A complete guide to Invoice Processing on Autopilot

Streamlining invoice processing is paramount to maintaining operational efficiency. The traditional methods of manually inputting and cross-checking all the key fields and line items are highly error-prone and lengthy. 

Automated invoice data extraction and streamlining invoice validation allow businesses with high volumes of documents to optimize their approval workflow while processing invoices with incredible accuracy and efficiency. 

Now the question is, how can you set invoice processing on autopilot? 

Keep reading to learn more about automated invoice processing and the importance of document AI in this process. 

Challenges in manual invoice handling and data entry

Manual handling of invoices and data entry is afflicted with inefficiencies such as: 

1. High error rate 

Three-way matching is a common accounting practice where the accounts departments compare the invoice with a purchase order (PO) and goods received note (GRN) to check its legitimacy. Generally, accountants manually check the items against each other and verify details like the final balance, due date, and order number. 

The analog matching skills make the invoice processing workflow prone to human errors. The subsequent process of correcting and reversing erroneous payments makes it a tedious and resource-intensive ordeal.

These systems get even more complex with four-way matching, which also includes inspection slips. 

2. Increased exposure to internal and external fraud

Manual approval and verification of invoices increase the organization’s exposure to both internal and external fraud. 

Aggrieved employees and finance professionals can manipulate the payment details and due dates to embezzle funds. Most likely, these fraudulent payments are detected only when there’s a major disruption in the cash flow. In addition, accounting discrepancies are flagged during monthly/quarterly/yearly audits. 

To add to the woes, the accounting department is the preferred target for phishing emails and ransomware. There have been instances where cybercriminals posed as members of the upper management or suppliers and persuaded the finance department to release unauthorized payments. 

3. Payment delays

Even after the implementation of sophisticated accounting software, 86% of companies still rely on paper-based invoice processing. Consequently, the invoices pass through multiple departments for validation and approval, causing payment delays.

Payment delays can strain relationships with suppliers and affect their cash flows. Repeated delays can potentially force vendors to levy late charges and other penalties. Streamlining the manual approval process for these invoices still cannot account for delays caused by unforeseen human errors. 

4. Invoice mismanagement 

Lastly, paper-based invoices and purchase orders get misplaced. The retrieval process only increases the burden on the already overworked accounting department. In the case of document misplacement, the organization has to contact their vendors to release another invoice, restarting the entire process. 

Document AI for automated data extraction and validation 

Document AI for invoice processing is capable of resolving the shortcomings of manual data extraction. 

The AI, along with optical character recognition (OCR) and natural language processing (NLP), streamlines the invoice data extraction process. The captured data is also instantly verified and validated, and then sent downstream for further processing. 

1. Data extraction

Automated invoice data extraction incorporates AI-enhanced OCR to automatically convert complex and varied invoice formats into machine-readable and searchable texts. Then, NLP understands the context and automatically categorizes it for the accounting department.

The AI’s machine learning (ML) capabilities ensure that the document AI software gets accustomed to new invoice formats with little to no human intervention. 

2. Data validation 

Following the data extraction process, the automated invoice processing software conducts name, line-item, and pricing validation. 

To begin with, the name validation process checks whether the vendor and client names are correctly mentioned along with the bank’s name. Next, the automated line-item validation process checks for the order quantity, quality, delivery dates, due date, and reference number and compares this captured data with multiple internal documents like GRN, PO, and procurement records. 

Lastly, the document processing platform conducts two-way, three-way, or even four-way matching depending on the organization’s needs. For the majority of the invoices, this is the final validation step. But, for the few others, the invoices are also matched with the contracts to complete the process. 

Benefits of Document AI for invoice processing 

Document AI software has revolutionized invoice processing. Apart from automating the invoice  data extraction and invoice validation process from start to finish, it also-

1. Reduce invoice processing time to 30-60 seconds

Document AI massively reduces invoice processing time thanks to its sophisticated ML algorithms and data servers. Since all the invoices and essential data are stored in the cloud, it becomes easier for the accounts payable team to retrieve documents from this single source of truth. 

Beyond that, document AI for invoice processing offers role-based access to these documents for added security. 

2. Increase accuracy rate to more than 99%

Accounting errors and mishandling of paper invoices create operational bottlenecks for multiple departments. Accounts payable and the finance departments have to reallocate resources to resolve these hurdles. 

On the other hand, the document AI software extracts data and processes it with 99% accuracy. Exception handling in invoice processing also becomes easier as it automatically flags any irregularities in the invoices and notifies the accounts, payable team.

The end-to-end invoice processing automation reduces human intervention, further reducing the scope of errors. 

