Moderated by Emily, Digital Transformation Consultant at Hyperbots
Emily: All right. Hello, everyone. This is Emily, and I am a digital transformation consultant at Hyperbots. Today, I am very glad to have Jaspuneet on the call with me. Jaspuneet is the head of finance at AB Industry and has been a strategic advisor to different organizations. Thank you so much, Jaspuneet, for taking the time to speak with us today. It’s great having you on board.
Jaspuneet Mohie: Thank you for having me.
Emily: So, Jaspuneet, we are looking forward to discussing punch-out technology and its role in modern procurement processes. Let’s dive into some of the key topics. Can you start by explaining what punch-out technology is and how exactly it integrates with procurement systems?
Jaspuneet Mohie: Sure. Punch-out technology allows buyers to access a supplier’s online catalog directly from their procurement system. When a buyer needs to make a purchase, they “punch out” to the supplier’s site, select items, and then “punch back” the cart into their procurement system. This integration ensures that purchase details are accurately captured and streamlined throughout the procurement process.
Emily: Got it, understood. How does punch-out technology benefit high-volume, routine purchasing for organizations?
Jaspuneet Mohie: For high-volume purchases, punch-out technology offers several benefits, including streamlined purchasing processes, real-time catalog updates, and reduced manual entry errors. It helps organizations maintain procurement compliance and ensures that buyers have access to the most current pricing and product information directly from suppliers.
Emily: Got it. What are some common challenges associated with implementing punch-out technology in an organization’s procurement process?
Jaspuneet Mohie: Common challenges include integration complexity, as setting up and maintaining punch-out catalogs can be resource-intensive. Vendor adoption can also be an issue, as not all suppliers support punch-out technology. Additionally, system compatibility and the potential costs associated with implementation and maintenance are notable concerns.
Emily: Understood. In your experience, how important is supplier participation to the success of punch-out technology?
Jaspuneet Mohie: Supplier participation is crucial for the success of punch-out technology. The effectiveness of the system largely depends on whether suppliers support punch-out and maintain up-to-date catalogs. Without broader supplier adoption, the benefits of punch-out technology can be limited, and organizations may need to rely on alternative procurement methods.
Emily: Got it. Just out of curiosity, are there any specific industries or types of organizations where punch-out technology is particularly beneficial?
Jaspuneet Mohie: Punch-out technology is particularly beneficial in industries with high-volume and routine purchasing needs, such as manufacturing, healthcare, and government sectors. These industries often require efficient and accurate procurement processes, making punch-out technology a valuable tool for managing large-scale purchases.
Emily: Understood. How do you see punch-out technology evolving in the future, especially with the rise of new procurement technologies?
Jaspuneet Mohie: Punch-out technology is likely to evolve with advancements in integration capabilities and user experience improvements. As new procurement technologies and digital platforms emerge, Punch Out may become more integrated with other systems, like AI-driven procurement tools and analytics platforms. This evolution will enhance its functionality and potentially address some of its current limitations.
Emily: So, what are the alternatives to punch out technology, and in what scenarios might they be more suitable?
Jaspuneet Mohie: Alternatives to punch out technology include direct integration with suppliers’ ERP systems, hosted catalogs, EDI, and procurement marketplaces. Direct integration might be more suitable for complex or less frequent purchases. Hosted catalogs can be used when real-time catalog updates are less critical. EDI is useful for sending purchase orders electronically, while marketplaces provide a centralized buying experience for diverse product ranges.
Emily: Understood. How can organizations assess whether punch-out technology is the right fit for their procurement needs?
Jaspuneet Mohie: Organizations should assess their procurement needs by evaluating factors such as the volume of routine purchases, the level of supplier participation, integration complexity, and cost considerations. If high-volume routine purchases are a significant part of the procurement process and the supplier base supports punch out, it could be a valuable tool. Additionally, organizations should consider their existing technology infrastructure and whether punch-out technology aligns with their overall procurement strategy.
Emily: Got it, got it. Thank you so much, Jaspuneet, for sharing your insights on punch-out technology and its impact on the procurement process. Your perspective on its benefits, challenges, and future developments is invaluable. Thank you so much for joining us today.
Jaspuneet Mohie: Thank you for having me. It’s been a pleasure. Have a great day.
Emily: You too. Thank you.
