Sage Intacct

July 13, 2023

What Every Finance Professional Needs to Know About Generative AI in Finance

AI in finance

As generative AI invades the planet, finance teams are asking, “So what?”

The term “generative AI” is popping up everywhere, just like those pesky targeted ads that follow you across your devices or that puppy video you can’t stop watching. You’ve heard the hype — that AI will take your job and ultimately lead to the downfall of society. You’ve also heard the buzz — that generative AI will automate our most mundane tasks, freeing us to do all those things that we never knew we needed to be doing. In the face of plenty of confusion and uncertainty about what generative AI really means, many of the finance professionals we speak with are asking, “So what?”

We love taking on the “so what” questions at BT Partners. So, let’s take a mostly serious look at what every finance professional should know about generative AI.

War of the words — what is generative AI?

Remember when AI was this futuristic concept that seemed straight out of a sci-fi movie? Well, that future is here. Distilled to earthly proportions, AI is all about creating computer systems that can perform tasks that usually require human intelligence — think language comprehension, pattern recognition, learning from experience, and decision-making.

Within the grand AI universe, there’s a subset called Machine Learning (ML). ML is like AI’s ambitious younger sibling, allowing systems to learn from data without being explicitly programmed. It’s like feeding your computer a steady diet of information and watching it grow smarter day by day. Deep within this ML realm, we find another subset, Deep Learning. It’s not named ‘deep’ for its philosophical insight but rather for its structure — multi-layered artificial neural networks that imitate the human brain. We’re getting a bit too far out into space though, so let’s reel it back in to focus on the star of our show, generative AI.  

Imagine you’re in your high school art class. There are two types of students. Some meticulously copy the details of a still life in front of them — these are your discriminative models in AI. They classify and differentiate data really well but aren’t overly creative. Then there are students who, after studying numerous still lives, start creating their own. These imaginative souls represent generative models, the key element of generative AI.

Generative AI doesn’t just understand and replicate information — it produces new content after learning from existing data. It’s like feeding your computer a diet of romance novels and then watching it write its own heartfelt sonnets. Or giving it thousands of images of dogs and seeing it generate pictures of breeds that don’t even exist. All these creations are not random guesses but are based on the patterns and structures the system has learned. Pretty smart, right?

Generative AI’s creativity isn’t limited to literature or dog breeds. It is now being used in a diverse range of applications. In the world of music, for example, it’s composing original melodies. In medicine, it’s helping generate 3D models of organs for better diagnostics. In the automotive industry it’s creating scenarios for autonomous vehicle testing. The list goes on.

What does it mean for me?

When we’re bombarded with stories about the earth-shattering potential of AI, it’s easy to wonder if it’s a technology that really matters to the everyday tasks and functions of your organization’s finance department. Here is where you may be shrugging your shoulders and asking, “So what?” Let’s start to answer that question.

Imagine if you could accurately forecast trends or swiftly identify and mitigate risks by leveraging AI in finance departments. These tasks are squarely in generative AI’s orbit. AI digests all your organization’s financial data and handles it with precision, learning from historical financial data and then predicting future patterns.

Generative AI in finance can be used to model scenarios and stress tests, an invaluable tool for strategizing for potential economic downturns or market changes. Its ability to learn from vast data sets and generate possible future scenarios supports a deeper understanding of how various factors might impact your business. It can offer insights that your human analysts might miss due to the sheer scale and complexity of the data involved.

An efficient application of generative AI in finance departments is to automate manual workflows. With its myriad documents, complex approvals, and many stakeholders, Accounts Payable processing is a prime candidate for AI’s talents.

Another fascinating potential is in the realm of fraud detection. Traditional methods can flag unusual transactions, but generative AI can go further by continually learning and identifying patterns in data sets. In doing so, it can identify anomalies, errors, and potentially fraudulent behavior with much higher accuracy, helping to keep your organization and its customers safer.

Can we trust it?

While it’s pretty exciting, it’s also important to mention that generative AI isn’t perfect. Sometimes its creativity gets a bit off track, and sometimes it gets things downright wrong. Newspapers have had to recant articles they’ve published because their journalist used AI in the research that was completely made up. However, as the technology improves and the learning data becomes more refined, the results will become increasingly accurate and usable.

So for now, think of AI as that smart student who sat in front of you in Calculus class — but don’t copy all her answers — do a few calculations of your own.

One more caution. We mention AI’s incursion into the fields of music and art and would be remiss not to note that this is causing real issues surrounding plagiarism and intellectual property rights. So, for now, forget asking generative AI to write you a song about debits — unless you can give the original artists the proper credit.

From “so what” to “what’s next”

The potential of generative AI for businesses, especially AI in finance departments, is vast. It’s like having a super-intelligent, never-tiring team member who thrives on number-crunching and pattern-finding. As generative AI technology advances, its power to transform the financial world will only grow. So, rather than asking, “So what?” perhaps the question should be, “What’s next?” Stay tuned for part two of this series, where we’ll highlight the five reasons finance professionals cannot ignore AI — and offer suggestions about how to deploy it. Spoiler alert, it starts with a financial management solution, like Sage Intacct, that builds AI into its thinking.

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