AI-driven end-user monitoring promises significant value for financial businesses' back-office ops

Artificial intelligence is already reshaping the financial sector with 75% of banking, pensions and other financial firms using AI, and another 10% planning to use it over the next three years. According to the second EY European Financial Services AI Survey, a significant 91% of UK financial firms have integrated artificial intelligence into their operations, to some degree, aiming to boost productivity and efficiency.

There are a number of areas where AI can enhance back-office operations, from improving data accuracy and providing predictive insights to streamlining workflows and enabling better- decision-making. But are there any potential drawbacks when automating back-office operations?

Some organisations claim initial setup costs, integration challenges, and the need for employee training as potential drawbacks, but for fintech companies specifically, the benefits of automation significantly outweigh the challenges. For example, one financial services enterprise automated its IT operations, including common IT tickets or tech issues. By running these automations, they saved 8,704 hours annually – which equates to four full-time resources. 

Obviously, the impact of automating back-office operations can be significant, but you must prioritise two things to make them work. Firstly, visibility. Fintech companies need to know what is running throughout their operations, and the best way to do this is to collect data directly from the devices running those operations. Secondly, the human in the loop. Today’s back-office automations are going to be AI-driven. Human judgment is invaluable in complex situations where automated systems may miss important nuances or make incorrect decisions. So keeping humans in the loop is a critical key to success.

The most significant impact I’ve seen of AI on back-office operations has been the evolution of IT in financial services organisations. Technology disruptions for fintech companies equate to money lost. If the cost of device downtime is a failed trade, millions of pounds can be on the line. The most forward-thinking companies recognise this and have used AI to enhance back-office IT operations to transition from reactive to proactive, or even predictive. 

Organisations are now using AI to identify and fix issues before they disrupt the business. By using advanced data analytics, AI can deliver deep insights into IT systems, enabling proactive and predictive IT management, thereby reducing downtime and enhancing service delivery.  For one global financial services company with 75,000 employees that meant 350% faster identification of IT outages and tech issues by being more proactive. 

While not limited to fintech, innovations in the digital employee experience, or DEX, have impacted fintech back-office operations the most.  DEX is not a new idea; it simply describes how end users (either employees or customers) interact with IT devices. But with advances in data analytics and AI/ML, the impact of DEX can be massive. 

To deliver the best DEX, fintech organisations need high-quality breadth, depth, and history of data from their entire IT estate. This data offers complete visibility so the back-office IT teams know what hardware, software, networks, systems, and devices are running in the digital environment at any given time. Once IT teams have that visibility, they can identify problem areas to boost productivity, efficiencies, and cost savings. 

For example, one financial institution identified unused software licenses across the enterprise.  By cancelling the unused licenses, it saved over £3.4 million. 

AI is transforming back-office operations in the financial sector and, despite initial concerns about setup costs and integration challenges, the benefits clearly outweigh the drawbacks, as demonstrated by companies saving thousands of work hours through automation.