Moderated by Emily, Digital Transformation Consultant at Hyperbots
Emily: Hello, everyone! This is Emily, and I’m a digital transformation consultant at Hyperbots. I am very pleased to have Jon on the call with me. Jon is a seasoned CFO. With experience in larger companies as well as startups and public companies. I’m so glad to have you on the call with us, Jon.
Jon Naseath: Appreciate it.
Emily: So the topic for today, Jon, is purchasing without purchase orders. This is an area that many organizations grapple with, and I’m looking forward to your insights. So let’s just dive into the 1st thing that I’d want to ask you is, what are the common reasons that you’ve observed? That leads to an organization, you know, to make purchases without using a purchase order.
Jon Naseath: Yup. A lot of times it comes down to using a purchase order may not be a key control, and it’s just an additional process. So they find ways to work around it if they need to. A lot of times. The ERP systems, whatever one you’re using, have complicated interfaces and so I’ve seen companies avoid not wanting to have to give everyone logins to those systems and looking for others. Well, they could be open to other ways. But that’s a key challenge to the system itself.
Emily: Got it. Can you provide examples of situations where you know bypassing the PO process might seem justifiable?
Jon Naseath: Well, I would argue that there are times when it is justifiable. I usually work and figure out where the threshold is. And so, if purchases are needed, they are below a threshold. There could be times when you decide as a company. We’re not going to do PO’s there. In those situations. What I usually do also is we’ll either provide a credit card for individuals for those smaller purchases that have a set limit to still control it or you could do kind of what we call a blanket PO for certain areas. So it’s not specified to a given vendor, but it allows them a defined budget that they can use within that function or project.
Emily: Got it, and any risks that you see associated with making purchases without a purchase order?
Jon Naseath: Well the purchase order itself is a tool, and I remember a situation where it was very difficult for projects and for different departments to understand how much budget they had, and they were constantly going over budget. And so we needed to find a way that enabled direct visibility to how much budget they had, and how much they were within budget to spend something and allow them the authority to control their own department or function or project budgets. In that example, we found that Pos could be a powerful tool because they’re already doing all this work to figure out the budgets and their projects. They want to feel like they own that budget so allocating that budget out into different POs for what the project says. Vendors are going to need, or for a blanket PO to catch. The remainder was a powerful tool.
Emily: Got it. And from your experience, Jon, how does the absence of a PO process affect vendor relationships and negotiation power?
Jon Naseath: Yeah so especially when there’s a large vendor or a strategic vendor you’ll negotiate terms, and there’s so much work that goes into establishing those contracts and all the terms around it. And so then opening up the PO, based on that contract, is a nice way to control and keep everything transparent and open. Now there are often situations where you might not use all of the PO, so it’s important to have visibility to how much is being used, and it’s not just purchase orders, but the purchase requests that then feed into those and then at the same time being able to see for vendor management how much available capacity is still on that old purchase order. For when you need to do the next project, and maybe you have to discuss it. Can we roll that over into the next purchase order that wasn’t used? Or is that money needed to be held back for the budget for another department?
Emily: Got it understood. And so how do you view the cost and complexity of implementing a PO system, particularly for smaller businesses?
Jon Naseath: Sure. I don’t know if it’s about the size, but also the operational maturity of the organization. You know, if you’re just starting. It’s not your biggest priority. You just have to get customers in the door and make sales or if you’re just in the process of scaling and you have tight you you feel like you’re in control of the spending. That’s happening. Then that’s fine. But when you reach that point where you, as an organization, are so big and so complex that you don’t know or have control over the demands of spending. And you people need to be able to, in different departments, own their budgets, instead of having kind of a centralized finance, be approving every spend as it goes out. The nice thing about pos is that kind of pre. It’s kind of a pre-approval for future spending. And so it’s allocating out budgets in an approved way so I’d look for the complexity when it becomes when you need a solution, and you’re looking for a way to control your spending. The whole process of that procurement process can be very helpful.
Emily: Got it makes sense. So, Jon, do you believe there is a you know. One-size-fits-all approaches to whether organizations should adopt a peer-driven process And why or why not?
Jon Naseath: I don’t think that there is just a 1 way. Many businesses are different. One example is you have recurring, spending that’s happening, or if all of your stuff is just transactional, and one-time spending there are also opportunities to do a lot of similar controls through different types of credit cards, and where you can get cash back from credit cards but especially with larger spends. You know, doing a purchase order, or purchase request process is a powerful way to do it. Again, I want to call out that concept of an open PO or a blanket PO for things that you. You can still allocate it to a department or a project, but then they can spend it against that blanket PO where it’s not exactly known how much it’s going to be. The other one, I’d call out, is for different utilities, or or recurring subscriptions. You might not need a Po, for, because you’re not getting an invoice, you’re just paying a recurring bill, but still creating that blanket open PO for your internal controls and budgeting can be helpful. You don’t need to tell the customer or the supplier about that PO but it’s just a way to control budgets.
