IDC TECHNOLOGY SPOTLIGHT Sponsored by: Bill.com

Intelligent Accounts Payable: A Look into the Future May 2019

Written by: Kevin Permenter, Research Manager, Enterprise Applications

Situation Overview Every business must manage two essential money functions: money coming in (sales revenue/accounts receivable [AR]) and money going out (accounts payable [AP]). In today's fast-paced global business environment, successfully managing the AP process is essential. AP is an important part of the relationship between clients and vendors. Poor service in terms of late or incomplete payment can damage relationships with key suppliers and clients. As such, the AP function impacts a customer's experience with a brand. The AP function can be complex and fraught with inefficiencies for companies of all sizes. During IDC's interactions with AP professionals, the following issues were top of mind:

» Manual processes. Today, thousands of companies of all sizes still have overly manual and complex AP workflows. As a result, these processes become exceedingly inefficient (consuming precious resources and delaying approvals), with a multitude of errors and limited fraud detection capabilities. Moreover, manually driven processes within AP can lead to inflexibility and a lack of agility, which can be extremely harmful to a company's ability to maneuver in the increasingly dynamic digital economy.

» Resource constraints. In many growing companies, AP professionals are being asked to process greater transaction volumes with the same resources. This puts unbelievable strain on the bandwidth of AP professionals, especially in fast-growing companies, often leading to heightened chances for errors, missed invoices, miscommunication, and supplier issues. One of the most pressing issues that strike at the imbalance between staffing and transaction volumes is the presentation of duplicate invoices, which can quickly lead to overpayment.

» Lost discounts. Companies with inefficient AP processes often lose opportunities to take advantage of early payment discounts. These discounts can positively impact the organization's cash flow and represent an opportunity for the AP function to contribute directly to the company's bottom line.

In today's fast-paced business environment, successfully managing the accounts payable (AP) process is essential for most organizations. AP is an important part of the relationship between clients and vendors — and poor service or incomplete payment can damage these key relationships.

KEY STATS » Approximately 80% of end users' time is

spent on lower-level AP tasks such as invoice matching, verifying general ledger transfers, and exception resolution.

» Nearly 37% of companies indicated that at least some of their invoices are still processed manually.

WHAT'S IMPORTANT Accounts payable is beset with manual processes and is fraught with inefficiency and human error. Intelligent accounts payable solutions can streamline and simplify the entire process.

AT A GLANCE

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IDC TECHNOLOGY SPOTLIGHT Intelligent Accounts Payable: A Look into the Future

The Growing Challenge of AP

Accounts payable is becoming more complex given budget restrictions, looming fraud threat, and changing regulations. Unfortunately, AP remains mired in legacy processes and antiquated tools. Data from the most recent IDC SaaSPath survey reveals the following regarding the current outdated state of the average AP process:

» The average organization has six people or less devoted to processing invoices.

» 50% of respondents would describe their invoice management process as "mostly spreadsheets."

» Nearly 37% of companies indicated that at least some of their invoices are still processed manually.

AP is a complex function that demands coordination between procurement, finance, supply chain, and legal. As a result, the AP process can be fraught with inefficiencies and pitfalls, including the following aspects:

» Lack of data visibility. Without visibility, organizations struggle to accurately know how money is being processed. In certain companies, the complex nature of AP and the often still manual AP process make it exceedingly difficult to gain visibility into transactions, delivery dates, and payments.

» Prevalence of human error. Unfortunately, the AP process is highly dependent on human beings who are not perfect and who make mistakes. Common mistakes include overpayments because duplicate invoices are paid twice. Without the right tools in place, many AP managers are overly exposed to this type of error.

» Lack of exception management. For AP departments, dealing with exceptions can be extremely time consuming. Finding the source and extent of the exception (i.e., calculations, addresses/fiscal data, duplications) can take precious time away from AP clerks and create a bottleneck within the AP department.

