Editor’s Note: Thank you for joining for part four of four in our “Beyond ChatGPT” blog series. If you’ve missed the previous installments in this series, click one of the following links to review this critically important content.
Global executives have reached a near unanimous consensus heralding the paradigm shift in the application of artificial intelligence (AI), altering not only where but also how it is harnessed.
Accenture’s 2023 Technology Vision report underscores a unanimous consensus among global executives, revealing that a staggering 97% of industry leaders concur on the transformative potential of technology models in facilitating connections across diverse data types.
In light of this transformation, businesses are compelled to embark on a journey of exploration into the full gamut of capabilities offered by generative AI. This exploration is integral to ensuring their success in navigating the complex landscape of the emerging global order.
As we look ahead, it’s imperative for financial leaders to note the immense growth projected in the global AI market. With forecasts from Statista.com in March 2023 predicting that the market size will approach the $2 trillion mark by 2030, it is increasingly clear that AI will play a significant and expanding role in the corporate world.
In response to these developments, companies across various industries are actively seeking innovative ways to harness GenAI-enabled tools. The applications of such tools extend far beyond the realms of technology, permeating areas like finance, including the critical domain of invoicing.
For CFOs, Treasure VPs, and senior credit professionals, this presents a unique opportunity to leverage the power of GenAI in addressing complex financial challenges, streamlining processes, and fostering a more innovative culture than that of competitors. As we venture into this new era, it is imperative that finance departments explore the transformative capabilities of generative AI to remain competitive and future-ready.
Generative AI in Billing
To review, Generative Artificial Intelligence (GenAI) refers to AI-enabled algorithms that can be used to create new content, including images, audio, code, text, 3D models, simulations, and videos. The technology enables generating new and unique outputs by using the knowledge acquired from learning patterns from existing data. Recent breakthroughs in the field, such as ChatGPT, Midjourney, and Emagia’s finance-focused GiaGPT have significantly advanced capabilities and the potential to drastically change the way we approach content creation.
In the finance domain, specifically in billing, GenAI can be used to address some of the pressing pain areas that have been long prevalent in billing and invoicing including:
- Detecting fraudulent invoices by analyzing patterns and identifying anomalies in invoice data.
- Extracting data from invoices.
- Checking and confirming customer information, payment details, invoices, and other relevant data before initiating a payment.
- Creating unique and good-looking invoices with AI-generated suggestions for text, images, and design elements.
GenAI in Finance
New technologies emerge almost constantly, but AI is already establishing itself as one of the most disruptive possibly since the widespread adoption of Internet use itself. Virtually any industry can find positive applications for AI and automation technology.
In a recent Gartner webinar poll of more than 2,500 executives, the results showed that 38% considered customer experience and retention to be the primary purpose of their investments in GenAI.
With e-invoicing becoming the norm, AI’s potential in accounts receivable and invoice factoring areas is only expected to grow, as it can be deployed to help ensure Accounts Receivable functions aren’t subject to too much risk or inefficiency. Helping avoid such issues proves helpful drastically reducing cash flow problems.
One way GenAI can help companies in their billing processes is by decoding various specifications, images, and other pieces of information from a customer order. AI solutions can also extract data from other communication channels like email or chats as well as data in the public domain, if desired. However, many users are increasingly wary about information security, which has given rise to more “closed-cloud” (private) GenAI solutions – like GiaGPT – that rely on the users manually (but quickly) uploading their own data. This cuts potentially erroneous public domain data and potential risk of information getting stolen out of the mix.
Fighting Fraud and Risk
Detecting fraud and risk is one of the most common uses of GenAI in the finance industry, with 58% of financial services enterprises adopting it here, according to Statistica.
Machine learning algorithms that can spot trends in large data sets that humans may miss are leveraged for identifying fraud and risk. If a client with a reasonably consistent payment history starts missing payments or making purchases much higher than their average purchase history, GenAI will try to investigate the same to identify the likelihood of fraud. If such analysis identifies deviations from the norm, it may lock the account, and flag it for employees to investigate further. Signals like this may slip by human workers until they become more glaring and apparent. Accounts receivable teams of businesses can use these insights to quickly and accurately qualify or disqualify potential customers.
E-invoicing has already helped automate accounts receivable management making it faster and more efficient than older, pen-and-paper approaches. That said, GenAI can take these benefits even further.
Reviewing documents to assess risk can be time-consuming for an employee, but GenAI can handle the task in minutes — if not seconds. Similarly, Gen AI can assist in billing clients, processing payments, recording transactions, and performing other data-entry tasks almost instantaneously. That efficiency and speed is unthinkable with the manual processes even at businesses with a properly level of well-trained staffers are in place.
But automation with the help of AI helps free human resources to focus on more value-adding work. GenAI can streamline and automate the entire billing process making it free from the human touch, thereby saving of time and cost while enhancing customer satisfaction.
Minimizing Human Error
Errors and mistakes are typically part and parcel with the invoicing process. That can result in invoicing delay, which ultimately delays collection. Manually checking for the errors and mistakes and correcting them is not rocket science, but it IS tedious and time-consuming. AI can do this with a consistent level of attention to detail and accuracy, virtually every time. As a result, billing teams can just about eliminate errors by automating with GenAI.
Fixing invoicing errors typically costs businesses an average of $53.50 per invoice. That can add up to thousands of dollars a year at a large enough enterprise. Consequently, by using GenAI to manage these processes instead, businesses can significantly improve their bottom line. Minimizing errors will also help build better relationships with customers.
Delivering accurate invoices quickly to customers is considered one of the top customer experiences. The increased adoption of GenAI by companies in their invoicing processes helps the financial sector and domain become far more accurate, secure, efficient, and smooth. No organization can neglect the benefits the technology is bringing to invoicing. Gen AI will soon become the industry standard for e-invoicing, changing the way the invoicing process is managed across businesses.