Generative AI explained: Why GenAI is the (friendly!) future of financial performance analysis (2024)

In this article, we’ll explore GenAI, what it is, how it works, and ways finance teams can apply it to improve CPM processes.

Today’s finance teams are well acquainted with the struggle of managing large data volumes. To say we are dealing with big data would be an understatement; enormous data would be a more accurate description.

As we struggle to make business sense of data across our enterprises, we’re confronted with an ever-increasing number of reporting requirements—ESG, BEPS Pillar Two, lease accounting—that require the highest degree of corporate performance data mastery.

How can we confidently comply with new and emerging disclosures when we still struggle to foster efficiency in processes as longstanding as the annual report?

One answer comes via AI. And not just any AI. Generative AI (GenAI.)

In this article, we’ll explore GenAI, what it is, how it works, and ways finance teams can apply it to improve CPM processes. Let’s dive in.

What is generative AI?

To answer this question, we went straight to the most well-known form of generative AI: Chat GTP. First, we asked Chat GTP for a concise explanation of generative AI. Here’s what it said:

“Generative AI creates new content mimicking human creations by learning patterns from existing data. It's used in text, image, music, and video generation, with examples like GPT for text and GANs for images.”

(Not bad, Chat GTP.)

From this definition, you can see how finance, as a data-driven department that relies on text and visualization, could benefit from GenAI. GenAI is a handy tool for finance teams that must analyze performance data, manage performance data, and produce visualizations from that performance data, as GenAI can augment all three job functions.

How does generative AI work?

When you feed GenAI models historical data, the AI learns to recognize data patterns. It then uses those patterns to generate similar new data.

For example, to train a GenAI model on a language, you feed it websites, books, and text until it learns the statistical likelihood of one word following the next. The process to generate images is similar. The AI ingests pictures, photos, and graphics. Eventually, it learns to reproduce visual patterns.

Three ways finance can apply generative AI to CPM processes

Since financial processes are marked by repetitive processes, data exploration, and the analysis of large datasets — the three things GenAI does best — CPM solutions that use GenAI can profoundly impact the daily lives of finance professionals. Here are three ways GenAI can assist finance teams.

AI helps finance embrace a data deluge & connect the dots

The world's data is anticipated to reach 175 zettabytes, or 175 billion terabytes, by 2025. And there’s no end in sight.

GenAI thrives on large volumes of data. It gets to the root of data to identify patterns and hidden correlations that would not be evident to the human eye (especially not after late nights crunching numbers.)

GenAI doesn’t replace your critical thinking, but it can identify missing pieces that round out your thinking and make connections you might have missed. It can identify subtle patterns, correlations, and hidden factors influencing performance. Its ability to analyze everything leads to more informed and impactful decisions, helping you to move from the “what happened” to “why did that happen?” and “what will happen next?”

AI is a helpful assistant

According to the findings of the AI in Audit Survey released by KPMG, finance executives that use AI are already experiencing the following benefits:

  • 51% increased efficiency and a reduced burden on employees using AI.
  • 50% experienced greater data accuracy, reliability, and predictability using AI.
  • 50% increased visibility into end-to-end processes and controls using AI.

While GenAI can support finance tasks, it’s important to understand that it is more of a research assistant and less of a fortune teller. GenAI can provide insights based on historical data and trends, but the final decision-making should be on you, the human.

When managing GenAI, it’s vital that finance teams can set parameters, choose the datasets AI will be trained on, and submit their own queries. While GenAI takes care of the labor of data-smithing, humans still need to vet and verify the GenAI’s work. It is efficient and intelligent, but it is not infallible.

Tl;dr: Look at GenAI as an assistant that augments part of your intuition, refines your analysis, and boosts the accuracy of your decision-making.

AI boosts productivity and analysis

Research by CFO.com found that the average FP&A employee spends 75% of their time gathering data and administering the process, leaving just 25% to provide value-added analysis to the business. GenAI has the power to flip this statistic.

GenAI specializes in making repetitive processes like data exploration and analysis almost instantaneous. Finance teams can reclaim their time on data exploration, driver-based analysis, creating charts, and crafting commentary for reports and instead focus on driving the business. Essentially, GenAI augments your decision making by providing intelligent insight into emerging trends.

