Uncovering Artificial Intelligence Potential for the Contemporary CFO

Today's CFOs have a remit that reaches far beyond merely financial management; they must assess risks, think innovatively and plan strategically. In today's world of numerous global markets, regulatory fluctuations and innovative technology, CFOs must juggle their usual duties with a multitude of responsibilities that involve both strategy and operations. As the complexity of business operations and the CFO role have expanded, advances in technology have been made to create a more comprehensive CFO tech stack. However, there remain some areas that need improvement. Generative AI is a viable solution, as it has the potential to gather and assess huge data sets, reduce tedious handiwork, and provide insights in accordance with the specific context. We present an analysis of the current finance ecosystem and discuss the potential of genAI to help CFOs and their teams remain ahead of the ever-fluctuating finance landscape. Historically, CFOs have had to rely on spreadsheets and individual software applications to perform financial activities. In the 1990s (Wave 1), ERP systems were introduced to give CFOs access to one singular platform covering accounting, finance and other operations. This was beneficial in terms of improving efficiency and could be costly, requiring advanced analytical powers and only being available to bigger corporations (like SAP, Oracle, Workday and IBM). With Wave 2 came the emergence of cloud-based solutions catering to CFOs needing real-time data and advanced analytics. While these platforms were attractive to middle-market consumers, there still remained a need for technical knowledge, making them a choice of only a select few — Anaplan, Adaptive Insights and Planful being the prime examples. Today's Wave 3 solutions demand user-focused design, swift implementation, and automation as core components. Startups have emerged that enable CFOs to take advantage of advanced AI, accommodating contextual comprehension to give more pertinent results. While a lot of the new offerings are supplementary tools attached to extant solutions as an alternative to standalone platforms, CFOs are empowered to increase output by an order of magnitude with prudent expenditure. Interviews with CFOs have revealed a number of difficulties they are still confronting despite advances in the financial value chain: The financial services sector has been more hesitant about getting involved with genAI than other industries, and it's understandable considering the strict regulation and the need for near-perfection to prevent costly repercussions. Nevertheless, genAI still presents an exciting opportunity to revolutionize delivery solutions, provide more specialized services, and ultimately boost efficiency. There has been an increase in genAI copilot solutions targeting more basic processes that are not as close to the main product or customer. This makes back-office CFO applications ideal places to use these solutions. Although there are many finance processes that require a great deal of precision and human input, genAI is able to vastly improve productivity by providing easy access to data and research, as well as automating personnel tasks that can lead to errors. Here are some illustrations: It is essential to identify how AI will increase customer value, construct with purpose, and pinpoint the correct beginning difficulty to gain quick momentum. We have discovered from successful tools which match the requirements of traditional financial companies and fintechs, as well as conversations with Chief Financial Officers in regards to how startups can build by making use of their variable demands and advanced AI features: The quality of generative AI tools is contingent on the context to which they are exposed, so integrating them directly into existing workflows can leverage their capabilities. An example of this would be the AI chatbot in Excel, which surfaces trends and produces models directly within the Excel interface. This tool needs to be prompted by the user and its results double-checked, yet having the AI integrated as an essential part of the workflow encourages more advanced examination with an understanding of the context as well as an ease-of-use UX. Runway offers a convenient, integrated experience by seamlessly integrating with modeling workflows and CRMs, so users don’t have to leave the platform to access customized copilot solutions. For instance, VAT regulation and recovery are complex because of dissimilar rates and rules dependent on nation, goods and services. As a result, finance teams manually examine and draw out data, which doesn't have the capacity to grow and is susceptible to mistakes - resulting in lost refunds that cost companies a tremendous amount of money. By instilling VAT reclaim tools into financial flows, businesses can automate data analysis extraction, confirmation and fraud inspection with real-time feedback and analytics - increasing effectiveness, minimizing mistakes and optimizing recovery. Moreover, VAT automation has the potential of being a startup's first step into a venture, enabling it to move ahead into other monetary services. Successful solutions integrate with different components of an organization, facilitating "interaction" between isolated applications. Artificial Intelligence applications are being incorporated into tools like CRM, ERP and staff management systems. This helps people understand where and why money is being used. Identifying the right integration point is vital - the best starting spot is where the greatest difficulty lies and is essential to increasing usage rapidly. Startups IRL - Cobbler, Finally, and Pennylane - begin with accounting and AP/AR management or link into popular accounting and payroll programs, uniting financial planning into one unified solution. Teams have become more lean and dispersed, with different levels of tech know-how. To break down the resistance to adoption, user-oriented solutions with collective work as a major part can help. Moreover, given the current macroeconomic environment, up-to-the-minute KPI reports have become essential and many organizations have switched to more regular reports, pushing the need for highly tailored solutions. Mosaic and Basis offer dashboards that can be manipulated with a drag-and-drop system, allowing users to design their own key operational metrics and reports to suit their business' needs. It's a convenient, time-saving solution, allowing users to quickly implement without needing to learn a new user interface. Over the last few years, there has been a great influx of horizontal tools, making the market highly competitive. Despite this, there are still certain niche markets which are not properly catered to. The biggest advantage of utilizing AI solutions tailored to these specific domains, using language models, is that they can be employed for a variety of unique applications in ways that horizontal software cannot. This presents users with more refined output that takes into consideration the special needs of the financial services domain, and eliminates the need to connect multiple applications. In-person startups such as Parcha (artificial intelligence agents pertaining to finances), Hadrius (AI-supported SEC regulations for fiscal services), and Basis(AI helpers for bookkeepers) can be singled out as good cases in point. On a platform's viewpoint, having a direct access to or owning special data is essential to putting up a fortification, and the gap can only increase as the models acquire a more profound cognition of consumers. The CFO stack has evolved significantly thus far, propelling CFOs into a critical function in achieving their company's objectives. Nonetheless, difficulties continue to endure, from data connections and up-to-the-minute understanding to predicting accuracy. By applying genAI, CFOs can resolve problems and step up their strategic assistance, piloting corporations towards a brighter future. We’re looking forward to the breakthroughs that the next generation of CFO tools can bring to the table. Our focus rests on creating with flexibility, collaboration and interoperability to facilitate growth of dynamic finance teams with genAI-enabled integrations. A “one-stop solution” might be appealing, yet we think the optimum plan is to initially tackle the most cumbersome pain point for product adoption, and then branch out to other components. Constructing on the premises? We'd love to hear from you! This content was authored by Andrea You and then edited by Jaclyn Hartnett of Cathay Innovation. For additional perspective on the arenas of AI, fintech, and startups, take a look at our prior postings.

Source: https://medium.com/cathay-innovation/gaps-in-the-modern-cfo-stack-the-generative-ai-opportunity-1ccd6c3428a6?source=rss------fintech-5