OCR is not a silver bullet. Four reasons why it should only form part of your AP automation strategy - Photo by Towfiqu barbhuiya on UnsplashEconomic uncertainty has expedited the need for businesses to embrace digital transformation at all levels. Finance teams have an important role in reducing manual workflows, increasing efficiency and cutting costs. When run efficiently, they drive strategic leadership. It, in turn, supports the rest of the C-Suite with key decision-making that helps navigate the changing economic environment.

The importance of alleviating the accounts payable (AP) workload for the finance team cannot be understated. According to research by the Institute of Financial Operations and Leadership (IFOL), over half (56%) of finance professionals spend over ten hours a week processing invoices and supplier payments. It is time which could be spent focusing on strategic initiatives that will drive the business forward.

Optical Character Recognition (OCR) technology often forms part of a finance team’s invoice processing tools. It works by using automation to extract readable data from invoices into machine-coded text. For industries that deal with heavy loads of data processing, it is a tool that has freed up time from keying in data, enabling them to focus on less repetitive and tedious tasks.

However, using OCR to inform the entire AP automation strategy can only take the finance team so far on its digital transformation journey. Its accuracy is limited and only automates a sliver of the range of AP tasks completed by finance departments. Instead, businesses need to leverage AP automation tools that remove manual processes across the whole suite of tasks, from supplier onboarding to processing and reconciling payments.

Below are four reasons your AP workflows should not rely solely on OCR.

1. Accuracy is limited

OCR is only accurate 85%-90% of the time. This partial accuracy means that data extraction of invoices isn’t fully automated and will still need an element of manual processing. CFOs must look at either costly verification services or use staff resources to review and verify the accuracy of extracted data from all invoices.

On top of taking time away from other projects to perform tedious manual checks, there is still the risk of data being imported into ERP software inaccurately due to human error. It also creates a clear drawback for those needing access to real-time data, as processing invoices with partial automation isn’t instant.

These inaccuracies can lead to suppliers being paid late or the wrong amount and thus damaging relationships. It is something which a fifth (21%) of AP teams have experienced due to processing challenges. It creates a further administrative burden on the finance team and inaccurate forward-looking forecasts that can impair decision-making and cash flow visibility.

2. OCR’s legacy tech cannot keep up with newer invoicing types

Invoice formats vary from business to business. OCR technology is predicated on a one-size-fits-all format. It often struggles to read and extract relevant data on newer invoicing types that may not be laid out in a traditional format or style. This further undermines OCR’s accuracy and could create compliance issues, such as taxes if values are not extracted correctly.

OCR is relatively simple. It tries to extract the information it’s programmed to capture. It isn’t capable of understanding an invoice’s underlying data or context. Its accuracy and capabilities can be enhanced to accommodate different invoice types when combined with machine learning.

Machine learning goes beyond data extraction by analysing the structures of multiple invoices and looking for patterns to distinguish between different components, such as numerical addresses, total values, and due dates.

When the two technologies work together, it can create a robust system for invoice capture, making OCR a more intelligent model that can handle a wide array of invoice types, extract data as values, and place it into the correct fields for posting on ERP systems.

3. OCR doesn’t support the onboarding of new suppliers

Many CFOs believe that AP automation begins and ends with OCR. However, it only fulfils one of many supporting AP activities.

One of the most critical elements of AP is onboarding new suppliers and ensuring their data is accurately collected and entered across all relevant systems. It is the first touch point new suppliers will undergo with purchasing companies, and it’s critical to provide them with a positive experience to build a stronger overarching relationship where each party can be vested in the other’s success.

Automated supplier onboarding activities should include verifying bank accounts, collecting tax documentation and contact information via a self-serve platform. It renounces the need for AP teams manually process this information. It, therefore, frees up time to focus on new innovations and growth strategies.

4. OCR cannot detect fraud

The biggest risk in solely using OCR is its inability to detect fraud. Over 80% of finance leaders believe fraud and risk exposure to be among the biggest AP challenges. OCR alone cannot solve this key pain point.

Not using fraud detection for your AP workflows creates the risk that company funds may become misappropriated. This is due to false supplier invoices or legitimate invoices being tampered with across the AP lifecycle, such as during the approvals process or at the time of payment.

The most common perpetrator of payment fraud is manual processes. It is more likely to occur if businesses undertake disconnected manual processes that require input from multiple staff members.

The risk of setting up fraudulent invoices for payment can be minimised by using AP software tools to detect unusual patterns, show where a threat has been identified, automatically open cases, and notify team members.

Creating a fully comprehensive AP automation strategy

When tasked with turning their hand to multiple facets of AP with high levels of accuracy – including onboarding suppliers, raising purchase orders, executing payments, reconciling and reporting – it is clear that OCR alone is not enough. It only serves one part of the AP lifecycle. When AP complexity is compounded by the need to be increasingly agile amidst economic pressures, finance teams need a fully comprehensive strategy that reduces manual interference.

To truly optimise efficiency and resources, finance leaders need to be actioning a broad range of solutions that can solve pain points across the entire AP function. Businesses can use the time saved with automation to become more productive, increase visibility and control, and ultimately, be fit to scale.

Tipalti from March 2022Tipalti comes from the Hebrew expression for “We handled it.” Tipalti is the only company handling both Accounts Payable and Global Partner Payments workflows for high-velocity companies across the entire financial operations cycle: onboarding and managing global suppliers, instituting procurement controls, streamlining invoice processing and approvals, executing payments around the world and reconciling payables data across a multi-subsidiary finance organisation.

Tipalti enables high-growth companies to scale quickly by making payables strategic with operational, compliance, and financial controls. Companies can efficiently and securely pay thousands of partners and vendors in 196 countries within minutes. Thousands of companies, such as Amazon Twitch, National Geographic, Business Insider, Hopin, Cazoo and Time Out use Tipalti to reduce operational workload by 80 percent and accelerate the financial close by 25 percent, while strengthening financial controls and spend visibility.

For more information, visit tipalti.com.


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