Generative AI explained: Why GenAI is the (friendly!) future of financial performance analysis (2024)

FAQs

Generative AI explained: Why GenAI is the (friendly!) future of financial performance analysis? ›

GenAI doesn't replace your critical thinking, but it can identify missing pieces that round out your thinking and make connections you might have missed. It can identify subtle patterns, correlations, and hidden factors influencing performance.

Why is generative AI the future? ›

The future of generative AI seems promising precisely in connection with the unification of the efforts of neural networks in math models and human heads. This unification has the potential to lead to significant economic benefits. Generative AI guide.

What is Gen AI in finance? ›

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.

Which of the following is an example of a generative AI application in finance? ›

A notable example of generative AI application in finance already used by several banks is automation in financial document monitoring. Moreover, financial institutions are going to build powerful and unique access-based digital profiles of customers, the data will be safer and more secure.

What is generative AI the future of content creation? ›

The future of content creation is being fundamentally redefined by generative AI. Its applications across various industries—from entertainment and education to healthcare and marketing—demonstrate its potential to enhance creativity, efficiency, and personalization.

What is the next big thing after GenAI? ›

if there is a need for deeper contextual understanding or task automation then consider an AI agent. AI agents are designed to understand and act within a specific context. They maintain state, manage multi-point conversations and execute complex tasks.

How will GenAI impact the future of work? ›

Generative AI may automate those tasksaltogether, freeing up a worker's ability to focus on new tasks, or they make those tasks easier for people and create time for the individuals. Some tasks humans do better. Some tasks machines do better. Some tasks are better done with a combination of the two.

Why AI is the future of finance? ›

In investments and trading, AI may become advanced enough to make very accurate market predictions and also execute sophisticated trading strategies. This could allow the firms to optimize investments and also returns. However, appropriate governance will be very necessary as AI takes on more financial decision-making.

How can generative AI help finance and accounting professionals? ›

Financial management is undeniably time-consuming and prone to human error. This reality can limit accountants' ability to concentrate on higher-level analysis. Generative AI offers a solution by automating routine tasks, empowering specialists to shift their focus toward strategic advising.

How does AI benefit finance? ›

How is AI used in finance? AI in finance can help in five general areas: personalize services and products, create opportunities, manage risk and fraud, enable transparency and compliance, and automate operations and reduce costs.

What is the main goal of generative AI? ›

The main goal of Generative AI is to create new data or content that is similar to the input data it has been trained on.

Which banks are using generative AI? ›

In the three months of fall 2023, Morgan Stanley, JPMorgan Chase, Citigroup, and Goldman Sachs all announced their custom internal generative AI tools.

What are the generative AI benefits for business? ›

Generative AI enables businesses to analyze vast amounts of customer data and generate personalized recommendations, product suggestions, and marketing messages. By leveraging AI algorithms, businesses can enhance customer engagement and satisfaction, ultimately driving sales and loyalty.

What is the future of generative AI? ›

AI Delegation And Making Work Better

But more jobs will be augmented – enhanced – by generative AI. Because generative AI allows us to hand over the more mundane and repetitive tasks to machines, human workers will have more time for value-adding tasks like problem-solving, creativity, and relationship-building.

How will generative AI impact our lives? ›

The article sheds light on these innovations and their implications for everyday life. 📝 Content Creation: Generative AI can assist in creating high-quality and original content in various domains. It can generate realistic images, generate personalized recommendations, compose music, or write articles and stories.

Why is generative AI good? ›

By automating tasks that previously required human intervention, generative AI saves valuable time and reduces operational costs. For instance, in architecture and design, AI algorithms can generate building designs based on given specifications, significantly speeding up the design process.

Why artificial intelligence is the future? ›

The productivity of artificial intelligence may boost our workplaces, which will benefit people by enabling them to do more work. As the future of AI replaces tedious or dangerous tasks, the human workforce is liberated to focus on tasks for which they are more equipped, such as those requiring creativity and empathy.

Why has generative AI taken off so quickly? ›

Why has generative AI taken off so quickly? Productivity boosts that nearly double previous increases are driving genAI's rapid growth. Functioning as a co-pilot for hyper-automation and hyper-creation, the technology allows people to save time on a variety of tasks.

Why is generative AI emerging on a massive scale? ›

Generative AI is emerging on a massive scale due to rapid development, significant attention, and market growth projections from 1.5 billion to 6.5 billion dollars by 2026, reflecting a 34.9% compound annual growth rate.

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