Emily: Sure understood. And what alternative approaches can organizations take if they find a full peer-driven process? You know, too rigid or cumbersome.
Jon Naseath: Yeah again, it’s based on the size, the size, and the complexity of the organization. If you feel like you’re controlling it through your own active communication of people in real-time. Then that’s fine. It’s just when it becomes too complex. Like, I remember a situation where I had a product manager, set up a strategic planning workshop with one of his best friends who was a vendor, and they were amazing at doing what they were doing. It was an awesome strategy and marketing workshop over a few days. You know, they flew a large team in, and there were dinners that we thought they were paying for and I only got invited to one of the dinners. When I said that, we thought that this product manager was being paid by them. I attended one of the dinners, and I started talking to them at the dinner and realized that they were going to be charging us for everything back through that ended up being like 1.5 or almost 2 million dollars for their advisory consulting project that didn’t result in any transformational change that we did. So that was problematic. So avoiding those is kind of like spending. And just, it’s just a way of controlling spending is a nice way of thinking about it, and there can be. Usually, it gets put in place when something happens that shouldn’t have happened. Oftentimes, when I see it come into place it’s a way to tighten up controls.
Emily: Makes sense.
Jon Naseath: Sorry. One more point there. It’s oftentimes not the key control for Sarmeans, Oxley, or something. So it’s something that might not be required, for you know what accounting would push for but as , I think that as a finance leader is a very helpful tool from an FP and a perspective and again, just watching for where the demand is. That’s where it adds value.
Emily: Okay that’s pretty insightful. So in your opinion, what should organizations prioritize when deciding whether to implement a PO-driven process?
Jon Naseath: I like to look at finance from the perspective of a finance business partner, and so a lot of times where there are lots of departments or lots of projects that are all asking for money literally. The terms are purchase, request, and purchase order. So I remember one time sitting down with a product development team and an organization where we had many different teams doing lots of different development. And they all had requests and I sat down with them, and we did a lean 6 Sigma style process map and mapped out the current state. And then we looked at it and looked for waste in the process, and we looked at how we could optimize what was happening and through that process of discussing, how can we help these teams fix their purchase request problems. I wrote in the box on the future state diagram. I said, this is a purchase request, and you guys make a purchase request when you need money, and then that gets approved. And this is a purchase order, and when it’s approved becomes a purchase order, and then you get a spend. And they were like, Wow! That’s a great idea. We should do that all the time, and if I had just gone in from the beginning and said, Oh, your answer is, you need personal purchase orders, and let’s put it in place. I’m sure there would have been pushback, but when you approach your app, your question is like, When is it needed? And my answer is when your different departments and teams your business partners in the business are asking for support, getting the funding that they need. This is a nice way of helping them feel like they’re at least participants and have a process for requesting funds. That’s literally what it is.
Emily: Funny. So just one last question to summarize everything. Jon. you know AI is the birth of the town. So how can AI help automate the PO process?
Jon Naseath: Yeah. I think it’s exciting what AI will be able to do for it because a lot of you know, even if companies don’t have what an accountant might call a purchase, order, purchase, request, procurement process. Every company is doing procurement. Every company is figuring out how to buy things in their way. So the idea of taking that current state process and saying, Well, how can AI enable that procurement process in whatever way it is? Maybe there’s a future state where, based on different insights that AI can do, you can make it so that AI will be able to approve more of the purchase requests without needing so much manual approval or manual touches. And certainly, there’s a threshold where you have to have the manual touch and manual check. But I think that AI could alert for risks when it needs to be double-checked or I look at AI as providing a kind of that 1st sanity check on things. And then it’s good at identifying problematic areas. But overall, it should be able to simplify and expedite that purchase request process. You never want to end up in a situation where the business departments feel like they’re not able to spend money because they’re waiting on a PO. They’re waiting on a purchase request, approval. And so whether it’s helping the AI could help identify the risks related to that purchase request, or it could help identify threshold approvals where certain ones can just be approved without manual touches. I think of it similarly to how I mean just a parallel example. Similarly to how, when you do your taxes say you’re using TurboTax as an example, and you’ll come. You’ll prepare your taxes. Think of that as kind of quasi, like a purchase request, and then, when TurboTax, it will go through everything, and it will say, Oh, we don’t see any issues in this, and if there are issues we’ll support you in mitigating them. But we think this will be fine and I’m a Cpa. I’ll confess I still use TurboTax, advanced stuff for my accounting in different ways and I think that similarly AI could be used for purchase requests and purchase orders to do that risk profile and help the person who’s submitting it. Usually, it’s stupid, simple things that might be wrong or might not be appropriate in a purchase order. I think that AI can help identify those for the person submitting it so they can modify them if needed, and get everything to go through faster.
