Revolutionizing Accounting Efficiency: The Power of Automated Cash Application
30-01-2023 4 min read
Nils Strachanowski, VP of Cash Application, Serrala discusses how humans and AI can work together to accelerate outstanding invoice processing to boost efficiency in organizations with automated cash application.
In times of economic uncertainty optimized Accounts Receivable is more important than ever. What are the main challenges organizations face in their cash application process and how are these challenges exacerbated by the current crisis?
The cash application process is defined by a certain set of challenges we see in basically every organization. Foremost, we have manual and repetitive tasks that slow down the allocation process and the cash flow – this is a problem, especially in times of tightening liquidity, when you want to have your cash available as soon as possible. Delayed cash application is often a result of sluggish processes. Many organizations also suffer from a lack of visibility, which can be even more detrimental when you are going through a crisis and need to know where your cash is. Furthermore, fragmented processes and limits of currently implemented solutions also hinder finance departments to tap into the full potential of their cash application process.
How can organizations overcome these challenges?
Well, manual and repetitive tasks can be easily addressed with intelligent automated cash application. There are solutions that can achieve the highest possible automation rates of nearly 100 %, reducing manual activities across the board. They significantly bring down the number of outstanding invoices and update customer accounts first thing in the morning and help with the monitoring of important KPIs and gain full transparency of the process. Organizations also really benefit from a higher level of standardization with a solution capable of processing all incoming formats and facilitating intelligent technology including Artificial Intelligence and Machine Learning to achieve the best possible results and contribute to overall business efficiency.
How can automated cash application process be maximized?
There are 3 key areas to successful cognitive cash application:
Neat end-to-end processing is key. All common formats from banks, such as statements and lockbox, from customers, including all types of remittance advice, and settlement files, and from payment service providers are automatically accepted. Numerous re-built reporting KPIs and KYC features ensure transparency and users can create their own matching rules, while integrated workflows improve process quality.
It’s crucial to bank on future-proof technology. For example, Artificial Intelligence and Machine Learning used for matching of outstanding invoices and supporting the digital transformation via a hybrid cloud approach, combining on-premise advantages with cloud agility.
Ensure these technologies are perfectly married to humans’ abilities. Through this symbiosis organizations achieve high automation rates and reduce manual and repetitive tasks by 85% on average. The result: same day receivables matching and no more unapplied cash, lower DSO and more efficiency in the up-and downstream order to cash processes.
You mentioned Artificial Intelligence and Machine Learning. These are also sometimes called “cognitive technology” due to their self-learning and self-acting capabilities. Can you give an example of how cognitive and automated cash application works practically and how organizations benefit from these technologies?
The key approach is to have humans and AI work together for the best possible results in automated cash application. Today people can be more empowered to make strategic decisions by giving them tools that reduce non-value-added tasks. Choose cash application solutions that offer rules that are simple to set up – even for complex scenarios. This way you can leverage any information provided in bank statements, remittance advices, and settlement and lockbox files and adjust pre-configured rule templates within seconds. Transparent feedback loop helps to further improve the rules. Then our AI Match feature provides AI-based matching without any manually created rules. Customer payment behavior is analyzed and affects the scoring and decision making and machine learning is applied for customer names and bank details. Automatic learning is also used to improve remittance advice recognition. Next, cognitive technologies can easily detect exceptions and thereby speed up the exception handling for bank statements, lockboxes and remittance items. Finally, automated triggering of follow-up actions significantly reduces the time to handle outstanding invoices and collect cash.
From your experience and feedback you get from your clients, do you expect cognitive technologies to play an important role in the future of the cash application process?
Definitely. We’ve seen it moving in that direction for a long time now. And the remote working movement has once again emphasized the importance of a solid digital infrastructure. We, at Serrala, do our best to support our clients on their digital transformation journey. For instance, next to our new cloud solution for automated cash application, we have cloud-based solutions for automated request to pay and PSP reconciliation in our portfolio. They perfectly complement our cash application solutions, once again following our end-to-end approach in AR automation. We believe this is the future in finance and accounting, and our clients and overall market developments seem to agree and already are reaping benefits from these technologies.
Want to learn more?
Visit this page and discover how you can improve your AR automation and eliminate manual effort with real-time cash application.