Exploring artificial intelligence in finance

February 15, 2024

A blog post by Beth Kaplan, Katie Glynn, Court Watson, Oz Karan, and Madeline Mitchell

Artificial intelligence (AI) and machine learning technologies are rapidly transforming today’s controllership business models. However, just as the first generation of AI capabilities became widespread across businesses, a new era for AI is fast approaching. This next phase of emerging AI technologies has the potential to offer finance and accounting organizations—and finance leaders who may have a critical role in the pace of change—many opportunities and new technological capabilities to reach greater heights. But what makes this new frontier in AI different? How can it work for finance and controllership? 

By now, most of us have a general idea of what AI means. It is a large umbrella encompassing many technologies, some of which are already widespread in society and businesses and used daily. When we talk to digital assistants, use autocomplete, incorporate process automation tools, or use predictive analytics, we are using AI. These tools and other rules-based innovations are pervasive, but AI is entering a new era. AI is having a moment, and the hype around AI innovation over the past year has reached new levels for good reason. What changed? In short, AI is graduating. It is transforming from rules-based models to foundational data-driven and language models. With a foundation model focused on predictions and patterns, the new AI can empower humans with advanced technological capabilities that will transform how business is done. These tools include everything from intelligent automation to machine learning, natural language processing, and Generative AI, and they present new opportunities, possible benefits, and many emerging risks for finance and accounting.

Before we explore some of those potential opportunities and benefits for AI in finance and controllership, it is crucial to understand what this new model of AI is built from, what it looks like, and how that translates into tools and technologies we can already use and the innovations that have yet to emerge. To do that, let’s put the spotlight on Generative AI.

What is Generative AI?

Innovations in machine learning and the cloud, coupled with the viral popularity of publicly released applications, have propelled Generative AI into the zeitgeist. Generative AI is part of the new class of AI technologies that are underpinned by what is called a foundation model or large language model. These large language models are pre-trained on vast amounts of data and computation to perform what is called a prediction task. These predictions can then predict or generate a broad range of new tasks. For Generative AI, this translates to tools that create original content modalities (e.g., text, images, audio, code, voice, video) that would have previously taken human skill and expertise to create. Popular applications like OpenAI’s ChatGPT, Google Bard, and Microsoft’s Bing AI are prime examples of this foundational model, and these AI tools are at the center of the new phase of AI.  

If you look at just a few of the Generative AI applications this model renders, it also becomes apparent why it has captivated the attention of both society and the business world across the spectrum of industries.

Examples of Generative AI applications

• Text: Generate text that can summarize existing articles or write new original content; conduct legal and scientific research; draft company reports; and assist coders in numerous programming languages.
• Speech and audio: Produce high-quality speech that can be used for realistic narration and dubbing on videos and presentations; power a digital customer service agent with natural language processing and human-like speech.
• Images and video: Generate abstract or hyper-realistic images and videos given text inputs from users, which can be used as presentation templates and materials, graphics, and marketing content.
• 3D: Generate 3D objects given text prompts and 2D inputs that can be used in building virtual omniverse environments and characters, or AI-assisted design and manufacturing.

Opportunities for AI in finance and accounting

When looking at the emerging AI tools and their various generative applications, the opportunities they present to finance and accounting are tremendous.

AI can act as an operations force multiplier:

• Summarize and simplify using AI to generate a concise and coherent summary of a long text or a collection of texts such as meeting minutes, news summaries, and reports.
• Answer questions or address customer needs by using AI to generate a natural language answer to a natural language question based on a given text or a knowledge base utilizing a chatbot or other tools.
• Transform and generate content by converting it into a new specified type, format, or style, such as text to code, style transfers, and personalization.
• Generate logical analysis and reasoning, such as inference, deduction, or explanations of relations given a context or knowledge base to produce impact analysis and reports.

Using AI technologies can guide decisions and focus on critical tasks:

• Produce trends reports, proposals, RFPs, and data with AI by generating content based on a set of input examples, documents, data, or a specific topic. 
• Make classifications or analyses with AI by generating a category or label for a given input.
• Create training manuals, vision models, brand libraries, and graphics using AI to generate images from text prompts.
• Extract specific information for forms or key data from reports by generating information or entities from a given input.
• Reduce the burden of human interaction for many tasks by generating novel content from existing content.

How finance leaders across functions can use Generative AI

Generative AI’s broad applicability makes it useful across the personas and functions within finance and accounting and throughout the business. Here are just a few examples of how different functions can use Generative AI to help enhance their operations:

• Controllership can systematize recurring entries and reconciliations, perform source-to-target chart of account mapping, review and analyze contract terms, and prepare internal and external financial reporting that includes commentary and insights.
• Strategic finance can assess corporate development deals, run due diligence, identify opportunities for capital optimization, and perform risk assessments and advanced scenario modeling.
• Internal audit can proactively detect and prevent fraudulent activities, analyze data and generate audit reports, and determine compliance with regulations and internal policies.
• Financial planning and analysis can predict income statements, balance sheet, and cash flow; automate the creation of data visuals and presentations; provide quick reporting and commentary; and perform quality checks.

For the finance and controllership workforce, finance leaders and accounting professionals can also use Generative AI tools targeted specifically for their role in the function or professional motivations:

• Finance leaders can use Generative AI to maintain a pulse on the business and adapt to market conditions, predict and preempt strategic macroeconomic blockers, enhance organizational structure, and provide quick answers to evolving questions and real-time information.
• Directors and managers that need to focus time on strategic process improvements; improve budget efficiencies; provide key, timely insights to enable business decisions; synthesize information to understand problems; and streamline processes can use Generative AI to conduct trend analysis, proactively manage organizational spending, generate insights from emails and reports, and perform tasks that can help drive management efficiencies.
• Experts can use Generative AI to run intelligent searches of knowledge bases, standard op procedures, and regulatory documents; generate control compliance reports to provide domain-specific expertise to business decisions; and monitor compliance, ethics, and control across the business.
• Finance and accounting analysts can use Generative AI tools like virtual assistants and intelligent bots to deliver vital operational tasks faster and more efficiently and respond to ad hoc reporting requests. AI applications such as virtual finance analysts can also help analysts drive operational excellence and value-added strategic tasks.
  

With such a vast array of applications and customizable capabilities, Generative AI can serve as a powerful tool for finance leaders to address key agenda items and realize strategic priorities and objectives for finance and controllership. 

In the second part of our series on AI in finance, we will dive deeper into the potential benefits of Generative AI in finance, the current risks associated with Generative AI, and how to manage risks with a framework that can enable a successful AI program. In the meantime, listen to our Dbriefs webcast to further explore the new frontier of AI opportunities for finance and controllership: A new frontier: Exploring artificial intelligence in finance