Accounts receivable (AR) procedures are becoming both more efficient and more humane at the same time - thanks to artificial intelligence and machine learning.

Although the largest asset on the financial statements of most businesses is typically accounts receivable (AR), there are ways to manage it more profitably. Initially created to keep the bill payment process as organised as possible, AR processes have become more challenging to manage as B2B supply chains and payment terms have advanced in sophistication.

The costs of “getting it wrong” are increasing as a result of poor management of the processes from invoice to cash collection, which causes a build-up of past-due invoices and subsequent issues with cash flow.

Businesses must rely more and more on pricey bank financing as they have less control over operating cash. This problem can be solved if credit is available. However, nowadays, it is not always possible to obtain bank credit. And let’s not forget that the day’s sales outstanding or DSO ratio closely correlates with the company’s financial health.

This article explores the impact of artificial intelligence on accounts receivable processes. It will cover how AI technology is automating and streamlining tasks such as invoicing, payment processing, and debt collection. The article will also examine how AI-powered analytics and predictive modelling are improving cash flow forecasting and credit risk assessment. By leveraging AI tools, businesses can improve their overall AR efficiency and enhance their bottom line.

Accounting and finance are two industries that have been significantly impacted by artificial intelligence (AI). Specifically, AI is changing how Accounts Receivable (AR) is managed, resulting in more efficient and accurate processes.

AUTOMATED INVOICING

One of the most time-consuming tasks in the AR process is invoicing. Traditionally, creating invoices requires manual data entry and processing, which can be a tedious and error-prone process. AI technology is now being used to automate invoicing processes, thereby eliminating the need for manual data entry.

AI-powered invoicing software can extract data from various sources, such as purchase orders, contracts, and receipts and automatically create invoices. The software can also use natural language processing to interpret and extract data from unstructured data sources such as emails and text messages. This saves businesses time and reduces the risk of errors, leading to faster payment processing.

AUTOMATED PAYMENT PROCESSING

Another way that AI is transforming the AR process is through automated payment processing. Businesses can use AI-powered payment processing software to receive payments automatically from customers. The software can automatically reconcile payments with outstanding invoices and initiate reminder emails to customers when payments are past due.

AI-powered payment processing also enables businesses to accept a variety of payment methods, including credit cards, electronic bank transfers, and mobile payments. This flexibility helps businesses to reduce friction in the payment process, leading to faster and more efficient payment processing.

DEBT COLLECTION AUTOMATION

Debt collection is an essential aspect of the AR process, but it can be a challenging task for businesses to manage. With AI, debt collection can be automated, allowing businesses to focus on other critical tasks. AI-powered debt collection software can automatically generate reminders and notifications to customers when payments are past due. The software can also provide personalized communication and payment plans to customers, improving the chances of recovering the debt.

PREDICTIVE ANALYTICS AND FORECASTING

AI technology is also transforming how businesses analyse AR data, making it easier to forecast cash flow and manage credit risk. By analysing past payment trends and customer behaviour, AI-powered analytics can predict future cash flow and highlight potential payment delays.

AI-powered forecasting can also help businesses to identify credit risk and take proactive steps to reduce the risk of non-payment. By analysing customer data, such as payment history and credit scores, AI-powered analytics can flag potential credit risks and suggest appropriate payment terms.

IMPROVING CUSTOMER EXPERIENCE

AI-powered AR processes can also improve the customer experience by providing more personalized and efficient services. By automating invoicing and payment processing, businesses can reduce the time and effort customers need to spend on financial transactions. AI-powered customer service chatbots can also provide real-time support and answer customer queries, improving the overall customer experience.

CHALLENGES WITH AI IMPLEMENTATION

While AI has significant potential to improve AR processes, there are also challenges associated with its implementation. One of the biggest challenges is the need for accurate data. AI relies on accurate and reliable data to make accurate predictions and insights. If the data is incomplete or inaccurate, the AI system may provide incorrect recommendations or predictions.

Another challenge is the cost of implementing AI. AI technology can be expensive, and small businesses may find it difficult to afford the necessary software and hardware. Additionally, businesses need to invest in training their employees to use AI technology effectively, which can be a significant expense.

Finally, there is the challenge of trust. Many businesses may be hesitant to adopt AI-powered AR processes due to concerns about the reliability and accuracy of the technology. This challenge can be overcome by building trust with customers and demonstrating the effectiveness of AI-powered AR processes.

This article was written by Ms Seema KUMAR, MNS Credit Management Director, for the May 2023 edition of the FCI In-Sight Newsletter.

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• This article was recently published in the FCI In-Sight Newsletter, May 2023 Edition. To read more, click here.
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