Emily: Got it. Got it. Thank you so much, Jon, for sharing your insights, you know it’s clear that a peer-driven process offers many benefits. It’s not without its challenges. So your perspective on finding a balanced approach and leveraging AI to streamline the process will certainly help organizations make more informed decisions. So thank you so much for joining us today. It was great having you.
Jon Naseath: Pleasure have a great day.
Moderated by Emily, Digital Transformation Consultant at Hyperbots.
Emily: Hi, everyone. This is Emily, and I’m a digital transformation consultant at Hyperbots. I’m very excited to have Mike Vaishnav join us on the call today. Mike is a CFO, consultant, and strategic advisor to many privately held businesses and organizations worldwide. The topic we’ll be discussing today is PR and PO approval best practices. To get started, Mike, I’d like to ask: What factors do you consider most important when setting up the approval process and approval thresholds for PR and PO approvals? Also, how do you determine the appropriate approval levels for different purchase values? Mike, could you also explain how departmental needs influence the approval authority matrix?
Mike: Sure. There are several factors required for setting up the approval matrix. First, the nature of the expenses is critical whether they are capital expenses, operating expenses, recurring expenses, non-recurring expenses, or strategic/critical expenses. These aspects require different approval matrices for each department. Second, consider the budgetary allocation: Is this expense budgeted or unbudgeted? If it’s already budgeted, then the department head can typically approve it for that specific department. However, if it’s unbudgeted or a high-value transaction, multiple levels of approval may be required. Let me give you an example. If an expense involves collaboration between two departments let’s say procurement and operations while also needing input from R&D for a new product introduction, executive approval might be required due to the strategic nature of the project.
For routine inventory purchases, the operations department can approve them if they are part of normal production. However, for something more critical like stocking up on a high-demand product where supply is limited, additional executive approval might be needed. The approval matrix also considers factors like transaction volume and frequency. For high-value, low-frequency transactions, more hierarchical approval levels are necessary. On the other hand, high-frequency, low-value transactions like utility bills can be approved at the departmental level. The company’s philosophy whether it favors centralization or decentralization also influences the approval process, as it determines how much empowerment is given to employees while balancing proper controls, risk management, and compliance. The critical factor is setting dollar thresholds: for example, transactions under $10,000 may require one approval, those over $100,000 might need two approvals and those over $500,000 could require three or more executive approvals. The size of the company and the nature of the procurement all play a role in setting up the approval matrix.
Emily: Got it. Mike, how do vendor threshold limits affect the approval process?
Mike: Vendor threshold limits help monitor and control total spending, manage vendor risk, and ensure compliance. Here’s a step-by-step breakdown: First, vendor threshold limits are essential for risk management. You need to evaluate whether you’re dealing with a new vendor or an already verified one. You should consider the value and volume of transactions with that vendor. Second, compliance is key. The audit trail, segregation of duties, and other controls help mitigate fraud and fund misappropriation. You also need to assess whether the vendor is strategic or critical. For example, if a vendor provides a product crucial to operations and there’s high demand with limited supply, you don’t want to delay approvals. Pre-authorized expenses for such cases help speed up procurement and avoid operational disruptions. For strategic initiatives like R&D, or where vendors offer significant discounts, having pre-approved spending limits ensures that opportunities aren’t missed due to lengthy approval processes. However, you should balance this by avoiding overstocking. Budget vs. non-budgeted expenses also play a role in vendor selection and approval.
Emily: Understood. How often should the approval authority matrix be reviewed and updated?