» Overreliance on manual processes. AP managers are spending a massive amount of time looking for specific invoices, matching those invoices, finding the appropriate general ledger (GL) codes, updating spreadsheets, and conducting other nonvalue-added activities.

Technology That Simplifies AP The growing complexity of AP management means solution providers must build software that simplifies and streamlines the everyday for AP professionals. Solutions with advanced intelligence tools provide end users with the ability to quickly manage information while ensuring invoice management efficiency.

AP workflows are quickly changing as part of digital transformation initiatives. This shift will also bring forth a new chapter in the evolving story of intelligent AP software applications, which will be characterized by the technologies shown in Figure 1.

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IDC TECHNOLOGY SPOTLIGHT Intelligent Accounts Payable: A Look into the Future

FIGURE 1: Technology Driving Intelligent AP

Source: IDC, 2019

While the number of areas where artificial intelligence (AI) can disrupt the applications within accounts payable processes is expanding every day, the first applications that AI will affect will be data-heavy repetitive tasks that weigh down the AP process in terms of agility, accuracy, and efficiency.

Current Use Cases of AI in Accounts Payable

Roughly 80% of end users' time is spent on lower-level AP tasks such as invoice matching, verifying general ledger transfers, and exception resolution. Artificial intelligence is being used to automate many of these lower-level tasks — freeing up valuable AP organizational resources to focus on higher-level strategic tasks. Table 1 describes a few of the AP use cases where AI is rapidly finding its footing.

Optical Character Recognition (OCR)

• One of the major pain points for AP managers is dealing with the mountain of paper invoices. It can be tedious and time consuming to enter invoices manually. Also, the information on invoices can be used (if efficiently processed) to drive real cash flow and forecasting insights. OCR is being used by businesses to capture the value of information left on invoices and streamline the process.

Machine Learning

• Recently, companies have turned to structured machine learning to speed up/streamline key financial processes, including AP automation, invoice reconciliation, and tax compliance. In addition, early adopters of machine learning have been able to eliminate a large amount of time spent on manual tasking while decreasing error rates.

Robotic Process Automation

• RPA software entities are pre-programmed to handle repetitive tasks such as compiling data from various sources into a single report or refreshing an analysis with the latest data. AP is well suited for RPA applications due to its high number of rules-based, manual activities. RPA software entities, when applied correctly, excel in the high-volume transaction environments that are inherent to accounts payable.

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IDC TECHNOLOGY SPOTLIGHT Intelligent Accounts Payable: A Look into the Future

TABLE 1: AI-Driven Use Cases for AP

Invoice process automation

Invoice processing can be a tedious task of receiving invoices and logging invoices into the ERP system by manually looking up the specific general ledger codes or managing permissions for specific roles. Artificial intelligence is being used to automate these aspects of invoice processing, drastically reducing the time spent by AP managers within this workflow.

Auditing invoices and payments

AP auditing is very often a highly manual process that can be painful without the right tools and controls in place. However, AI and machine learning are being leveraged to match receipts, identify transaction exceptions, and analyze behavior patterns.

Data analytics AP professionals must be able to accurately account for and provide detailed information on hundreds of transactions. AP professionals need to both verify and analyze these transactions for relevant reporting metrics, business insights, and compliance. This information may come in a variety of formats and sources, and the amount of this type of information is increasing daily, rapidly making the task of finding relevant business insights extremely daunting.

Payment fraud AP fraud schemes such as false invoices and check fraud are major issues for AP professionals, and they are difficult to mitigate because of the large amount of data and the speed at which the data is moving. Self-learning algorithms can be deployed to identify and stop exception issue AP transactions. Further, the self-learning software algorithm can home in on AP anomalies through pattern detection.

