Evaluating AI-Powered Accounts Receivable Solutions for Smarter Collections

Business-to-business (B2B) transactions, like those in other industries, have continued to shift toward completely digital payments. Every year, fewer retailers and organizations use paper cheques to cover expenses. 

And, as with other areas, the primary reason for using digital payments is convenience. Digital payments provide faster, more accurate payment cycles, which is critical in an industry with increasing workloads and regulations.

Because of the drive for improved efficiency, many organizations and businesses are now incorporating AI into their accounts receivable solutions (A/R) and payments. 

This is not it, in this blog post, we are going to explore an important impact on all billing and invoicing that takes place today using these advanced algorithms and provide valuable insights to the readers.

Let’s begin!

Key Takeaways 

• Understanding the role of AI in accounts receivable 
• Taking a look at the automation procedure 
• Discovering different types of AI technology 
• Uncovering some positive impacts 

What Does AI Do In Accounts Receivable?

There are many uses for AI in accounts receivable processes. Usually, though, they’re either for automation or pattern recognition. For Automation, businesses often use AI to streamline message creation or other communications. It can also be used in remittance settlement or even cash application. Sometimes it’s also used for AI chatbots as a first line of response for customer service queries. 

For pattern recognition, this is typically for identifying subtle trends that might go unnoticed by humans. This technology can be leveraged to improve forecasting, provide predictive analytics, and assist in orchestrating valuable insight, which is useful for decision-makers. It’s also possible to use it for detecting fraudulent behavior or activities that might have an impact on the payment process.

Interesting Facts 
 Instead of generic dunning emails, AI personalizes the timing, tone, and delivery channel of payment reminders based on customer behavior. This improves collection rates while preserving customer relationships.

A Closer Look At Automation

There are various options when it comes to automating accounts receivable solutions. For one, AI can be used during the billing process. This means it can create accurate invoices that are sent out on time. It can check profiles, shipping confirmation, tax rules, and other information that are automatically retrieved from integrated CRM systems by synthesizing multiple data streams at once. This approach can reduce errors and the length of a billing cycle, so customers are invoiced as quickly as possible, making them happier with the efficiency, and the company receives payment when it should.

Customer management is another area where AI can add automation features to A/R solutions. Chasing up on clients or delivering outstanding invoices can be a tedious manual process. However, with AI automation, follow-ups can be sent out, personalized emails, and more, all based on customer behavior and payment history. As such, it’s easier to keep up a positive customer relationship.

AI in A/R can also be used for support and reporting at an internal level. As such, it’s not just about keeping customers happy, but employees too. Using AI can make it easier to consolidate accounts receivable data across dashboards. This means being able to find trends in late payments or those areas with a cash flow risk. Instead of manual analysis or static reports, this allows finance teams to see real-time insights and be more proactive. Using AI can also help to bring up anomalies within data, or be used to flag accounts that are not following up on payments.

Automation can also be used for cash application, matching any arriving payments with the correct invoice. This is a time-consuming process within accounts receivable, especially if payment or remittance details are unclear or cover a multitude of invoices. As AI has the ability to rapidly look through data, it means that auto-match is possible between open invoices and outstanding payments, reducing manual oversight and speeding up all processes. All of this combines to aid in risk management to ensure better analysis of different payments. As such, using AI in these A/R processes can provide smarter decision-making regarding things like credit extension or when to escalate collection on accounts.

Types Of AI Technologies In A/R

As AI refers to any solution that automates tasks, it’s important to take a look at the different technologies on offer and what it is they specifically add to a platform.

• Machine Learning, or ML use algorithms to detect patterns in raw data and make decisions based on this analysis.
• Natural Language Processing collects relevant data from emails and chat logs and converts it into usable information.
• Predictive analytics uses historical data to make predictions.
• Robotic Process Automation or RPA, automates tasks that can become repetitive when performed manually.

The Positives Of AI In Accounts Receivable

As outlined, there are many benefits to using AI in A/R processes. First, processes can be accelerated, and this includes the whole process of invoice-to-cash process. As such, everything is streamlined with core tasks taking just seconds rather than hours. 

Accuracy is also increased as some of the more repetitive or mundane tasks are often prone to mistakes. Cash flow becomes stabilized as there is faster processing and fewer errors throughout the workflow. AI’s improved decision-making and pattern-recognition capabilities boost security, resulting in a better experience for all.

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