Concrete AI Use Case that Generates Significant ROI for the Financial Close

⇨ The financial close process is undergoing significant transformation due to automation and AI, driven by a shortage of accounting graduates and a demand for improved employee satisfaction and efficiency.

⇨ Trintech's innovative approach includes the development of a proprietary Large Language Model that streamlines the journal entry process, saving clients substantial time and resources by reducing manual tasks.

⇨ Organizations are encouraged to identify and leverage small, incremental use cases for AI and automation in mundane processes to achieve significant operational improvements, while also promoting their AI strategies to attract younger talent.

The financial close has been around since businesses were created. Over the past several decades, there have been limited innovations. But now that is rapidly changing with the advent of advanced automation and Artificial Intelligence. SAPinsider recently sat down with Christopher Witt, the director of Product Marketing at Trintech, to discuss the latest evolution of the company’s AI strategy and how it is reaping specific and tangible rewards for some of its biggest clients.

The Issue at Hand

According to Witt, the financial close and those who work on it are at a crossroads. “There is a sea change happening in industry. There are fewer and fewer core accounting graduates, fewer people taking the CPA, and greater attrition amongst current workers. Managers are struggling to hire. If you dig into the issue you have these old school accountants who are proud of working their 16-hour days during the financial close, which they should be. But that reality does not fly with the newer graduates coming out of school. They are demanding automation because they do not want to be stuck doing menial tasks for most of the day,” reports Witt.

Employee satisfaction is only a piece of the benefit. Auditability, efficiency, and accuracy are additional reasons for making the move toward greater automation and intelligence. “No one wants to manually match transactions anymore,” said Witt.

How is Trintech Looking to Solve the Challenge

According to Witt, Trintech developed true expertise with various levels of automation throughout the years, including Robotic Process Automation (RPA), Machine Learning, and Artificial Intelligence. It spun together a center of excellence as well as an innovation lab. The company’s most recent breakthrough involved its own proprietary Large Language Module that incorporates the data that the company collected throughout its 30-year existence in the industry.

Trintech is beta testing a unique use case with one of its largest clients. This use case focused on the pain point of creating and adjusting journal entries. Currently, this customer deals with close to 10,000 journal entries per month in one division alone. It gets scores of emails asking for adjustments. Creating these new general entries requires on average 8-10 minutes per entry.

By applying the intelligence and data within Trintech’s LLM, the users can copy the email request into its AI interface and the LLM will guide them through the change process offering template options and auto generating the new journal entry. The new entry can be easily validated through the SAP certified connector and can go through requisite approvals if necessary.

In the end, it now takes less than a minute to process these adjusted entries, saving the customer close to 30 working weeks per year. This is a significant resource saving not to mention limits on tedious manual matching and work.

“Other partners are spouting buzz words. We are actually building use cases that matter,” asserts Witt.

This is just the beginning and Witt stressed that organizations should not search for the big bang, big buzz use case. He and his team have had the most success looking for those seemingly small incremental value use cases where companies can make a difference in cutting minutes of a mundane, tedious task.

What this means for SAPinsiders

Get your key close partners to divulge their AI strategy and use cases: Partners such as Trintech are not alone in their exploration of AI and Machine Learning. It is collaborating with their biggest clients on revealing their progress and results. You need to thoroughly understand these stories and strategies so that you can apply them within your own organization. The options are out there. If your current partner is not aggressive or advanced enough, explore its competitors.

What may be boring, may be the perfect use case: As with the lessons from this story, the gold may be buried in the most mundane places. Examine where you are spending unnecessary time and manual intervention. These are places to explore the application of automation and AI, and you may reap some exciting rewards that you never thought possible.

Publicize your AI and Automation Strategy: Younger employees are looking for cutting-edge companies to work for. They want to know that you are aggressively exploring automation and AI to improve your current processes and free your employees from mundane tasks.