital transformations and making investments in automated technologies such as AIOps. These tools will provide a competitive advantage in delighting customers, simplifying internal operations, and combating cyber attacks.


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