AI Helps Accenture Realize Dramatic Difference In Quarterly Reporting

The professional services sector encompasses a wide range of companies and different types of businesses, all with varying needs when it comes to digitalizing products, processes, and strategies.

Despite these differences, digital transformation in professional services is essential. Statista predicts that global spending on digital transformation overall will reach $3.4 trillion by 2026, cementing its significance as a business investment for companies of any size in any industry.

Thanks to the surge in emerging technologies such as RPA (Robotic Process Automation), chatbots, and artificial intelligence, the professional services sector is experiencing unprecedented change, making it particularly ripe for further technical development.

For companies such as Accenture, whose business is to provide tools and strategies to help its customers digitalize, that transformation begins at home.

Moving at the speed of business

“Many companies find it challenging to adjust their business model amidst industry upheaval,” said Michalene Schechter, Director, Finance Product Strategy, SAP Platform Architect at Accenture Global IT. She was speaking on the “Professional Services Companies as Digital Enterprises: Is your company ready?” Webcast.

“The goal of transformation is to ensure that the strategic business model of an enterprise works with its operating model,” said Schechter. “Our job is to help organizations move at the speed of business. The cloud gives us the flexibility and agility to respond to their needs in real time.”

Improving workplace efficiency and increasing transparency are among the top challenges facing professional services companies. Cash application, the process of matching incoming payments to outstanding invoices and to the proper account where they can be entered, is one area that exemplifies that need.

Incoming cash can’t be utilized until it has been properly assigned. The sooner a business can utilize its cash, the sooner it can pay salaries and bills, fill purchase orders, invest in other opportunities, and pay dividends to investors. Cash application has become highly relevant in the digital age because customers now have many ways to pay for purchases, presenting new challenges for organizations.

Serving more than 7,000 customers in 120 countries, Accenture issues more than half a million client-facing invoices each year from 200 locations globally. Cash application is part of the accounts receivable process. While seemingly straightforward, the process for a large, global, and diverse organization such as Accenture is complex and performed at huge scale.

Improving the process with AI

To address the issue, Accenture introduced SAP Cash Application software, creating a leap in capability through a machine learning–enabled matching model.

Before digitalizing the process, cash application at Accenture required 250,000 manual entries using rules-based, high-maintenance confutations. There were issues with discounts, withholding taxes, and payment amounts not matching invoice amounts. There were even cases where the collection team was calling clients that had already paid, but the invoice had not yet been cleared.

These issues have been eliminated with SAP Cash Application, which automates clearing processes and provides machine learning–generated proposals to reduce manual processing. The software passes new incoming payment and open invoice information from SAP S/4HANA to a machine learning–enabled matching model on SAP Business Technology Platform (SAP BTP).

As a result, the Accenture team achieved greater accuracy and faster application of payments that in turn reduces open accounts receivable balance.

“Historically, we have struggled globally with low automatic rates and needed to find a better way,” said Schechter. “Since using the tool’s deep machine learning model, which proposes a match, we’ve almost doubled the hit rate from 30 to 54 percent and increased cash processing by 80 percent.”

Schechter was also pleased to report that the use of AI has dramatically improved the pre-close reporting process. Previously, this was mostly a manual activity performed by individual country controllers. The process involved downloading a report, analyzing it on a spreadsheet, sending e-mails around to collect edits, and then uploading a final report.

Now, the team has developed a single, global dashboard running the SAP Analytics Cloud solution on SAP BTP, that all controllers use together to comment and sign off on their reports.

“We’ve been able to augment the pre-close process with generative AI,” she said. “It now generates 90 percent of the commentary and automatically sends Microsoft Teams notifications to explain key financial variances that require immediate attention. The tool provides our financial leadership with early alerts customized to their role, so they can make relevant decisions at a time period when every minute is critical.”

By digitalizing cash application tasks, the team saves time and can redirect resources to more value-added activities. These achievements are helping Accenture become the next best version of itself. Successfully managing its own challenges with the help of technology and human ingenuity helps Accenture address the needs of its own customers with greater expertise and credibility.

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