According to a 2020 Forrester Consulting survey, 65% of businesses report that reconciling payment transactions with open invoices is among the most labour-intensive business process. However, this issue can be mitigated by implementing automated banking transaction reconciliation.
AI-powered banking transaction reconciliation can help reduce expenses, improve accuracy, and even reduce—if not eliminate—labour costs. So, in this post, we’re going to discuss how you can implement the technology and show you how you can work around its challenges.
AI-embedded banking transaction reconciliation is a powerful tool for that can simplify and streamline your organization’s payment process. While the transaction reconciliation is automated, it is still fully auditable by humans.
You can set up rules for allocating payments based on your company’s accounting system or other logic, enabling you to eliminate manual steps in reconciling data. In addition, it can identify discrepancies and irregularities in data entry for immediate correction.
Of course, since the entire reconciliation process is automated, you can cut down labour costs and save time.
We go through various payment transactions on a daily basis—from parking fees, a coffee at Starbucks, or phone bills. Every time you process a payment, the system will learn and establish bank rules to classify them automatically. The algorithm will then be able to determine how a transaction flows into the correct account and line item in an automated reconciliation.
We know that automation brings a host of benefits, but implementing intelligent finance tech is not without challenges. Here are some of the issues you may encounter:
Data Security and privacy are major concerns that must be addressed when implementing intelligent finance technology. As institutions adopt automation, they will increasingly collect and store the data of their customers.
This data is extremely valuable and could be used by criminals or hackers to commit identity theft or other crimes. Financial institutions must ensure that customer data is protected from unauthorized use by implementing strong security measures.
There are no clear guidelines on how regulators should oversee these types of transactions. Moreover, it is unclear whether the current rules are sufficient. Financial institutions will need to work with the right governing bodies to ensure that any transactions conducted using AI technology are in compliance with applicable regulations.
The development and implementation of AI technologies require the participation of a wide range of stakeholders, including financial institutions, technology companies, and regulators. Each of these groups has its own interests and priorities, and it can be difficult to reach a consensus on issues such as standards and regulatory rules for AI-powered finance.
Since automated banking transaction reconciliation is a new process, you’ll need to retrain your employees. You need to educate them on how the technology can improve your business processes and financial services. Now, workers who are not familiar with AI-embedded banking may find it difficult to keep up with the rapidly changing landscape of the financial industry.
As we’ve mentioned, automation has advantages, but implementing it comes with challenges. Thankfully, there is a tool that can simplify the entire process—Tirnu. With Tirnu’s AI-embedded system, you can automatically manage, monitor, and reconcile your banking transactions.
With the tool’s lightweight and user-friendly design, you won’t experience a learning curve. Within a few taps on the app, you can monitor expenses, organize invoice payments, and even manage your investments.
Because Tirnu’s AI tech learns your spending behaviour, you can cut down labour-intensive tasks and focus on more important matters.