Generative AI in Finance (2024)

Perspectives

Part I: Opportunities for finance and controllership in the new Generative AI frontier

Artificial intelligence (AI) technologies are rapidly transforming today’s business models, and the emerging Generative AI and advanced applications are presenting new opportunities and possibilities for AI in finance and accounting. From Generative AI to machine learning and other foundation model solutions, we look at the new era of AI innovations, the tools they may offer accounting and finance, and considerations for incorporating an AI framework for success.

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?

ARTIFICIAL INTELLIGENCE (AI) is the theory and development of computer systems able to perform tasks normally requiring human intelligence.

-- Oxford Dictionary

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

Get in touch

Generative AI in Finance (1)

Beth F. Kaplan

Managing Director | Deloitte &Touche LLP

bkaplan@deloitte.com

+1 619 237 6848

Beth is the managing director for the Center for ControllershipTM. A Deloitte Risk & Financial Advisory managing director at Deloitte & Touche LLP, she has more than 35 years of experience both as an ... More

Generative AI in Finance (2)

Katie Glynn

Partner | Risk & Financial Advisory

kaglynn@deloitte.com

+1 949 337 8579

Katie is partner with Deloitte & Touche LLP. She specializes in helping clients address complex record to report challenges to reduce risk and enhance management oversight through business process re-... More

Generative AI in Finance (3)

Court Watson

Partner, Risk & Financial Advisory, Controllership

cowatson@deloitte.com

+1 206 716 7082

Court is a partner in Deloitte Risk and Financial Advisory’s Digital Controllership practice, with more than 14 years of public accounting experience and 18 years of experience working with the CFOs, ... More

Generative AI in Finance (4)

Oz Karan

R&FA Trustworthy AI Leader

okaran@deloitte.com

+1 310 986 5652

Oz is a partner within Deloitte & Touche, LLP's Risk and Financial Advisory (R&FA) practice and serves as R&FA's Trustworthy AI leader. He has more than 20 years of risk management, regulatory complia... More

Fullwidth SCC. Do not delete! This box/component contains JavaScript that is needed on this page. This message will not be visible when page is activated.

Generative AI in Finance (2024)

FAQs

Generative AI in Finance? ›

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.

How can generative AI be used in finance? ›

Generative AI can be used for fraud detection in finance by generating synthetic examples of fraudulent transactions or activities. These generated examples can help train and augment machine learning algorithms to recognize and differentiate between legitimate and fraudulent patterns in financial data.

What is a generative model in finance? ›

Generative artificial intelligence in finance enables sophisticated portfolio optimization and risk management by analyzing historical data, market trends, and risk factors. It helps financial institutions make data-driven decisions to maximize returns while minimizing risk exposure.

What is Gen AI in finance Mckinsey? ›

A review we conducted of gen AI use by 16 of the largest financial institutions in Europe and the United States showed that more than 50 percent of the businesses studied have adopted a more centrally led organization for gen AI, even when their usual setup for data and analytics is relatively decentralized.

How is AI used in the finance industry? ›

What is artificial intelligence (AI) in finance? Artificial intelligence (AI) in finance helps drive insights for data analytics, performance measurement, predictions and forecasting, real-time calculations, customer servicing, intelligent data retrieval, and more.

How are banks using generative AI? ›

Generative AI (gen AI) is revolutionizing the banking industry as financial institutions use the technology to supercharge customer-facing chatbots, prevent fraud, and speed up time-consuming tasks such as developing code, preparing drafts of pitch books, and summarizing regulatory reports.

What are the five generative AI use cases for the financial services industry? ›

Generative AI use cases in banking/financial services
  • Fraud detection and prevention. ...
  • Personalized customer experience. ...
  • Risk assessment and credit scoring. ...
  • Investment management. ...
  • Chatbots and virtual assistants. ...
  • Trading and investment strategies. ...
  • Compliance and regulatory reporting. ...
  • Cybersecurity and risk management.

