The finance and accounting department is the heart of any business, and where it sits in terms of digital transformation manifests where the organization sits. A modern-day CFO is considered a strategic changemaker who brings about innovation and automation through technological solutions rather than a bookkeeper. Processes such as Accounts Receivable are critical to the business and complex, highly labour-intensive, and detail-oriented functions. Simple automation too, struggles to create an impact, as there are a lot of unstructured data, complexity, and scalability issues. With the average accounts receivables days ranging from 10 to 300+ days, we wonder how we can enhance the process. In this blog, we will find out how AI-powered digital co-workers can transform the AR (Accounts Receivable) process and make an organization more productive with better customer and employee satisfaction.
What is Accounts Receivable?
A critical part of any company’s assets is Accounts Receivable. It supports generating cash inflow in the accounting books of the enterprise. It also determines the enterprise’s future cash flow as easing the transaction process for the customers, providing credit facilities, and establishing a robust relationship with the customer add value to the business. Furthermore, proficient AR management attracts better deals, as well as, good investors since a good collection efficiency record is a requisite for investors who are looking to invest.
Moreover, after the pandemic, whether a company is small or big, we can understand that the organization’s cash flow gets the foremost emphasis. Thus, every business is looking for the most effective and efficient ways to manage their accounts receivable so that the receivables in the balance sheet are quickly transformed into cash.
Why is Accounts Receivable important?
Management of accounts receivable has the capability to make or break a business. Mismanagement in AR can cause disastrous cash flow scarcity. According to research by U.S. Bank, about 82% of businesses close shop suddenly due to defects in their cash flow system. Thus, every business needs to manage its accounting carefully and avoid mishaps.
Manual vs. Automation processing
Though the exact workflow may vary, the basic AR process includes the following steps:
- Billing – Sending invoices to customers.
- Payment collection- Customers pay the outstanding invoices.
- Reconciliation- Matching payments to invoices and updating the records.
According to Paystream Advisors, for businesses that use manual processes for AR processing, 15% of their time goes to prioritizing work, another 15% to assembling data to collect, and only 20% of the time on customer communication regarding collections. Again, the businesses which use ineffective tools for managing the accounts receivable processes also spend a lot of time on manual efforts. Each step of the AR process, viz invoicing, payment collection, and reconciliation, involves many tedious, time-consuming, and error-prone steps. Automation can relieve many mundane tasks and augment the AR process.
What is AR processing after leveraging RPA tools?
Robotic process automation (RPA) has been around for some time, and it helps execute high-volume, repeatable, and rule-based tasks. It can automate AR processes such as invoicing and cash reconciliation smoothly. However, with the present high volumes of AR processing in most industries, mere RPA and OCR (optical character recognition) will not suffice. Moreover, there is a need for more workforce in every industry. In addition to that, customer expectations are grand. Customers hardly have the patience for slow processing or errors. Even after leveraging RPA solutions, the enterprise may need additional software and solutions. For instance, when it comes to prioritization and flexibility, an RPA tool cannot identify from a pool of invoices. Or when there are varied sources and multiple formats, RPA will need additional help to overcome them and automate the workflow. Thus, the time has come for enterprises to integrate Artificial Intelligence in simple rule-based automation processes.
Transformation beyond RPA- augmenting AR with a digital co-worker
What is the next best solution? Organizations need a comprehensive and cognitive solution to augment the employees. This is when Machine learning, Intelligent Character Recognition (ICR), Analytics, Artificial Intelligence, Natural Language Processing, and RPA all come together as a complete solution in the form of a digital co-worker. Just like another organization employee, a digital worker is a software solution who is intelligent and can not only automate the tasks but can carry out complete end-to-end tasks efficiently. With human-in-the-loop, the digital co-worker escalates any issues to the human employee and learns while doing. So that the next time the same issue comes, it can handle it on its own. The seamless blend of all the AI (Artificial Intelligence) tools, analytics, and automation can skyrocket the AR processes.
Transformational touch points
A digital co-worker can transform the AR process in several ways:
- Available 24/7 with no burnout- A digital employee works even when human employees take a break, all the while automating the tasks and managing the complete processes.
- Connection – Since a digital co-worker is easy to set up and forms a seamless connection between the processes and human employees, it delivers the best outcomes. It boosts not only the customer and employee experiences but also all the business stakeholders.
- Transforms the journey– Leveraging digital workers, you can re-engineer the user, customer, and employee journeys.
Tara, the Accounts Receivable Specialist
Let us consider the digital co-worker Tara- an accounts receivable specialist. Unlike any other automation processes, Tara can manage the entire AR process, from credit management to invoicing and reconciliation. Some of her responsibilities are:
- Receiving and authenticating all the bank wires
- Maintaining the auditing databases and spreadsheets and updating information whenever required.
- Corresponding with customers and clients to request payment and arrange payment plans
- Collecting payments from the customers and records in the system accurately
- Analyse and produce reports documenting overall profits and losses
- Updating clients’ accounts based on payments/contact information
- She can instantly connect to the financial systems of record.
- Collect and normalize forecast inputs across all the systems.
What are the key advantages of having Tara in AR processes?
- Complete automation of all the receivables
- 3 times increase in collections productivity
- 24/7 customer service
- 50% decrease in operational cost of collection
- 40% reduction in DSO
What is unique about having a digital co-worker?
- Scaling is easy– you can scale up or down easily, as per your requirements.
- Maintenance– For any automation processes, it is an ongoing process that incurs regular maintenance costs. For digital co-workers, there is none, as it is included in the subscription itself.
- No platform licensing costs– Any software solution will have its platform licensing costs. A digital co-worker does not require any license costs.
- Easy integration – Supporting restful API, digital co-worker gets easily integrated.
- No add-ons required – Any other software tool may require custom development and continuous improvements in its processes.
- Active learning – A digital co-worker keeps enhancing the processes by bringing about continuous improvement via active learning.
Digital Clerx
Saxon’s Digital Clerx is revolutionary and can bring about positive transformational changes for enterprises. Tara is one such Digital Clerx who handles the Accounts Receivables process. Apart from Tara, there are various other personas such as Emma- Accounts Payable Specialist, Insurance underwriter, expense management specialist, customer service specialist, and many more. You can also have a digital co-worker tailored for your specific roles. Moreover, you can schedule a free trial and see how it delivers value from day one itself.