Source: IDC, 2019

Human Impact of AI

Artificial intelligence is set to profoundly impact AP in the coming years. As a result, we need to understand the ways that AI will change the behavior of the people who interact with the technology daily. To address the most profound changes that AI will drive in the near-term future, organizations need to do the following:

» Create balance between automation and control. Financial professionals are generally excited about the potential of artificial intelligence. However, there is still a desire to maintain control and transparency within the system. It is imperative for AP software vendors to provide a detailed mapping of the AI algorithm to show AP managers the steps behind the results. Also, it will be important for AP software vendors to provide scoring (i.e., invoice matching likelihood score) to allow users to configure their tolerance for AI-driven automation within a given task.

» Change skills. Currently, the skill set is skewed toward analytical capabilities, but as AI software takes away lower-level tasking, AP professionals will need to be able to assess and communicate the strategic aspects of the invoice information. This emphasis on strategy is a departure from the traditional staffing priorities and job roles within AP. Also, the introduction of AI/machine learning AP managers may require AP professionals to incorporate more software programming skills to manage the various machine learning entities streamlining their AP tasks.

» Reevaluate head count. The introduction of AI may allow businesses to scale up without adding to their head count, which could vastly improve operational efficiency. In these scenarios, AP professionals run the risk of being overly dependent on AI/machine learning, exposing themselves to risk if the system crashes.

Artificial intelligence is set to profoundly impact AP in the coming years.

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IDC TECHNOLOGY SPOTLIGHT Intelligent Accounts Payable: A Look into the Future

AI Challenges/Limitations

While software vendors and service providers are moving rapidly into artificial intelligence, several challenges remain for AI before it can reach its full potential, including the following:

» Data issues. Artificial intelligence algorithms (machine learning) require a tremendous amount of data for them to approach the effectiveness of even a novice AP professional at any task. Many vendors have developed algorithms but don't have the depth and breadth of data to reach sufficient accuracy levels for accounting tasks such as invoice data extraction and matching.

» Specialization issues. Machine learning applications become very good at doing one task, which is a positive and a negative. The negative side is that the artificial intelligence application still needs help making connections from one task (i.e., invoice matching) to another related task (i.e., fraud detection).

» Transparency issues. Many accounting end users have expressed frustration with trying to understand how/why their AI technology enables tools to reach conclusions. This lack of transparency within some AI-enabled accounting applications on the market can make it difficult for AP professionals to build trust in the system and may result in continuous reviews and rework.

Future Trends in AP Many AP professionals are optimistic about the future of accounts payable. It is an area that is ripe for process improvement and automation, which will greatly impact the day-to-day grind for the AP professional. What will AP look like in the coming years? The following trends are set to shape the future for AP processes:

» Convergence of adjacent workflows. The traditionally siloed nature of financial functions such as accounts receivable, procurement, expense management, and accounts payable is rapidly changing. In the next few years, we will see these walls break down, allowing for more coordination, collaboration, and communication among these financial functions. As such, decision makers will have a much more holistic view of a company's financial position in order to make better strategic decisions. This convergence will occur in a few key areas over the next five to seven years, including:

■ Combining accounts payable and accounts receivable. Combining AP and AR provides financial executives with a more holistic look into the company's cash position, which is essential to budget forecasting more accurately and effectively. Also, in cases where a company is both supplier and customer, having visibility into both sides of the transaction can lead to more effective negotiations.

■ Understanding AP and procurement. Understanding the company's entire spend profile (including direct and indirect spend as well as AP) allows for better decision making regarding inventory management, supplier management, and other purchasing issues.

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IDC TECHNOLOGY SPOTLIGHT Intelligent Accounts Payable: A Look into the Future

» Increasing embedded intelligence. IDC predicts that by 2021, 90% of new packaged enterprise applications will have embedded decision architecture that automatically detects and evaluates conditions and makes decisions about how to respond. AP vendors must work to embed intelligence within the business workflows (cash management, expense management, and inventory management) to unleash the full power of artificial intelligence. AP vendors are using embedded intelligence to guide decision making and automate lower-level tasking within the applications. IDC expects this trend to continue and to be a key factor in determining market positioning among financial application vendors in the future.

