Automated Payment Reconciliation with Machine Learning in 2023 – A comprehensive guide

Automated Payment Reconciliation with Machine Learning in 2023 – A comprehensive guide

Payment Reconciliation

Inaccurate financial reporting can have major repercussions for businesses and all stakeholders involved, including investors and shareholders alike. Thus, it is essential for every business to keep track of income and expenses. By doing so, a business can ensure operational efficiency, more accurate decision-making, and better oversight of the company’s finances. 

To make sure that your financial reporting is accurate and healthy, you must set up a robust payment reconciliation that can leverage AI technology. 

In this blog, we’ll explain the meaning of payment reconciliation, the importance of the payment reconciliation process, and how modern technology can help automate and accelerate parts of it. Let’s get started! 

What is Payment Reconciliation?

Payment reconciliation is the process of matching up a payment received with the corresponding invoices, receipts, or other documents ensuring that the payment is properly applied. In essence, the process makes sure that the payments and bank statements match the accounting numbers of an organization for accurate and up-to-date financial records. 

For example, when an organization receives a financial statement, such as a bank statement, costs and payments are compared against invoices or receipts to make sure that everything is adding up correctly.


The Traditional Process of Payment Reconciliation

The payment reconciliation process can vary depending on the organization, its systems, and the specific payment circumstances. However, the following steps are often involved in the reconciliation process:

  1. Collect and review payment records: First step is to gather all relevant payment records, such as invoices, receipts, and bank statements, and review them to ensure they are complete and correct for the respective time period.
  2. Match payments to invoices: The next step is to match payments to corresponding invoices or receipts. This can be done by checking the payment amount, payment dates, and payee information from the bank statement.
  3. Check for discrepancies: After payments have been matched to invoices, it is important to check for discrepancies or errors to ensure that all payments are accounted for.
  4. Resolve any discrepancies: If any discrepancies are found during the reconciliation process, they should be addressed and resolved. This may involve contacting the suppliers or vendors to clarify payment details or simply adjusting the financial records if needed.
  5. Complete the reconciliation process: Once all payments have been reconciled, the process is considered complete. Often it is needed to prepare reports or summaries of the reconciled payments.

As addressed before, all of the previously mentioned steps are not always mandatory and some organizations may have more or fewer steps in their payment reconciliation processes. 

For small firms, the process can be very straightforward with fewer clients and cash flows compared to the bigger ones. However, when an organization scales, the process quickly becomes labor-intensive increasing the complexity and risks of error. This can lead to various drawbacks that are discussed below.

The Drawbacks of Traditional Payment Reconciliation

  • Inaccurate data: With a high chance of human error, mistakes are bound to happen, which will lead to discrepancies in data that can be challenging to resolve. 
  • Time-consuming: Companies can waste a significant amount of time reconciling payments, especially when it’s done manually or if there are a large number of payments to reconcile.
  • Inefficiency: Many traditional payment reconciliation processes rely on manual data entry and manual matching of payments and invoices, which can be extremely inefficient and prone to errors.
  • Lack of visibility: With the traditional process, companies don’t have a real-time overview of their expenses, payments, and outstanding invoices. The lack of cash flow oversight can be challenging for businesses to make informed decisions.
  • Risk of fraud: Any individual can create fake invoices or alter real invoices in order to receive payment for goods or services that were not actually provided using fictional company details. This is also known as invoice fraud.

Luckily, there are various tools and options for businesses to automate and optimize their payment reconciliation workflows. These tools are discussed in the following section.

Useful Tools for Optimizing Payment Reconciliation Workflows

Many businesses have already incorporated semi-automated procedures into their reconciliation processes using:

  • Enterprise Resource Planning (ERP) System
  • Accounting Automation Software
  • Robotic Process Automation (RPA)
  • Document Management Software

In the following sections, we will dive into these solutions, and explain how they can be used to streamline and improve the efficiency of the reconciliation process.

Entreprise Resource Planning (ERP) System

Enterprise Resource Planning (ERP) software is a comprehensive system that helps organizations to plan and manage their core processes, including supply chain, manufacturing, and financials. ERP systems can be used to automate the payment reconciliation process by providing a centralized location to manage financial transactions, including payments. 

With an ERP system, payments can be recorded and tracked in real-time, and invoices, receipts, and other documents can be easily accessed and matched with payments. This can help to reduce manual tasks, human errors and improve the efficiency of the reconciliation process.

Next to that, ERP systems can also be integrated with other systems such as accounting software, which can provide a comprehensive view of financial transactions and make it easier to track and reconcile payments.

Accounting Automation Software

Similarly to ERP systems, accounting software can provide centralized locations to manage and track all financial transactions of a company in real-time, including payments. With accounting software, invoices and receipts can be easily accessed and matched with the payments, making payment reconciliation convenient. 

Next to that, many accounting software programs offer automation capabilities, such as automated data entry and payment-invoice matching, further optimizing the reconciliation process. Overall, accounting software can be an effective tool for automating the payment reconciliation process and improving the accuracy and efficiency of financial transactions.

