Realize Gen AI Value in Financial Services: Moving Past Roadblocks
5 min readOver the past two years, leaders in the financial services industry (FSI) have been racing to implement the next game-changing Generative AI (Gen AI) solution. While there have been notable successes and steps forward, many institutions that have begun their Gen AI journey now find themselves facing new challenges as they seek to fully realize the technology’s value.
SoftServe recently commissioned a global study by Forrester Consulting to uncover where Gen AI adoption currently stands in FSI and what the expectations are concerning its future. The results were telling: Despite an initial fervor, early adopters have hit a wall as disillusionment has crept in.
Notably, 73% of FSI respondents believe that they have already achieved maximum value from Gen AI or will do so within the next 12 months. However, we believe that this is largely due to a lack of focus. The study also shows that FSI adopters are spreading their Gen AI initiatives across departments evenly rather than strategically planning and focusing on where the true value lies and taking appropriate steps toward implementation.
Despite common challenges, our clients continue to show an increasing interest in Gen AI. For example, according to SoftServe’s own workplace data, in the first half of 2023, Gen AI accounted for only 10% of our AI initiatives — a number that increased to 40% by the fourth quarter of that year. Trends observed so far in 2024 show that the upward trend continues.
So, how can you maximize value from AI after feeling stuck in the mud? By stepping back, realizing where needs lie, and strategizing.
Overcome obstacles to Gen AI adoption
Tapping into the full potential of Gen AI requires preparation. Organizations must have a plan in place and prepare infrastructure and data prior to rolling out pilot programs.
Roadmapping – Collaboration between technology and business is essential to identifying use cases and establishing realistic expectations of Gen AI. As organizations are just beginning to understand the technology and its benefits, detailed roadmaps must be established to adopt solutions that deliver the best ROI.
In our experience with roadmapping, one SoftServe client needed help in establishing Gen AI use case prioritization. We developed our Rapid Prioritization Framework to score business value, technical feasibility, and readiness. In doing so, we were able to cluster and prioritize use cases which were then developed and rapidly prototyped in a sandbox.
Infrastructure – The Forrester Consulting study showed that 31% of FSI organizations had trouble building prototypes and 52% faced challenges rolling out models. Infrastructure upgrades and core modernization address these issues.
Our client, a global custodian bank, struggled with AI model deployment due to disparate platforms. We worked with them to implement a ModelOps platform that streamlined accountability and monitoring of AI models which, in turn, led to a quicker time-to-market.
Data governance – The effectiveness of a Gen AI initiative is dependent upon data quality and availability. Of the FSI leaders surveyed worldwide, 83% predict an increased importance of governance as they develop new use cases.
Recently, we worked with a banking client that wanted to use data to develop chatbots and improve marketing strategies. We used infrastructure as code (IaC) to create an automated cloud infrastructure for the bank's data management system, enhancing risk management and customer activity analysis while supporting Gen AI solutions.
Looking ahead
While the last few years have been dominated by the hype of Gen AI, now it’s time for FSI organizations to refine their focus and efforts in order to get the most value from new initiatives. Common hurdles may have led to disillusionment about the promise of Gen AI in financial services, but they can be overcome with the right strategies.
