Cash Application Automation in the Digital Era

Cash Application Automation in the Digital Era

4 Min Reads

Emagia Staff

Cash application automation can help businesses achieve 90% and above straight-through cash posting by matching payments to their corresponding invoices and accounts.

The new digital era is changing financial processes. Until now, those processes have been very labor-intensive while lacking visibility into data that would provide insight. That is changing, thanks to a combination of technologies including robotic process automation, analytics, and artificial intelligence.

In the order-to-cash (O2C) process, these technologies are transforming credit, the accounts receivable portfolio and collections, and cash application. To read about the transformation of credit and AR/Collections, go here and here.

Cash Application is another in a series of complex O2C processes. But the intelligent technology available today dramatically speeds the process, improves accuracy, and lowers cost. Manual administrative tasks are automated, freeing staff to manage more value-adding work. And the systems can scale to support growth, provide accurate forecasting and valuable insights.

Cash Application Challenges

Cash application provides numerous challenges, starting with multiple internal and external data sources, with much data in unstructured documents. Data-gathering is laborious and error-prone.

Enterprises may have several ERP systems, deal with numerous banks and payment types, and operate across multiple languages and currencies. In addition, inefficient and diverse business processes are managed uniquely by regional or local entities. As a consequence, the enterprise suffers from limited transparency into performance and transactional data.

They are highly reliant on manual and fragmented processes to support compliance and controls. Existing systems provide poor insight, and cash app teams have limited time for value-added finance activities.

Transformation of Cash Application Essentials

The first essential in cash application is gathering data. A system must bring together payment and remittance information from multiple sources in multiple formats, digitize and read it, then find and apply it to the correct AR invoice information, often across multiple ERPs.

Cash application teams must gather payment and remittance information from multiple external sources. Required data come from lockboxes, emails, PDFs, check stubs, customer portals, EDI 820 files, and even phone calls. It is a very inefficient process.

In a modern digital system, bots take over information gathering. Bots automatically access and pull information from a wide range of external sources. A typical cash application team may spend 60 to 70 percent of their time gathering all the information to process. But a digital O2C system automates the process, freeing up considerable staff time.

Document data-capture “assistants” scan and extract the data from documents such as emails or PDFs. For example, Emagia’s Giadocs is an advanced data capture program with learning capability based on AI deep learning neural networks. It can “read” formats from unstructured sources in multiple formats and bring all the data into a file to match open invoices. This capability saves a tremendous amount of time, as well as considerable savings in bank fees.

Matching and Posting

Rules in the system matching engine take over to match payments to accounts receivable, utilizing advanced digital technologies. Using AI, the system learns over time based on experience where to apply a payee’s checks or to which customer a particular kind of payment is applied. The system will give suggestions and learn from the human direction it receives. As a result, the matching process becomes much faster. And it is yielding an auto-match rate of 90 percent.

The 10 percent of unmatched payments route to a “workbench” where short pays, overpayments and unidentified payments can be sorted and addressed. The time savings provided by the system in gathering information and auto-matching means that cash application staff spend their time on the workbench, solving problems.

Not only have they got time to work short pays and uncover and address errors, but they can also conduct root-cause analysis, which allows the organization to eliminate recurring problems.

The system allows tolerances on deductions and disputes. For payments outside tolerance, the system identifies and assigns custom reason codes, then sends them through appropriate workflows for resolution. The system enables collaboration so the cash application team can interact with sales or the customer. Interactive collaboration is an essential element in resolving problems.

Analytics: Information Gain

Enterprises need reporting across all aspects of cash application—the ability to drill down to find payments received, remittances received, amounts matching up. For example, what is the automated match rate? How is cash posting? How much cash is unapplied?

With the data in one place, custom dashboards monitor throughput, backlogs and error rates. AI-enabled analytics forecast short-term cash flow. An enterprise can see an accurate rolling forecast of cash six or eight weeks out. It can look at best-possible cash flow if all customers pay on time or predict cash flow according to customers’ payment patterns. Accurate forecasting is of tremendous value to the treasurer’s management of working capital.

AI automation and analytics can take over 70 to 90 percent of manual operations in cash application. Visibility into data enables insight into issues, identifying shipping or product-line issues. The data in a company’s system is gold, but the company must have access to it. A comprehensive digital O2C system with intelligent analytics, reporting and visualizations, does that and powers the enterprise to new performance levels. It improves the cost efficiency, timeliness and accuracy of cash application.


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