AI Is Here To Help In Every Cash Application Scenario
With the rising needs and challenges, it is important to move towards digitization and understand the intricacies of AI usage and how it would play a significant role in the coming years. Read along to understand the importance of AI and how it can help in streamlining the A/R processes.
The 3 Key Aspects of Cash Application
There are three main aspects of Cash Application, namely:-
Let us look at each of these processes up-close to understand how Cash Application works better with AI implementation.
Remittance Data Capture
Customers might share remittance data from multiple sources such as checks, emails, or customer portals. These might be in specific formats such as handwritten checks, Excel, PDF, Spreadsheets, or as attachments in an email body. What this translates to are the numerous working hours invested to surf through documents that could be easily automated using AI.
How does AI improve the process?
- It scans through the document for specific data such as invoice number
- It segregates pages with no remittance information
- It identifies the pattern of customer behavior and improves performance/ accuracy
Sometimes customers might send non-invoice reference number. Manually matching invoices to purchase orders and goods delivery receipts is complex and time-consuming. Especially when it requires matching invoices to purchase orders at the line level.
How does AI make a difference?
- AI creates multiple correlations to identify the invoices are corresponding to a payment
- It flags the work-list item for an analyst to decide, if unsure
- It incorporates the decision taken by future prediction/invoice matching
A/R teams of companies with a large customer base, sometimes find it challenging to deal with exceptions in the cash application process. Standard exceptions include truncated invoice numbers, incorrect invoice data, missing invoice data, and short-pays with a credit memo. Such repetitive exceptions are resolved by AI using pattern recognition and trend analysis.
How Is Exception Handling Done Using AI?
- AI uses identifies patterns in exceptions that are monitored by teams
- It maps exceptions to the identified patterns
- It resolves exception based on the pattern
Future Scope Of AI
With each passing day, newer formats of remittances, as well as their sources, might, with the traditional way of doing things, it is not possible to scale things up in order to meet the challenges.
With each newer format/source (homegrown), the system needs recalibrating, which is not only time-consuming but also labor-intensive. Now, compare yourself which might be better:-
Recalibrate the system every time some new format, source, or challenge comes up
Let AI do its job without having to overlook anything
As problems evolve so does the technology of dealing with it, so while it is okay to deal with the changes at one's own pace, it is nearly impossible to ignore them outright. Learn more about how AI can help in streamlining processes
so that you do not get left behind in the evermore competitive market.