Treasury management
March 16, 2022

New technology is easing the burden of manual cash application processes

March 16, 2022
Michael Zinkowski
Head of Banking and Treasury Management Sales & Advisory, North America
SUMMARY

Advancements in technology, including the use of artificial intelligence and machine learning, are creating an opportunity for automation in the cash application process and increased operational efficiency.


Cash flow is the lifeblood of every business. The better an organization’s cash flow, the more easily it can operate, endure hard times and grow. While every chief financial officer knows this fundamental truth, they do not necessarily reflect it throughout their operations. Cash application is a case in point.

Cash application is the process of matching incoming payments with open invoices. Once an open invoice is matched to an incoming payment, the payment can be posted to the accounting or enterprise resource planning system. At that point, the resulting cash flow can be deployed by the organization. By contrast, payments that cannot be matched remain as exceptions.

Clearly, cash application efficiency is one factor that helps determine a company’s cash flow. When performed manually, it is time-consuming and costly. It leads to slower match rates between incoming payments and remittance information, an issue that human error exacerbates.

Organizations that rely on manual cash application thus have longer days sales outstanding (DSO). This negatively impacts working capital that could otherwise be used as a source of liquidity for the company expenses, projects, and investments.

Cash application challenges

Unsuccessful invoice-to-payment matching issues relate to remittance data defects and payment amount discrepancies.

Remittance data are invoice details accompanying an incoming payment. These include the payor’s identity and the goods or services to which the payment should be applied.

An incoming payment received without such remittance data presents a challenge for the company to apply the payment. Traditionally, remittance data was sent in the mail alongside a paper check. However, with the rise of electronic payments, remittance data often arrives separately, be it via email, electronic data interchanges (EDI), or third-party web portals.

Not only do payments and remittance data typically come separately, but there may also be a significant lag between them., Remittance data in some cases is sent days or even weeks after the payment is received. The combination of separation and delay intensifies the challenge of manual cash application. The more different remittance data formats are involved – and the more errors, such as missing or incorrect details – the more effort is needed in matching. 

A payment amount discrepancy occurs when the amount paid differs from the invoice amount. Common causes include incorrect payments, payment discounts, disputed charges or a single payment covering multiple invoices. 

Unresolved differences create an additional need for manual reconciliation and posting. Unidentified differences may also impact financial reporting validity and any invoice write-off decisions.

Innovation in accounts receivables

Thanks to advances in technology, cash application need not be nearly so laborious.

Electronic invoicing is a solution that combines electronic invoices with payments by allowing companies to invoice customers via an online platform. This enables more efficient collection across multiple payment types.

The invoice information is already attached to the payment and is received by the company as an automatic cash application file. Electronic invoicing has the additional benefit of helping to shift customers’ payment types to the preferred method, typically automated clearing house (ACH). From the customer’s perspective, they gain the convenience of being able to view, download, dispute and pay invoices through a secure web portal.

Artificial intelligence (AI) and machine learning (ML) are also easing the burden of manual cash application. Automating the cash application process can reduce human errors, enable the reallocation of resources to more value-added projects and lower operating costs.

AI and ML consolidate data from multiple sources. Alone, such data provides limited value, but AI enriches the data which is then used to match payments and remittance data with open receivables. ML identifies patterns and behaviors, continually improving match rates over time.

The ability to automate the end-to-end cash application process significantly reduces the manual effort required by companies. This leads to greater visibility on the company’s cash position and the ability to optimize working capital.

The future is now

Treasury management is undergoing a digital transformation. Innovations are creating more efficient, smarter, and integrated treasury operations. The shift to automation is ultimately expected to see treasury operations become a more strategic partner, enabled to pro-actively deliver value-added input as they shift away from manual tasks.

At Citi Private Bank, we believe that now is the time to embrace these advancements. Whether step-by-step, or through a complete operational overhaul, businesses can potentially enhance their cash flow while reinvesting time and energy in their core businesses.

To learn more about these issues, please contact your Private Banker or Treasury Management Sales Specialist.
Treasury management

Treasury management

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