Mike: The approval authority matrix is typically reviewed annually, but it’s not limited to just that. Some companies review it quarterly or semi-annually, depending on their needs. There are other triggers for review as well: changes in corporate strategy, significant company growth, technology upgrades, market condition changes, or key personnel transitions. If a key employee who holds crucial knowledge leaves the company, a review might be needed to transfer knowledge and adjust the matrix accordingly. Overall, while annual reviews are standard practice, companies should remain flexible and review the matrix when significant changes occur.
Emily: All right, Mike. One last question: What role does technology play in streamlining the PR and PO approval process?
Mike: Technology plays a crucial role in automating workflows, ensuring compliance, maintaining audit trails, and customizing the approval process. Automation reduces manual intervention, which is used to involve paperwork or lengthy email chains with mobile technology, approvals can be done remotely, making the process much more efficient. Some AI-driven solutions integrate directly with the procurement system, allowing approvals without logging into separate platforms. AI can also enhance data analytics and reporting, providing instant insights without waiting for reports from the procurement or accounts payable departments. Moreover, technology simplifies vendor management. Vendors can upload invoices directly into the system, eliminating the need for manual data entry. As companies grow or introduce new products, technology ensures scalability and smooth migration to updated processes.
Emily: Understood. That was great. Thank you so much, Mike, for sharing your insights on PR and PO approval best practices. It’s always a pleasure having a conversation with you, and it was amazing hosting you today.
Mike: My pleasure.
Moderated by Emily, Digital Transformation Consultant at Hyperbots.
Emily: Alright. Hello, everyone! This is Emily, and I am a digital transformation consultant at Hyperbots. Today we are joined by John Silverstein, and we’ll be talking about strategies for matching in accounts payable. John is the VP of FPNA at Extreme Reach and has over 20 years of experience navigating Fortune 500 giants and dynamic startups. Let’s dive right into the topic, John. Just to start with a very easy question: What is the choice of fields for matching in the accounts payable process, and why is it critical for any organization?
John Silverstein: This is one of the most important parts of the AP process. Once you set up the matching criteria, it controls whether your matching is efficient and accurate and whether you’ll need to perform rework. Essentially, it ensures that we pay for what we purchase. Proper matching can prevent errors, fraud, and overpayments while ensuring compliance with contracts and internal policies. However, being too strict on the matching can slow down processes. It’s not just about the matching itself; it’s also about what data you’re gathering. You might match on three or four fields, but you could be gathering 20 fields, which may not need exact matches but can help inform decisions down the line.
Emily: Got it. So, John, can you explain the difference between two-way and three-way matching and when each is most appropriate?
John Silverstein: Two-way matching doesn’t involve the receipt of goods; it’s based only on matching the invoice with the PO. This method speeds up the process since you’re matching PO fields against the invoice fields. It’s especially useful for services or low-value transactions where you don’t necessarily have goods to receive. Three-way matching, on the other hand, includes the receipt of goods. This ensures that what you ordered on the PO is what was received. This method is more thorough and is ideal for high-value or high-risk items.
Emily: In your experience, what are the most critical fields to include in three-way matching, and why?
John Silverstein: The most critical fields are the PO number, quantity, unit price, and total amount. These fields ensure that you’ve received everything as expected and that the invoice matches the PO. The PO typically contains all the necessary accounting details, which predetermines how the item is booked once received. The PO number links to the invoice, while the quantity and unit price confirm that what was ordered matches what was billed.
Emily: Should the address field also be considered for matching?
John Silverstein: The address field is hard to match but critical for capturing from a sales tax perspective. Matching addresses can be tricky because billing often happens through different entities with varying addresses, which can slow down the process. While it’s essential for tax compliance, in my experience, I don’t usually match the address due to the many nuances.
Emily: Makes sense. Should the dates on invoices be matched as well?
John Silverstein: Yes, but dates should be matched within a tolerance. An exact match isn’t always expected since invoices might be issued a day before or after the receipt of goods. There are multiple dates like order date and ship date, making it confusing. AI can help with this by identifying the appropriate dates, but it’s still important to have some flexibility when matching dates to avoid unnecessary back-and-forth.
Emily: What do you do for tax matching?
John Silverstein: Sales tax typically isn’t matched at the PO level as the PO might not include sales tax details. However, it’s crucial to capture and validate this information. If you’re tax-exempt, you want to ensure you aren’t being charged incorrectly. Even when there’s no sales tax, it’s still important to check since your organization might still be liable.
Emily: What are the potential risks of matching too many fields in the AP process?