How can AI be used to create a financial model? ›

AI enhances financial modeling by processing vast amounts of data rapidly, identifying complex patterns and correlations, and generating more accurate predictions for investment opportunities, risk assessment, and portfolio management.

What is the financial forecast for generative AI? ›

Generative AI in the financial services industry is forecast to grow at a CAGR of 28.1 percent between 2022 and 2032. Based on this compound annual growth rate (CAGR), the market size of generative AI is projected to exceed 9.4 billion U.S. dollars in 2032, up from around 0.85 billion U.S. dollars in 2022.

Which industry is likely to benefit the most from generative AI? ›

The healthcare industry stands to benefit greatly from generative AI. One of the key areas where generative AI can make a significant impact is in medical imaging.

How is JP Morgan using generative AI? ›

The application of Generative AI in Cash Flow Intelligence represents a paradigm shift in how corporate financial management is approached. By drastically reducing manual workloads by nearly 90%, JPMorgan demonstrates how AI can tackle complex, time-consuming tasks with unprecedented efficiency and accuracy.

What are the 3 C's of AI? ›

Any Intelligent system has three major components of intelligence, one is Comparison, two is Computation and three is Cognition. These three C's in the process of any intelligent action is a sequential process.

What is the future of gen AI in banking? ›

Generative artificial intelligence (Gen AI) could radically change financial services, potentially generating higher value by 2030 and enhancing productivity. Financial institutions are increasingly exploring Gen AI applications, seeing improvements in operational efficiency and customer service.

Will finance be replaced by AI? ›

Impact on the future of business finances

However, it is unlikely that AI will fully replace human accountants. Instead, AI will most likely be used to augment the work of accountants, allowing for more strategic decision-making and deeper insights.

What are the cons of AI in finance? ›

Drawbacks of AI in Accounting and Finance
  • Job Reskilling or Redeployment. As automation progresses, job displacement concerns arise. ...
  • Sensitive Data Exposure. There is always a risk of exposing sensitive information when using AI. ...
  • Complacency and Over-reliance. AI should not replace human judgment, but rather augment it.
Mar 14, 2024

How to use chat gpt for financial analysis? ›

To use ChatGPT to analyze financial data, you would typically first need to prepare your data in a suitable format, such as a CSV file, which can then be uploaded to the platform or environment where the ChatGPT model is being run.

How generative AI is applied to quantitative finance? ›

Their versatility and contextual understanding make them valuable across numerous applications, from content creation to customer service. Generative AI and LLMs are transforming quantitative finance by providing powerful tools for data analysis, predictive modeling, and automated decision-making.

How generative AI can be used in business? ›

Quicker delivery times on projects: Generative AI models can quickly generate responses, new content, useful data, and other value your organization may need at scale. This leads to more efficient production and allows your team to complete projects on tighter timelines, which is ultimately more cost-effective.

What is the application of generative AI in Fintech? ›

Practical use cases of generative AI in the financial sector include fraud detection and prevention, algorithmic trading, personalized financial advice, credit scoring and risk assessment, automated financial reporting, natural language generation for customer support, portfolio optimization, and asset allocation.

Which accounting firms are using generative AI? ›

How can accounting firms leverage AI? Here are a few ways accounting firms can leverage AI in their businesses: Client communications. Use generative AI to create a first draft of client emails or newsletters which you can then modify for accuracy and personal insight.

Top Articles
Latest Posts
Article information

Author: Rubie Ullrich

Last Updated:

Views: 6368

Rating: 4.1 / 5 (52 voted)

Reviews: 83% of readers found this page helpful

Author information

Name: Rubie Ullrich

Birthday: 1998-02-02

Address: 743 Stoltenberg Center, Genovevaville, NJ 59925-3119

Phone: +2202978377583

Job: Administration Engineer

Hobby: Surfing, Sailing, Listening to music, Web surfing, Kitesurfing, Geocaching, Backpacking

Introduction: My name is Rubie Ullrich, I am a enthusiastic, perfect, tender, vivacious, talented, famous, delightful person who loves writing and wants to share my knowledge and understanding with you.