Reconciliation: The Bane of Every Treasurer’s Existence…Or Is It?

Reconciliation: The Bane of Every Treasurer's Existence...Or Is It?

If you’re a treasurer, chances are good that you dread reconciliation. It’s time-consuming and notoriously difficult to get everything to match up perfectly, and it often requires manual intervention. But what if I told you there was a way to make reconciliation easier? Well, there is—this is where RPA (Robotic Process Automation) and AI (Artificial Intelligence) come in to assist.  

RPA automates repetitive, rules-based tasks, such as data entry, while AI can help with more complex tasks, such as identifying patterns or discrepancies. Combined, these two technologies can greatly assist with the bank reconciliation process. Let’s take a closer look at how they work.

The Perils of Reconciliation

One of the biggest challenges of bank reconciliation is that it’s time-consuming. Financial professionals must manually review each transaction on the company’s books and compare it to the corresponding transaction on the bank statement. This process can take hours, if not days, to complete—especially if there are many transactions to review. And if any discrepancies are found, even more time must be spent researching and resolving them.

Another challenge of bank reconciliation is that it’s prone to error. Human beings are fallible, and even the most careful professional can make mistakes when reviewing a long list of transactions. One incorrect entry can throw off the entire reconciliation—and cause many headaches in the process.

Thankfully, there’s a solution to these challenges: automation. Automated bank reconciliation software can quickly and accurately review all transactions on both the company books and the bank statements—saving valuable time in the process. And because automated reconciliation is done using algorithms rather than human beings, it’s much less likely to contain errors.

How RPA Works?

RPA automates routine, rules-based tasks that humans typically perform. For example, data entry is a perfect candidate for RPA because it is repetitive and requires little to no judgment. By automating this task, you can free up your employees to focus on more value-added activities.

RPA software “bots” mimic human actions to interact with digital systems just like a human would. They can log in to applications, enter data, click buttons, and so forth. Bots can also be programmed to make decisions based on set rules—for instance, if X happens, then do Y. This makes them well-suited for automating complex processes that require multiple steps and touchpoints.

How AI Works?

AI takes things one step further than RPA by adding cognitive capabilities such as natural language processing (NLP) and machine learning (ML). NLP allows computers to understand human language and respond in a way that is natural for humans. ML enables computers to learn from data to improve their performance over time without being explicitly programmed.

For bank reconciliation specifically, AI can be used to identify patterns or discrepancies in large data sets—something that would be difficult or impossible for humans to do manually. For example, if you have thousands of transactions happening daily, it would be impossible for a human to go through all of them and identify which ones don’t match up. However, an AI system could quickly scan all of the data and flag any discrepancies for further review.

What to look for in reconciliation automation software?

When choosing reconciliation automation software, there are a few key features to look for:

  • The ability to automate both simple and complex tasks: Look for reconciliation software that can automate both routine data entry tasks and more complex tasks such as pattern recognition.
  • A user-friendly interface: Reconciliation software should be easy to use, even for those who are not tech-savvy.
  • Robust security: Since reconciliation software will have access to sensitive financial data, it’s important to choose a solution with robust security features.
  • Integration with other systems: Reconciliation software should integrate seamlessly with other systems, such as accounting and ERP applications.

Conclusion

If you’re tired of dealing with the headache that is bank reconciliation, know that you’re not alone—but also know that there is a solution. RPA and AI can greatly assist with this process by automating repetitive tasks and providing cognitive capabilities such as pattern recognition and anomaly detection. Automation provides real-time visibility into a company’s financial position and generates reports that can be used to improve the reconciliation process going forward. So, if you’re looking for a way to take some of the pain out of reconciliation, look no further than automation!

Fennech can easily do all of the above for you with minimum implementation. Working smarter, not harder, drove us at Fennech to create F³, our intelligent platform. No more headaches! We are just a call away. Get in touch!

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