John Silverstein: The main risk is that you’ll never achieve an exact match on all fields like descriptions, item codes, product codes, and dates due to differences between the vendor and your system. It’s crucial to only match fields that are necessary for catching fraud and discrepancies like quantities and amounts. Matching too many fields can lead to errors, confusion, and manual processing, which defeats the purpose of automation.
Emily: On the flip side, what could be the consequences of matching too few fields?
John Silverstein: Matching too few fields, like just the PO, could result in missing key details such as quantities received. It’s important to strike a balance matching enough fields to ensure accuracy without overcomplicating the process. Depending on your industry, you’ll have different rules and risks to consider, but finding the right balance is key.
Emily: How can AI play a role in optimizing the matching process?
John Silverstein: AI accelerates the process by allowing systems to read invoices and correctly match them with POs and receipts. In the past, this was a manual process, often involving paper checks. AI not only automates this process but also improves accuracy by identifying potential matches that might not be straightforward. As AI learns over time, it can even begin to match more fields that weren’t possible before, reducing errors and manual interventions.
Emily: How do you balance the need for accuracy with the need for efficiency in the AP process?
John Silverstein: It’s all about how many fields you’re matching and capturing. Accuracy is crucial because it impacts accounting, audits, and overall financial integrity. AI helps by learning and adapting over time, enabling you to strike the right balance between accuracy and efficiency. As AI continues to evolve, it will further optimize this balance by reducing manual checks and improving the precision of automated matching.
Emily: Looking ahead, how do you see the role of AI and technology evolving in the accounts payable process?
John Silverstein: AI will make AP processes much easier by taking over tasks that currently require manual effort, like data entry. The keystrokes and data entry AP clerks handle today should become minimal. AI will also improve the integration between AP and AR processes, simplifying how invoices are issued and paid. Eventually, AI will handle complex formats and requirements, transforming how organizations interact with vendors and customers. It’s exciting to think about the potential AI has to make accounts payable more efficient and less error-prone.
Emily: Thank you so much, John, for sharing your insights on such an important topic. It’s clear that the right approach to matching in accounts payable, when supported by AI, can significantly impact a company’s financial health and operational efficiency.
John Silverstein: No problem. Thank you.
Moderated by Emily, Digital Transformation Consultant at Hyperbots
Emily: Hey, everyone, this is Emily, and I am a digital transformation consultant at Hyperbots. I’m very pleased to have Anthony on the call with me. Anthony is the CEO at Coast to Coast Finance. Thank you so much for joining us today, Anthony. We appreciate it.
Anthony Peltier: Thanks, Emily.
Emily: Today, we’ll discuss the intricacies of handling multi-currency purchases. Let’s just dive in. Anthony, multi-currency transactions are a common challenge for companies operating globally. Could you walk us through the typical scenarios where a company might face multi-currency purchase challenges?
Anthony Peltier: Yeah, definitely. As you mentioned, when a company operates globally, they may deal with vendors who typically prefer payments in their local currency. Several scenarios can arise, right? Whether you’re receiving quotes in a foreign currency, sourcing items from multiple countries, or generating global purchase orders, it’s important to think about how to manage the PO, how to handle payments, and how to record currencies in your general ledger to mitigate risks due to currency fluctuations.
Emily: Got it. When a U.S-based company deals with, let’s say, European vendors who prefer payments in Euros or GBP, how should the company decide on the currency for purchase orders and payments?
Anthony Peltier: Good question. Generally, I would recommend issuing the PO in the vendor’s preferred currency. That way, you can provide clarity on pricing and avoid complications due to rate fluctuations. Then you can make the payment in the currency specified in the PO. Of course, the company’s GL would still record the transactions in their functional currency, whether that’s USD, Euro, or whatever is standard for them. This approach balances the need for vendor payments with internal financial accuracy.
Emily: Understood. In situations where vendors provide quotes only in foreign currencies, how should a company handle this when issuing the purchase order and recording the transactions in their general ledger?
Anthony Peltier: Right. When you receive a quote in a foreign currency, the PO should reflect that currency to ensure the vendor receives the expected amount without conversion risks. Then your GL would record the PO’s value in your company’s functional currency based on an exchange rate that you’ve set up, perhaps in your ERP for currency conversion. If there are fluctuations in the rate between the PO date and the payment date, you may capture that as a purchase price variance, or if this occurs frequently, you may set up a forex gains and losses account.
