In today's competitive financial landscape, maximizing return on investment (ROI) is essential, and generative AI (GenAI) is delivering beyond initial expectations. From slashing research times to enhancing data completeness, the ROI of GenAI in financial services is both tangible and transformative. Financial institutions aren't just adopting GenAI to save time; they're using it to elevate the depth and quality of insights, creating smarter, more agile systems. By driving efficiency and sharpening analytics, GenAI offers returns that outpace traditional methods, making it a game-changer in the financial sector.

Efficiency: more than just saving time

The most obvious and immediate benefit of GenAI for finance professionals is time savings. Take the example of Moody’s Research Assistant, which has been adopted by some key players in wealth management, portfolio management, and credit analysis. Users are reporting a 27% increase in time savings, completing tasks faster by having relevant data aggregated and compiled for them in an easily digestible format, rather than spending hours manually hunting through databases.

But it’s not just about speed. In fact, at one of Moody's largest clients, initial findings showed that users of Moody's Research Assistant had consumed up to 60% more research compared to previous months, despite spending less time doing it. This combination of efficiency and expanded access to information allows financial analysts to make faster, more informed decisions. It’s not just that they’re saving time — they’re also processing more data and reaching better conclusions.

Completeness of information: knowing what you don’t know

Efficiency is only part of the story. GenAI doesn’t just speed up processes; it delivers more comprehensive and insightful results. Financial analysts often grapple with the problem of “not knowing what they don’t know.” GenAI solves this by pulling from a vast array of sources — going beyond the typical reports analysts might consult — and delivering insights within seconds.

In the past, when using traditional methods, a financial analyst might reference a single document because that's what they know to use - they simply may not be aware that a certain concern is referenced in other material. With the GenAI-powered Moody's Research Assistant, however, the same task will likely pull in half a dozen documents or more, offering a more well-rounded perspective that traditional methods can’t match. This is particularly valuable for credit analysts who need to ensure that every possible angle of risk is covered. The use of GenAI ensures that they not only work faster but also smarter, enabling a level of completeness that’s previously been out of reach.

Increased engagement and usage

Another clear sign of AI’s impact is how it’s changing user behavior. Professionals are engaging more deeply with research and integrating it into their decision-making processes. Traditional search methods are being replaced by AI-driven discovery tools, resulting in more relevant content, and users are engaging with this content at a higher rate. They’re consuming and integrating more research into their decision-making process.

This has resulted in a clear shift in how professionals are working - and it's not just surface-level. As these new AI-powered tools help users improve their strategic insights, they demonstrate a high return not only in terms of efficiency but also in the quality and scope of the work being done.

For instance, our research shows that thematic research and strategy pivoting, typically high-level tasks, account for 39% of Research Assistant usage. Meanwhile, credit analysis and monitoring make up 32%, with initial screening and idea generation contributing another 20%. These figures and diverse use cases illustrate how deeply GenAI can be integrated into various workflows and how broad the impact GenAI can be, from the early stages of idea generation to detailed financial analysis.

However, it's not just about the percentages and increases — real clients are seeing tangible benefits. More research consumed means a more comprehensive view of the factors around risk, while less time spent on research can result in an enchanced ability to focus on key strategic deliverables as well as the potential to ameliorate work-life balance.  These gains are directly tied to the depth and breadth of insights GenAI offers, and the narrative of success is likely soon to be echoed across the board. Whether it’s uncovering hidden risks, making faster decisions, or simply doing more in less time, the ROI of GenAI in financial services is clear.

Looking forward: an evolving landscape

While the current benefits of GenAI in financial services are already significant, the evolution is far from complete. Tools and features like Advanced Query are poised to push the ROI of what AI can offer even further, enabling users to make faster, more accurate, and smarter decisions than ever before. As financial professionals become more adept at leveraging these cutting-edge tools, we can expect even more impressive gains in efficiency, accuracy, and output quality. The ripple effects of GenAI adoption will continue to grow, revolutionizing not just individual workflows but entire organizations.

The ROI on GenAI is no longer a theoretical promise — it’s firmly grounded in data and real-world success stories. Whether by increasing efficiency, providing more comprehensive insights, or improving decision-making processes, AI is fundamentally reshaping how financial professionals operate. It delivers returns that outstrip traditional methods, transforming both the speed and quality of financial analysis. When we talk about the ROI of GenAI, it’s about much more than just time saved —it’s about creating a smarter, more agile, and highly responsive financial system that’s better equipped to navigate the ever-growing complexities of modern markets.

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