A New AI Series on Payables Place
The power of artificial intelligence (AI) is undeniable. Its impact and influence are revolutionizing the Accounts Payable (AP) and Business-to-Business (B2B) payments automation market. According to research from Ardent Partners, AI will soon be ubiquitous in this sector, offering unparalleled efficiencies and capabilities. The transformative possibilities of AI will drive innovations in invoice processing, payment automation, fraud detection, and overall financial management, streamlining enterprise operations and improving business decision-making.
In view of these advancements, Ardent Partners is launching a special “AI in Action” interview series. Our “AI in Action” series represents an opportunity for our Chief Research Officer, Andrew Bartolini to sit down with senior executives at the ePayables solution providers that are focused on AI now and in the near-term and use these discussions as an opportunity to share their company’s focus on, expertise in, and vision for AI within the AP industry.
Today’s AI in Action profile features a conversation with John Wallace, CEO of Documation.
AB: Good afternoon John, tell our readers a little bit about yourself.
John Wallace, CEO for Documation.
I am the Founder and CEO of Documation, a software development company focusing on finance process automation. Documation delivers leading-edge, powerful, and robust solutions across all industries, with a level of customer care and support that sets us apart from our competitors. With a wealth of experience in innovation, leadership, and consultancy, I am a recognized thought leader in the field of finance process transformation, with a particular focus on P2P and accounts payable. I also provide consultancy and non-executive input to organizations across a range of industries and deliver keynote talks at conferences and seminars on the practical application of AI, machine learning, and software robots in finance.
AB: Where are the biggest opportunities for AI to improve accounts payable and B2B payment efficiencies and productivity?
JW: At the start of the AP process, AI is the key to rapid, accurate, and touchless capture of invoice data — our AI-based processes achieve fantastic read rates which are further improved by machine learning over time. By using built-in adaptive AI, even difficult domain-specific problems, such as data capture, can be solved, meaning this is brilliant tech for every industry situation.Further downstream, AI-powered invoice matching and pairing takes the touchless concept to the next level saving thousands of man hours whilst improving accuracy.
Together, AI-powered data capture and invoice matching are the key to the ultimate goal of straight-through invoice processing to supplier payment without human intervention. Smart use of AI reduces costs and helps identify opportunities for early payment discounts and reduce or eliminate late-payment penalties, which of course helps improve critical supplier relationships.Straight-through, touchless processing is great, but only if the invoices are genuine. With the continuing rise in invoice- and payment-based fraud, AI has a crucial role in protecting the organization by detecting fraud before it happens — and using machine learning to drive out false negatives.
AB: How do you view your customers’ (and prospective customers’) AI attitudes?
JW: Once they see the power AI provides to reduce costs and to allow finance teams to focus on more profitable work, customers are overwhelmingly in favor of AI. There is a caveat though — savvy customers know that AI is not flawless, and invoice payment is a high-stakes game. We’ve all seen the results of over-enthusiastic predictive text, for example. And the stigma of overt issues means that customers want the security of knowing what AI is doing and that they can override where needed. For this reason, we see data analytics as being a crucial part of the AI toolset, along with the ability to force human inspection or confirmation of AI decisions where needed.
Put another way, on one side, many customers are looking for the magic bullet and think AI will automate all their processes, and on the flip side, there are the customers who are nervous about touchless processes and want the “human” element of control. The key is balance — allowing the customer to choose the right balance of streamlining processes with AI, but with visibility and control at every stage. Fear of the unknown plays a part in customer attitudes, so discussing both the power and limitations with them and taking time to understand the challenges and concerns they are facing ensures a solution that really works for the customer and is therefore, an essential part of our communication.
AB: What are the leading AI subsets (e.g., machine learning, natural language processing, deep learning, etc.) with the biggest impact on accounts payable/B2B payment solutions? And why?
JW: Subsets of AI widely used in AP and payments to achieve touchless processing include, natural language processing, statistical pattern recognition, and neural networks such as deep convolutional neural networks. These technologies combine to achieve the high success rates we see in capturing and processing invoices through to payment. Domain-specific, feature-engineered machine learning is also widely applied, partly to improve AI results but also to help users achieve fast and accurate processing in a wide range of applications, including order and invoice coding, distribution, authorization, and fraud detection.
Expert systems are AI systems designed to mimic human decision-making by applying rules and knowledge-based inference. These are widely used for applying authorization protocols, delegation of authority, and supplier selection. Robotics is a field of AI focused on creating autonomous or semi-autonomous machines that can perform tasks in the real world. In state-of-the-art systems, software robotics play a fundamental part in virtually every process, replacing human effort and gaining faster and more accurate results.
Fuzzy logic comes into play in many areas, including for finding documents, identifying the correct GL codes to use, directing queries to the correct recipients, or providing automated responses to suppliers.
AB: How are you ensuring the accuracy and reliability of customers’ AI models (AI data output)?
JW: AI is a brilliant attribute for our systems, but an attribute that must be controlled, supervised, and continuously improved. The first key is to provide comprehensive business intelligence and analytics to identify where AI is succeeding and where it can be improved. In addition, monitoring and opportunities are built into processes so that where accuracy is in doubt, the Finance team can review, challenge, and override.
AB: How do you plan to support your AP clients if/when an AI skills gap exists?
JW: AI is continuously evolving, and our product roadmap reflects this evolution through constant research and evaluation of new techniques and technologies so that where there is genuine benefit to finance teams, enhancements can be incorporated and made available to customers.
AB: Where do you see AI going within the ePayables (AP automation) market over the next five years?
JW: Some aspects of AI already incorporated into processes, such as data capture, are relatively mature. The goal will be to take advantage of incremental improvements and consequent performance gains. Other aspects, including generative AI, are at a much earlier stage. It is these technologies which will make the greatest difference particularly in procurement, purchasing, and in rapid delivery of meaningful information to stakeholders like management teams, auditors, and suppliers.
AB: I appreciate your time today!
JW: Thank you.