Emily: Got it. Companies often source components from OEM vendors located in different countries. How does multi-currency management come into play in such scenarios?
Anthony Peltier: If you’re issuing multiple POs and managing multiple currencies, I would say issue the PO in the vendor’s preferred currency and make the payment accordingly. Your GL will convert and record these transactions in your functional currency. The real challenge lies in managing multiple exchange rates and understanding how fluctuations can impact overall costs. In such cases, having robust controls in place to track and manage these variations is essential.
Emily: Understood. That makes sense. For multinational companies with operations in various countries, how should they handle global purchase orders and the associated currency risks?
Anthony Peltier: For multinational companies, can issue the PO in either the local currency or the vendor’s preferred currency. You’ll want to record it in the local GL for the respective country where the company is operating. The parent company can then consolidate these local GLs into a global reporting currency, whether that’s USD or another currency. This allows each regional operation to manage currency risk locally while enabling the parent company to assess overall exposure and performance on a global scale.
Emily: Got it. That makes complete sense. Anthony, forex gains and losses are an inevitable part of currency transactions. How should they be computed and posted in the GL?
Anthony Peltier: If currency exchanges happen frequently, forex gains and losses are inevitable. For instance, if you issue a PO in euros and the exchange rate is 1 = $1 at the time, but when the payment is made, it’s 1 = $1.20, that additional cost would be recorded as a forex loss in the GL. Conversely, if there’s a favorable price shift, you’d record that as a gain.
Emily: Understood. How exactly can companies protect themselves from significant forex fluctuations when dealing with multi-currency purchases?
Anthony Peltier: That’s a good question. You can use hedging strategies or contracts to lock in exchange rates. Beyond purchases and vendor management, global companies must also consider how they pay employees in different currencies. If a parent company monitors forex markets, they can buy the currency needed for payments in advance to lock in favorable rates. The key is balancing risk management with cost efficiency, ensuring that hedging provides more benefits than costs.
Emily: Makes sense. Just to summarise, one last question: What role does AI, or what role potentially can AI, play in managing multi-currency transactions effectively?
Anthony Peltier: AI can be a game-changer. Automating exchange rate calculations and integrating real-time currency monitoring into your systems can make a big difference. The next step is to fully integrate this into your ERP to manage multi-currency POs, material requirements planning, payments, and GL entries. AI can also reduce manual errors. For example, someone might mistakenly move a decimal, leading to significant discrepancies. A quick story long ago when I first started working, I got a letter from the IRS saying I owed a substantial amount in taxes. It was a significant sum for me at the time, but it turned out they had moved a decimal point by mistake, leading to confusion. With AI, you can reduce such errors, predict currency movements, and make more informed decisions about currency conversion.
Emily: Got it. Thank you so much, Anthony, for joining us today and sharing your insights. Handling multi-currency purchases requires a strategic approach, combining financial acumen with the right tools and processes. Thank you for shedding light on this topic.
Anthony Peltier: Absolutely. Managing those transactions effectively is crucial not just for financial stability but also for supporting business operations on a global level, right?
Emily: Alright.Thank you.
Moderated by Kate.
Kate: Hello, everyone. My name is Kate. I’m a financial technology advisor here at Hyperbots. Today we have Polina McLaughlin with us. Good morning, Polina. How are you doing?
Polina McLaughlin: Good morning. I’m good, and excited to be here. How are you?
Kate: I am good. Thank you so much for asking. We are very excited to have you here with us today.
Kate: A little bit about Polina, she has years of experience in the pharmaceutical industry on the manufacturing and finance side and was heavily involved in cash flow optimization processes, improving AR and AP processes. Thank you so much for joining us today to discuss the importance of matching strategies in the accounts payable function. Let’s dive right in with our first question.
Polina McLaughlin: Go ahead!
Kate: Can you explain why matching strategies are critical in the accounts payable process?
Polina McLaughlin: Matching strategies are key in the AP process because you want to pay for what you’ve ordered and received. This way, you can avoid overpayments, fraud, errors, and paying twice, which can significantly impact the financial health of your company. Verifying POs to GRNs and invoices is critical for accuracy and for protecting the company’s assets.
Kate: Understood. Moving on to the next question, What are the different types of matching strategies used in accounts payable, and how do they differ?
Polina McLaughlin: You have three types of matching processes: three-way matching, two-way matching, and no matching at all. Three-way matching is for critical purchases where you match the purchase order with a goods receipt notice and the actual invoice, ensuring you received the correct items and billed the correct person or organization.
