How is AI revolutionizing Accounts Payable Automation?
23 Feb 2021 Ashutosh Saitwal
Accounts Payable Invoice Automation

Long before our country embraced civilization, millions of invoices were to be processed in a month. The finance sector was looking for a much-needed change in their traditional invoicing workflows which involved hand-to-hand exchange of invoices and payment. The accounts payable (AP) processes were entirely manual and human-dependent.

The Challenges of Accounts Payable Automation and Invoice Automation

Digital invoicing was the first time AP embraced technology where a scanned copy of the invoice is generated. This helped to keep the invoices in soft copy format, but the change was not enough to combat the challenges associated with manual invoice processing and payment. Digital invoices were indeed introduced to eliminate human intervention, but the AP processes still involved manual data entry into the ERPs, approval, and verification processes. Although digital invoices brought the commute to an end, they could not reduce the time, money, and resources spent in processing those papers to extract and interpret the data.

Hence, the AP department switched to OCR (Optical Character Recognition) to automate data entry. The new technology automatically extracted 100% data from invoices. But to interpret the data for specific fields like invoice number, invoice date, invoice amount, supplier name, PO reference number etc. was still done manually.

Also, the verification process was still manual. During the reconciliation of invoices, the AP department recognized errors in the extracted data along with many unprocessed invoices.

When one closely examines the issue, the lack of data interpretation is the major cause of errors and unprocessed documents. The concept of OCR did automate data extraction but it failed to incorporate the ability to understand the context of data into the big picture during accounts payable automation.

The advent of sales invoicing software itself posed a challenge for the AP department of the receiving organizations- the companies started using variable invoicing formats. Consequently, the template-based OCR solutions evolved. But these solutions had to use a new template for every invoice format to extract data from it. In addition, late processing of payments to vendors meant that the managers were all consumed in manually rectifying the errors and risking the company’s reputation for late payments. This led to only 20% cost saving and 40% automation.

The scenario is completely different today, isn’t it?

The accounts payable processes kicked out human intervention and boosted productivity by up to 200%. The introduction of AI into accounts payable automation paved the way for intelligent and contextual data extraction and interpretation while automating the routine functions, improving decision-making, and mitigating compliance and fraud risks. Even with the varying placements of the information, AI-based solutions made template-less data extraction and interpretation of invoices possible,

Let us take a detailed look at how AI made accounts payable automation evolve in its totality.

AI-driven Accounts Payable Automation - The Revolution

1. Automated time-consuming and repetitive tasks

Most of the AP professionals’ time is consumed in routine tasks involved in invoice processing. A comparatively lesser amount of time was left for high-priority functions such as data analysis and decision-making. AI has automated these time-consuming tasks including, data extraction and field interpretation, invoice routing, exception handling, and compliance checks.

The technology has also triggered the AP processes while freeing the staff to accomplish value-added goals.

2. Increased accuracy and productivity

AI has the capability to learn from the user feedback and the scenarios exposed to it. While traditional automated document processing was dependent on a layout-specific approach and led to inaccurate results, AI-driven AP processing can precisely extract and interpret even unstructured datasets. AI automatically trains itself on what should be done when confronted with unexpected scenarios by comparing their characteristics to known/solved scenarios.

The ability to self-train and identify possible solutions to a problem allows AI to improve document processing accuracy while eliminating human intervention. The technology thereby increases business productivity.

3. Reduced labor and implementation costs

Manual and semi-automated AP processes involved a lot of money invested in employee hiring, onboarding, and training. Further, implementing a new set of rules and templates for every other document added to the expenditure. On the other hand, AI driven OCR requires very little manual processes thereby reducing the cost.

Talking about implementation, AI employs a template-less data extraction and interpretation technique to process invoices. Hence, implementation costs are already reduced to a large extent. With template-less AI driven OCR, one can expect to save .

4. Enhanced forecasting and financial planning

While traditional automated AP processes fail to capture critical information and restrict decision-makers to access key information at the right time, AI-driven solutions make forecasting, easier, quicker, and more accurate. Apart from scanning and analyzing loads of information from various sources, AI uses patterns and trends in the data to forecast cash, spending, and other critical information to help businesses make strategic decisions.

On using the forecasts and predictions made by AI, the businesses can determine the potential opportunities to release cash and benefit from early-payment discounts.

5. Overhauled compliance checks and fraud detection

Due to their inability to deal with unstructured data, semi-automated AP processes result in erroneous data, compliance issues, and fraud risks. In contrast, AI proactively manages compliance and fraud risks by identifying trends and patterns that indicate potential frauds and violation of compliances. In addition, AI can also look for duplicate transactions or payments, thereby preventing loss of profit margins.

Whenever the AI flags a transaction inappropriate, the underlying authorities take over the charge of reviewing the documents.

The KlearStack Advantage

KlearStack powers a fully-automated and ERP integrated AI technology that enhances your AP departments’ efficiency to process more invoices in time and embrace exciting business opportunities. Our AI-based solutions incorporate deep learning, OCR, and NLP (Natural Language Processing) methods to contextually extract and interpret data for improved field level accuracy, forecasting and decision making with accounts payable automation.

Look after your business reputation before it’s too late! Contact us today to automate your accounts payable document processing in its totality.

Recent Post

How is AI revolutionizing Accounts Payable Automation?
How AI-driven OCR solutions trump traditional OCR for improving business efficiency!
How is the Accuracy Rate of an OCR Scanner Measured?

Meta

fmovies moviesjoy primewire yesmovies 123 series 123 movies hd 123movies 123movie watch tv shows free online watch tv shows online watch anime online free watch movies online free watch free tv series watch free movies online myflixer flixtor watch series online free swatchseries soap2day watchmovieshd watchserieshd