Robotic Process Automation (RPA)

Robotic Process Automation (RPA) is a set of software programs that utilize machine learning (a subfield of AI) to mimic workers. Instead of creating a set of processes/programs to use, RPA learns from human behaviors by using Graphical User Interfaces (GUIs) to replicate the same set of tasks. 

This ultimately reduces human effort in repeatedly typing in entries, for example, and further minimizes errors that are caused by potential fatigue or distraction. 

Within the payment reconciliation process, RPA can be used to eliminate manual data entry and matching of the documents. It can be integrated into various systems such as accounting software, ERP systems, and many others.

Document Management Software

Document Management Software can be used to store and organize invoices and other documents related to payments. This makes it easier to locate and match payments with the corresponding invoices or documents.

In addition, a few Document Management Software programs offer automation capabilities, such as the ability to automatically index and categorize documents, also known as document classification. This can further improve the efficiency of the reconciliation process.

Overall, the solutions we have mentioned are very useful in optimizing the payment reconciliation process. However, most struggle to help fully automate manual data entry and payment-invoice matching without technologies like Optical Character Recognition (OCR) and machine learning.

OCR & Machine Learning for Automated Data Extraction

OCR is the underlying technology that can turn an image into text given that the image quality is sufficient. With OCR, companies don’t need to manually record data from documents, such as invoices, into their bookkeeping or other software systems. OCR provides businesses with an easy means to extract data and digitize documents used in the payment reconciliation process.

Payment Records Extraction with ML

Of course, with OCR alone, you can only do so much. That is why Machine Learning, a subset of AI, is a very important technology to couple with OCR to automate payment reconciliation. With Machine Learning, it is possible for businesses to automatically match the extracted data with other documents or data sources, ensuring accurately reconciled payments.

To conclude, solutions that incorporate these technologies are potentially the best for automating payment reconciliation. However, there are some things to consider before trying out various solutions. This is why in the following section, we provide tips to start building an automated pipeline for your payment reconciliation. 

Possible Challenges & Tips in Automating Payment Reconciliation

There are a few factors that can make it challenging for your business to automate the payment reconciliation process. The following section discusses these challenges and tips for overcoming them.

  • Change of the existing systems: If your organization is large and is operating with complex systems, it can be difficult to implement software to automate payment reconciliation due to the possible need to change the existing system. 

Find out if the solution offers the right integration possibilities via a consultation call or online demonstration with the solution provider (it’s free!).

  • Limited resources: Automating the payment reconciliation process may require investment in new software or other resources, which can be a challenge if you have limited resources. 

Think about the long-term financial benefits that the solution may provide by calculating the ROI based on time and costs. If it’s costing less or at least the same amount as it would with manual payment reconciliation workflow, then it is definitely worth implementing.

  • Lack of technical expertise: Businesses may struggle with automation if they do not have the necessary technical expertise in-house, or if they are not familiar with the software or systems that are needed to automate the process.

In such a case, make sure that the solution provider can help with customer onboarding and implementation, or simply acquire a low-code solution that would not require technical expertise. 

Still here? Great! It means that you are seriously considering modernizing and automating your payment reconciliation process. In the next section, we give you insights into a possible candidate that can jumpstart your automation journey. 

The Modern Way Forward is with Tech

As mentioned earlier, finding a financial software solution that uses technologies such as OCR & Machine Learning can help automate your payment reconciliation process. 

Modern solutions like Klippa SpendControl, integrate both technologies to automate expense management and invoice processing workflows including payment reconciliation. With SpendControl, you can empower your financial and accounting departments by enabling them to: 

  • Easily submit and approve receipts and invoices via the mobile app or web application
  • Automatically record expenses directly in the accounting system with self-learning journal entries eliminating manual data entry
  • Prevent fraud with automatic detection of duplicate claims
  • Gain more accurate insight into costs, categories, cost centers, projects, departments and periods by reducing human error
  • Conveniently integrate the solution to your existing ERP, Accounting, or RPA systems without the need to change everything entirely
  • Reconcile payments automatically with intelligent payment-invoice matching through Machine Learning

What does using SpendControl look like in your payment reconciliation process?

  1. Your team can submit an invoice or a receipt via the Klippa mailbox, web application or mobile app
  2. Klippa SpendControl extracts all the payment data automatically from the submitted documents with AI-powered OCR technology into your financial system
  3. 2-way matching is done automatically by comparing the data from payment documents with credit card or bank statements
  4. If there are no discrepancies, you can successfully reconcile payments

To conclude, Klippa SpendControl is a smart all-in-one financial management solution with a wide range of integrations, enabling you to easily synchronize with your existing accounting or ERP system. With our experienced customer onboarding team and high-quality documentation, the implementation will be a breeze. 

In case you have a need for a custom solution in which you would need an accurate AI-powered OCR engine, you can do that using our OCR API. To get insights into how to integrate our OCR API, you can watch one of our demonstration videos here.

It’s time to move forward with modern technology and bring your payment reconciliation process to the next level. Set up automatic payment reconciliation with Klippa SpendControl now by booking a free demo below! 

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