» AP evolving into a profit center. Companies are quickly realizing the potential for AP modernization not just to increase operational efficiency but also, in some cases, to help improve profit margins. AP has the potential to improve profitability via early payment discounts and card rewards/rebates, which can be significant over time. Additionally, implementing AI within the AP process can positively impact working capital, which can be used to fund internal growth efforts (i.e., increasing sales/marketing campaign, international expansion).

» Further consumerization. The financial workforce is becoming more tech-savvy every day. End users are looking for applications that fit their business way of life better and provide a more intuitive user experience. Financial applications are becoming more social, mobile, and conversational. Simply put, end users are looking for a user experience that is increasingly consumer technology oriented.

» More emphasis on ecosystem. The AP management process is best when it is integrated with enterprise resource planning (ERP), procurement, supply chain management (SCM), and customer relationship management (CRM) systems. AP vendors must be aggressive in building out their partner ecosystem to include other related enterprise applications. Specifically, it is essential for vendors to utilize application programming interfaces (APIs) to create prebuilt integrations that streamline the data flow between systems.

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IDC TECHNOLOGY SPOTLIGHT Intelligent Accounts Payable: A Look into the Future

How to Get Started More and more companies are choosing to implement AI into their AP process to capitalize on the benefits mentioned previously. However, the implementation process is not without its challenges. Figure 2 illustrates some key steps in the journey toward optimizing workflows by incorporating intelligent AP.

FIGURE 2: Journey to Intelligent AP

Source: IDC, 2019

Begin by looking inward. Before you choose to implement an intelligent AP solution, take the opportunity to do some self-reflection. The following are a few key questions to ask regarding the internal resources and processes:

» What are some of the issues we would like to resolve by adding intelligence?

» Are the issues technology related or process related?

» How will processes need to change to adopt this technology?

» What are our internal support resources and capabilities?

» How should we define success for this implementation?

» Which internal stakeholders should we include in the evaluation processes?

Begin by looking inward

Select the right partners

Take a measured approach

Assess post-implementation success

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IDC TECHNOLOGY SPOTLIGHT Intelligent Accounts Payable: A Look into the Future

Select the right partners (internal and external). The journey to a more streamlined AP process via an intelligent AP solution involves developing a strategy and plan for the implementation of an AP solution. This includes doing the due diligence to find the right intelligent AP vendor. The following are a few key questions to ask regarding the AP vendor:

» Does the vendor have experience with our type of product, service, and company size?

» Can the vendor show examples of specific areas where its technology utilizes AI/machine learning to support the AP process?

» Has the vendor shown a commitment to supporting current features with AI and utilizing AI to introduce new features?

» Can the vendor show a hands-on demo with our organization's "live/real" data to demonstrate the benefit to the business?

» What is the vendor's strategic AI/machine learning investment outlook for the next three to five years? Why? How will that change and enhance our business?

Take a measured approach. Some organizations, once exposed to the potential of AI/machine learning, will seek to implement intelligence throughout the entire AP process immediately. However, the more common approach is to implement AI in steps or stages. The following are a few key questions to help organizations determine those steps:

» What are some of the most manual processes related to AP within our organization?

» Which areas will make the most impact on the operational goals of the AP department?

» Which processes would take the most effort (time, resources, etc.) to change?

» Which processes have the biggest internal capabilities gap in terms of skills or tools?

» Which areas might prioritize control over automation (i.e., large payments or new payment methods)?

Assess post-implementation success. In many ways, the success of any SaaS implementation hinges on what happens after the implementation is up and running. This is where change management takes center stage and the people side of AP management becomes essential. The following are a few key questions to ask regarding the post-go-live phase of AP implementations:

» Do we have a strategy to encourage 100% adoption among AP employees?

» Have we communicated the initial impact on success metrics?

