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Generative AI insights in treasury and finance

Amidst the evolving landscape of technological innovation, the prominent emergence of artificial intelligence (AI) and generative AI, with their significant promise and potential, has captured the widespread attention of treasury and finance professionals, prompting them to experiment with these technologies both personally and professionally.

However, beyond the customary hype that surrounds emerging technologies, are there substantial grounds for treasurers to focus and support traditional AI and generative AI so their organizations can effectively harness the combined strengths of humans and technology?

“Yes. Treasurers are unequivocal in their support of AI and generative AI, as shown by their actions and expectations to roll out AI in the near-term”,  stated the 2024 Generative AI in Treasury and Finance Survey Report underwritten by the Cash Management Leadership Institute (CMLI) and powered by Strategic Treasurer.* 

The inaugural edition of this survey report polled 145 finance and treasury practitioners from early December 2023 to the first week of January 2024 across North America, Europe, Asia-Pacific, Africa, Latin and South America.

In this standalone survey, the actions, attitudes, and plans of corporate treasury executives and providers, including fintech and banking respondents, are meticulously documented. Here are the key findings:

AI’s foremost challenge: Enhancing cash forecasting accuracy

Although there was notable overlap, corporate respondents exhibited higher expectations regarding AI's role in addressing treasury and finance challenges compared to providers, particularly in areas such as cash forecasting accuracy, manual reconciliation tasks, and the creation of draft reports for internal use.

Source: The 2024 Generative AI in Treasury and Finance Survey Report

Cash forecasting accuracy stood out as the top priority for both corporate and provider respondents, with 65% of corporates and 56% of providers identifying it as the primary area for AI utilisation. This shared emphasis underscores the pervasive interest in incorporating AI-driven solutions to improve forecasting accuracy and integrate them into business strategies.

“When asked in a separate question how they perceived the potential impact of AI on cash forecasting accuracy, 92% of corporate respondents saw the impact as either significantly positive (38%) or moderately positive (54%). The remaining 8% were neutral, with no one seeing a negative impact”, as outlined in the survey report.

With respect to manual reconciliation tasks, over half of the respondents, including 55% of corporates and 53% of providers, foresee AI addressing the challenges associated with manual reconciliation.

In relation to creation of draft reports for internal use, nearly half of the corporate respondents hold the view that AI will facilitate the generation of such reports for internal purposes. According to the survey report, “Corporates held this view far more strongly than providers, with a 12 percentage point gap between the corporate (47%) and provider (35%) responses.”

Conversely, providers demonstrate marginally higher expectations than corporate respondents regarding AI's ability to tackle challenges in areas such as aggregation and normalization of data, payment security and fraud prevention, risk management, and strategic decision making and analysis.

Fifty percent of providers and almost an equivalent number of corporate respondents, believe that AI will be beneficial in dealing with challenges related to both data aggregation and/or normalization (48%), and payment security and fraud prevention (46%).

In terms of risk management, 38% of providers and 32% of corporate respondents identify AI technologies as a useful tool that can strengthen their ability to identify and mitigate risks. As for strategic decision making and analysis, this category registers below one-third for both sides, with 32% of providers recognizing AI’s role in strategic analysis and decision making processes, compared to 26% of corporate respondents.

Generative AI utilisation: Risk identification and exposure assessment

Source: The 2024 Generative AI in Treasury and Finance Survey Report

In line with the report’s analysis, the majority of organizations envision using generative AI for risk identification and exposure evaluation (62%) and leveraging public information to assess counterparty exposures (52%). Nevertheless, there is considerable uncertainty among companies concerning the use of generative AI for examining and recommending actions for FX exposures (46%) and investment options (42%).

Furthermore, “When asked about their current and planned use of AI in three specific areas, cash flow forecasting automation was the only area where over half of respondents expected to use AI within just a year or two. Fraud-related activities (47%) and smart payment settlement processing (43%) took second and third place. Another 10-12% plan to start using each of these areas in over two years.”

In conclusion, generative AI is expanding rapidly, poised to become one of the most disruptive technologies of our time. As generative AI accelerates digital transformation, it becomes imperative for treasury and finance executives to gain valuable insights into its current utilisation activity within treasury operations, as well as the future plans envisioned by their organizations.  

To assist treasury and finance practitioners in embracing generative AI to enhance cash forecasting accuracy, enable superior fraud detection and prevention, reshape the landscape of decision intelligence, and more, we recommend that treasury and finance professionals download, review and benefit from Strategic Treasurer’s 2024 Generative AI in Treasury and Finance Survey Report (sponsored by CMLI).


⃰ Disclosure: Strategic Treasurer owns CTMfile.

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