AI revolutionizes financial statement analysis

Financial statement analysis has traditionally been a labor-intensive task for credit managers, involving extensive manual review of documents to assess creditworthiness. However, artificial intelligence (AI) can transform this process by automating data analysis, improving accuracy and delivering real-time insights.

Why it matters: AI streamlines financial statement analysis, freeing time for credit investigations and enhancing relationships with staff and customers. It reduces risk and empowers credit managers to make faster, more informed decisions.

Yes, but: Even with AI’s impressive ability to analyze financial statements, it lacks the nuanced understanding of industry context, relationship dynamics and strategic decision-making that credit professionals bring to the table. Credit professionals bring a forward-looking view to every transaction and customer relationship.

With AI technologies such as machine learning, natural language processing and robotic process automation, organizations can streamline their financial reporting processes, providing real-time insights and significantly reduce the likelihood of errors.

As an organization grows, AI systems can handle larger volumes of data. For smaller credit requests, AI can analyze all of the information available and recommend an action. “While several credit reporting agencies build score cards, those scorecards are often limited to that agency’s database or the information you feed them,” said Christopher Finley, CICP, manager of global credit at Club Car LLC (Evans, GA). “AI can search the web for negative publicity, public records and legal names that are filed with local governments.”

For larger credit requests, AI can analyze at financials and provide high-level summaries of trends or key metrics that you feel are important. “This information would be taken into consideration when approving credit but would not be the ultimate decision maker for the business,” Finley said. “Instead, it would be a recommendation to help speed the process up. This would also be used as a starting point for annual reviews.”

What AI can do

#1 Time saver

AI streamlines financial statement analysis by handling repetitive tasks, allowing your credit team to focus on strategic initiatives. AI tools can perform complicated calculations and analyses in moments, saving hours of manual work. For example, Scry AI can generate a one-page credit report that highlights the strengths and weaknesses of the financial situation of a company.

#2 Improve customer experience

By reducing time spent on financial statement analysis, AI allows you to focus on strengthening relationships and enhancing service experiences. “AI will provide the foundational data needed to make quicker decisions, which will help support the sales team while allowing time to focus on building customer relationships,” said Finley.

#3 Improved accuracy

AI improves accuracy and reduces potential human error when analyzing financial statements. “Spreadsheets can have numerous mistakes because a person is crunching hundreds of numbers but with AI, it’s much harder to make those mistakes,” said George Schnupp, CCE, instructor for NACM’s Financial Statement Analysis 2: Credit & Risk Assessment course.

AI can also detect unusual patterns in financial data, helping to identify and prevent fraudulent activities. Automated compliance checks in AI software ensure adherence to regulatory standards, minimizing the risk of fines and legal issues. “My goal when automating our process is maintaining stricter fraud prevention and risk mitigation practices while improving the customer experience,” Finley said.

#4 Real-time data

AI software can continuously analyze incoming data by identifying trends, detecting anomalies and providing insights much faster than traditional methods. For example, Scry AI can generate a report in real-time based on industry trends or macroeconomics that could impact business operations of specific customers. “It can analyze various factors or events and inform you on how they can impact the overall ratio of probability of default,” said Myla Ramos, CICP, director of global credit at Hitachi Vantara LLC (Santa Clara, CA).

#5 Predictive analytics

AI can predict future payment behavior and the financial state of your customers, which helps credit managers make risk-adverse, informed decisions. “Scry AI takes into account any adverse conditions or situations that would deteriorate the financial results and impact the overall operations of a business,” Ramos said. “It can provide some estimates for one or two years ahead based on trends and outcomes of prior years.”

Credit managers must still know how to analyze financial statements manually, ensuring they can interpret complicated data, challenge AI-generated insights and make informed decisions when faced with unforeseen circumstances.

“Our credit analyst reviews the customer’s payment behavior as well as their overall Days Payable Outstanding (DPO) based on Scry AI reports,” Ramos said, “This helps us understand the potential impact on future cash flow and allows us to make more informed predictions.”

The bottom line: AI’s integration into financial statement analysis is transforming credit management. But even with AI’s impressive ability to analyze financial statements, the human touch of a credit manager will always be valuable.

NACM’s November in-person Credit & Risk Assessment course is a great way to perfect your analysis skills and work towards NACM’s CCRA designation!