3. Reduce turnaround time by 10X

Streamlining invoice validation with automation reduces invoice processing times from a few weeks to a couple of minutes. The increase in efficiency starts with the elimination of manual data entry processes. 

The faster matching times make it easier to complete the validation and verification within seconds. Overall, the implementation of document AI software in the organization drastically improves the productivity of multiple departments. 

4. Reduce operational costs by 65-70% 

The faster processing speeds enable organizations to make timely payments and avoid late payment charges. In addition, your company can capitalize on early payment discounts offered by vendors. 

The data is stored in the cloud, eliminating the need for physical storage of documents. Finally, flagging fraudulent activities, forged invoices, and duplicate payments helps prevent any financial leakages. 

How does Document AI automate data extraction from invoices?

It starts with data capture from key fields and continues to validate the data using ML algorithms. Here’s a closer look at the process. 

1. Extracting data from key fields

Document AI uses ML to identify and extract data from key fields in invoices, such as the invoice number, supplier name, date, line item details, and total amount. This data is stored in a structured format and can be easily processed by accounting systems.

2. Automating invoice validation 

Document AI can also be used to automate invoice validation. This means the platform checks invoices for errors such as missing or invalid data to ensure that invoices are accurate and compliant with different industry and international regulations. 

3. Reducing human intervention

The platform for streaming invoice validation does not require the human intervention required to complete data extraction. There are times when the organization might choose a human-in-the-loop system to resolve exceptions. That said, finance teams can focus on more strategic tasks, like budgeting and financial planning, rather than data validation. 

4. Handling exceptions

Some invoices may contain errors or be formatted differently than others. When the ML algorithms fail to handle these exceptions, it notifies the accounting departments to review and make necessary changes to the process. 

5. Integrating Document AI with existing accounting systems

The automated invoice data extraction software can be integrated with existing accounting systems to facilitate the downstream data flow. Docsumo’s native integration with QuickBooks, Stripe, Xero, and Chargebee allows it to easily transfer data without the requirement of third-party applications, thus increasing data security. 

6. Enhancing data accuracy

ML algorithms continuously learn from patterns in data and improve their processes. In other words, document AI becomes more accurate over time as it learns from the data it extracts and validates.

Data security considerations 

Regardless of the industry, the security concerns related to invoices remain the same for most companies. Let’s look at some of these data and security considerations, and how Docsumo’s document AI software gives enterprise-grade security to users. 

1. Sharing invoice data with third-parties

The biggest concern for most companies is the leakage of their financial information due to security breaches on third-party servers. The fear of misuse of this information by third third-parties also exists. 

Docsumo’s GDPR and SOC-2 compliance certifications alleviate these concerns and allow companies to automate their invoice processing without fear of any mishandling of this data. 

2. Security vulnerabilities 

Docsumo’s SSL encryption ensures that the user’s data is protected from end-to-end and prevents most cyber threats, like brute force hacking and ransomware. 

Best practices for successful implementation of the automated invoice processing system 

Follow these best practices for a seamless implementation of your preferred invoice processing software. 

1. Examine current invoice processes

The current invoice processing challenges should be the starting point for document AI software implementation. Identify the archaic process and how it can benefit from automation to better understand your landscape. 

2. Get approval from the stakeholders

Loop in your stakeholders, vendors, C-suite managers, accounts payable team, and finance before you implement your document AI systems and educate them about the benefits of the system. Their insights and suggestions help you prepare a framework and list of desirable features to look for in accounts payable automation software. 

3. Select the right IDP software provider

Ensure that the software has automation solutions for your industry and integrates with the third-party systems used by your organization. Try demos and take up free trials before committing to one. 

Conclusion 

Docsumo’s document AI can be better understood by closely looking at one of their recent use cases. 

An Australian-managed service provider, Valta Tech, was faced with the following invoice data extraction challenges. 

• A team of 20+ employees was responsible for manually processing over 20,000 invoices every month.
• Manually scanning and preparing unstructured invoices.
• Managing over 100 different vendors with 100 different invoice formats and subpar validation processes
• The accounting department had to do a double entry for all the documents

Docsumo’s advanced document AI features came in handy while streamlining the invoice processing workflows for Valta Tech.

• It used AI-based APIs to capture data from unstructured documents and invoices
• 95% STP rate meant that the employees only had to manage and review the exceptions
• Docsumo’s ML-based smart data extraction algorithm managed to capture data from more than 100+ different invoice formats
• The AI algorithm auto-classified letters and validated their data in real time. 

If you’re looking to automate and streamline your invoice data extraction and validation process, try out Docsumo for free.