Cash management processes mean more in uncertain times like these.
During the 2008 recession, accounts receivable (AR) levels increased by an average of 10 percent, a study by the National Retail Federation found. What’s more, Harvard Business Review research found that businesses with poor AR management were more likely to go bankrupt during a recession.
One cash management process that presents both challenges and opportunities is cash application – the task of matching customer payments to open invoices in a supplier’s system of record.
Traditionally a manual, time-consuming process, cash application is being revolutionized by artificial intelligence (AI), technology that performs tasks that previously required human intelligence.
This article shows how organizations can use AI-powered cash application systems to unlock efficiency, enhance customer service, and liberate working capital by reducing unapplied funds.
Biggest cash application challenges
Accurately applying customer payments is easier said than done for many businesses.
Here are some of the most common cash application challenges:
- Wasted employee time. Manually matching customer payments with open invoices in an enterprise resource planning (ERP) application or accounting software package requires a lot of effort, often resulting in errors, posting delays, and customer frustration.
- Long cycle times. It can take up to 10 days to manually apply payments, Cashbook finds. Slow cash application can negatively impact cash flow and tie up customer credit lines.
- Lots of transactions. The inefficiencies associated with cash application grow as a company gets bigger. Manually processing a high volume of payments can quickly overwhelm staff. It can be hard to scale manual processes without compromising accuracy and efficiency.
- Multiple payment types. The shift away from paper checks for business-to-business (B2B) commerce means that organizations are likely to receive multiple types of payments, including Automated Clearing House (ACH), card, wire transfer, and mobile. Businesses now receive payments through an average of 11 different channels, according to Quadient. Managing and reconciling all these types of payments can be complex and time-consuming.
- Inaccurate or incomplete remittance information. Seventy-five percent of businesses experience decoupled remittance information, Billtrust reports. Missing or inaccurate remittance information can make it difficult for staff to determine a customer’s intentions for a payment, resulting in delays in applying payments and misapplied payments. Things become even more complicated when customers have multiple open invoices.
- Exceptions. Forty percent of payments are short or split transactions, Versapay finds. Short or split payments can make it difficult to reconcile payments. Getting to the bottom of these exceptions and posting them correctly can be time-consuming and resource intensive.
- Unauthorized deductions. It’s not uncommon for customers to deduct money from their payment without providing a clear reason or explanation. Investigating and resolving these unauthorized deductions may require weeks of back-and-forth emails and phone calls.
- Fragmented systems. Accurately matching payments to open invoices may require data from different systems, including an ERP application, customer relationship management (CRM) system, and bank statements. Poor integration between these systems and the cash application process can contribute to mismatches, data discrepancies, and posting delays.
- Compliance risks. It can be hard for organizations to strike the right balance between efficiently processing payments and complying with regulatory requirements and standards such as anti-money laundering (AML) and Know Your Customer (KYC) regulations.
Overcoming these challenges is critical to optimizing cash management practices.
Many organizations are discovering that AI offers a way to do just that.
What is artificial intelligence?
AI is technology that performs tasks that previously required human intelligence.
The technology accomplishes this by using a broad range of technologies and algorithms to simulate cognitive functions such as learning, reasoning, problem-solving, perception, and decision-making.
Once trained on an organization’s data, AI-powered systems can automate manual tasks, learn patterns, make predictions, and improve performance over time without computer programming.
AI technologies already have been deployed for business applications in a wide variety of industries, including healthcare, transportation, manufacturing, and customer service.
But it’s AI’s potential in cash application that has finance professionals excited.
The benefits of AI-powered cash application solutions
AI offers tremendous benefits in cash application.
- Fewer manual tasks. AI-powered systems eliminate the need for manual, repetitive tasks such as keying remittance data, shuffling paper and emails, and chasing down information.
- Lower overhead. Automating the matching of customer payments with open invoices significantly reduces the labor and administrative expenses associated with the task.
- Better data quality. AI-powered systems analyze and match customer payments to invoices with high precision. By automating the cash application process, AI reduces the possibility of human errors, such as data entry mistakes or mismatching payments with invoices.
- Faster processes. AI-powered systems can match customer payments to corresponding invoices in real-time or near real-time. Accelerated cash application ensures timely and accurate recognition of revenue. Reducing the time to post payments also improves customer satisfaction by reducing delays in updating account statuses and issuing receipts.
- Enhanced cash management. Automating the cash application process provides real-time insights into outstanding invoices, incoming payments, and potential cash shortfalls. The visibility and control provided by AI-powered cash application systems enables organizations to optimize their working capital and make better informed financial decisions. For instance, AI can provide deeper insights into customer behavior, payment patterns, and potential risks.
- Streamlined exceptions and deductions management. AI-powered systems automatically identify discrepancies, flag potential issues, and initiate resolution workflows, reducing the time and effort required to resolve unidentified payments and disputed transactions.
- Improved scalability. AI-powered systems can quickly scale to process more volume without requiring additional staff and without compromising accuracy or performance.
These are some of the reasons that more organizations are automating cash application with AI.
What to look for in an AI-powered cash application solution
There are a lot of AI-powered solutions out there. Choosing the wrong one can set your organization back. Here are some key considerations when evaluating AI-powered cash application solutions.
- Accuracy and efficiency. Be sure prospective solutions have a proven track record for automating cash application tasks accurately, reducing manual effort, and minimizing errors.
- Data integration. Ensure that prospective solutions can seamlessly integrate with your existing ERP, CRM, and banking platforms. The system should be capable of extracting and processing data from multiple sources to provide a comprehensive view of cash transactions.
- Machine Learning. Look for a cash application solution that uses machine learning to continuously learn from historical data and improve its matching algorithms over time.
- Flexibility. Investigate whether prospective solutions can be configured to handle your organization’s unique cash application rules, invoice formats, and payment channels.
- Exceptions resolution. To help you deal with exceptions, deductions, and disputes, look for an AI-powered cash application solution with capabilities such as automated exception identification, resolution workflows, and communication and collaboration mechanisms.
- Ease of use. AI should empower your users to manage the cash application process more efficiently and effectively. Give extra weight to solutions with a user-friendly interface, and clear visibility into cash application processes, match results, and exception handling.
- Reporting and analytics. An AI-powered system should provide real-time insights into performance, reconciliation statuses, key metrics, and potential areas of improvement.
- Security and compliance. Prospective cash application systems should comply with relevant industry regulations, data privacy standards, and security protocols, and use tools such as data encryption, access controls, and audit trails to protect sensitive information.
- Scalability. Assess each prospective solution’s ability to accommodate increasing transaction volumes without disruptions or the need to hire additional staff.
- Customer support. Consider the support capabilities of each technology provider, including their training, ongoing technical support, and regular software updates.
Choosing a solution that meets these criteria will help ensure the success of your automation project.
Automate your cash application with AI
An efficient and effective cash application process is critical to the financial stability of a business. AI-powered cash application systems enable organizations of all sizes to streamline their processes, improve cash flow management, and enhance decision-making. With the strategies outlined in this article, organizations can improve their cash application process and navigate financial uncertainty.