» Do we have the right amount of training for employees to master the new features within the AP system?

» Are we communicating the purpose and benefits of the system change to AP employees?

» Have we aligned existing policies and procedures to enable the adoption of the new workflows?

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IDC TECHNOLOGY SPOTLIGHT Intelligent Accounts Payable: A Look into the Future

Considering Bill.com Bill.com is a digital business payments company with a network of 3 million members, processing over $60 billion annually. Bill.com helps businesses and accounting firms and their clients pay and get paid quickly and save time typically spent on accounts payable and accounts receivable. The Bill.com platform integrates with accounting technologies such as Oracle NetSuite, Sage Intacct, QuickBooks, and Xero. Bill.com has many partnerships with large accounting firms and large U.S. financial institutions. The Bill.com cloud-based Intelligent Business Payments Platform automates, streamlines, and controls the payments process, saving more than 50% of the time typically spent on payment tasks, according to the company.

Bill.com counts its use of artificial intelligence and machine learning to streamline payments, guard against fraud, and reduce cumbersome data entry among its advantages. The platform is designed to:

» Eliminate data entry. Bill.com has made investments into streamlining the often arduous data entry and data management aspects of AP. Currently, Bill.com uses artificial intelligence to extract key data fields (vendor name, amount, invoice date, invoice number, due date, and account number) from an invoice and input them into a bill in real time. Bill.com will soon be using artificial intelligence to extract line and field data from supplier invoices, including purchase order number and product quantity. This capability sharply reduces the burden on AP professionals.

» Streamline payments. Bill.com leverages the power of AI to streamline payments by automatically providing the accounting treatment, approval routing workflow, and stakeholder alerts for every bill. Bill.com also allows companies to track audit trails and payment status for multiple payment types such as domestic ACH, international wire, and virtual card.

» Protect against human error. Bill.com uses artificial intelligence to intercept and recognize human error. Currently, users are informed if there is a duplicate bill or if they are about to make a duplicate payment.

» Guard against fraud. Bill.com uses AI to protect customers from fraud by assessing multiple risk factors at the transaction level. The technology also monitors a wide variety of internal and external data sources to prevent fraudulent organizations from transacting in the Bill.com payment network.

» Utilize pattern recognition to streamline mundane tasks. In the near future, the AI in Bill.com will become even more responsive to human behavior by suggesting best practices when using the system. For example, Bill.com will apply pattern recognition to proactively suggest user roles and access levels as well as create those roles and permissions within the system.

Challenges

Bill.com has made a commitment to leveraging advanced technology such as AI to alleviate the pressure of today's complex, fast-paced business. Bill.com must continue working to position itself to capitalize on the growing popularity of AI and machine learning within the market for repetitive accounting tasks such as invoice capture and invoice matching.

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IDC TECHNOLOGY SPOTLIGHT Intelligent Accounts Payable: A Look into the Future

Conclusion There is no area within financial applications that won't be significantly altered by artificial intelligence in the coming years. However, AP workflows are quickly changing as part of broader AI-led digital transformation initiatives. AP departments are rapidly adopting new technologies to cope with the new market dynamics. As digital transformation continues to evolve within AP functions, the importance of AI/machine learning will increase accordingly. In addition, as AP becomes more and more complex, AI will continue to be the center of attention for both software vendors and their customers.

About the Analyst

Kevin Permenter, Research Manager, Enterprise Applications

As a Research Manager with IDC's Enterprise Applications team, Kevin M. Permenter provides insights and intelligence across multiple areas including enterprise resource planning (ERP), order management, financial applications, and project and portfolio management. He assesses the interplay, challenges, and trends regarding various enterprise application deployment models like mobile enterprise applications and cloud models. He also develops and delivers his views, opinions, and analysis on the dynamics and evolution of this complex technology ecosystem.

The content in this paper was adapted from existing IDC research published on www.idc.com.

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