Two-way matching compares the invoice to the purchase order and is useful when you don’t need to verify the physical receipt of goods, such as with software or consulting services. No matching is for situations where neither a GRN nor a PO exists, and you need to verify an invoice without matching. Each strategy has specific applications depending on the transaction’s nature and associated risks.
Kate: That makes sense. Could you provide examples of situations where three-way matching would be most appropriate?
Polina McLaughlin: Three-way matching is the most thorough approach, often used in industries like manufacturing or retail. For example, when you receive large quantities of raw materials, you verify that the PO, goods receipt, and invoice all match, ensuring that everything was received correctly and payment was made to the right entity.
Kate: That’s clear. What about scenarios where a company might choose to use two-way matching instead of three-way matching?
Polina McLaughlin: Two-way matching is less thorough and typically used when there’s no physical goods receipt involved, like when you purchase software or services. In such cases, you can compare the invoice to the purchase order or delivery note without needing a goods receipt notice.
Kate: I agree with you completely. What about situations where no matching is possible? How should these cases be handled?
Polina McLaughlin: Some situations don’t allow for matching, like utility bills, employee reimbursements, or direct expenses without a PO or GRN. In these cases, it’s crucial to have strong internal controls like pre-approval processes, budget limits, and detailed record-keeping to ensure that such expenses are legitimate and align with the company’s financial plans.
Kate: That’s understandable. What are some best practices companies should follow when implementing matching strategies in their accounts payable processes?
Polina McLaughlin: First, automate the matching process to reduce human error and ensure consistency. Then, ensure clear documentation for POs, GRNs, and contracts, making them easily accessible. Establish exception management procedures to quickly address discrepancies. Conduct regular audits to verify that everything is matched correctly, and provide training for AP staff to understand the importance of these processes. These best practices are vital for maintaining financial integrity and reducing the risk of fraud.
Kate: I completely agree. How does artificial intelligence enhance the matching process in accounts payable?
Polina McLaughlin: AI plays a pivotal role by matching hundreds or thousands of invoices quickly and consistently. It can flag discrepancies for review, speeding up the payment process while reducing human error. AI ensures uniform data, helping companies achieve straight-through processing and significantly improving the overall efficiency of the AP function.
Kate: That was insightful. Now, we’ve come to our last question. What challenges do companies face when trying to implement these matching strategies, and how can they overcome them?
Polina McLaughlin: The first challenge is data quality. Poor data quality hampers automation efforts. Companies should invest in modern, integrated AP solutions to ensure uniform data and reduce human error. Another challenge is resistance to change. People often prefer manual processes they’re comfortable with. Overcoming this requires educating staff about the benefits and showing how automation can free up time for more meaningful tasks. Lastly, ensuring data accuracy across documents is essential. Companies need stringent documentation practices, regular audits, and a commitment to data integrity to maintain the financial health of the company.
Kate: I couldn’t agree with you more; that made a lot of sense.
Kate: Thank you so much, Polina, for providing such detailed insights into accounts payable matching strategies. These practices are vital for maintaining financial control and ensuring the smooth operation of any business. Also, a big thank you to all our listeners.
Kate: Thanks a lot, Polina, once again, and we’ll connect sometime later.
Polina McLaughlin: Yes, thank you. It was my pleasure. Ensuring the integrity of the AP process is fundamental to the overall company’s financial health, and I’m glad to share these strategies. I hope they help others achieve that. Have a wonderful rest of your day.
Kate: You have a wonderful day too, Polina. Bye-bye.
Polina McLaughlin: Bye.
Moderated by Emily ,Digital Transformation Consultant at Hyperbots
Emily: Welcome, everyone! My name is Emily, and I’m a digital transformation consultant at Hyperbots. Today, I’m excited to have Ayo, an expert in finance and strategic negotiations, join us for a conversation about managing time and material service invoices. Ayo’s vast experience in financial analysis and transformative project finance is going to give us some valuable insights into this topic. To start, Ayo, could you explain the key challenges that organizations typically face with time and material service invoices?
Ayo: Thank you, Emily. When we talk about time and material services, we’re referring to services where the billing is based on the time spent by consultants and the materials used. This type of service is inherently ambiguous if not tracked properly. The primary challenges include the lack of predefined quantities, variabilities in service delivery, difficulties in verifying time sheets, and ambiguities around what constitutes service completion. Unlike fixed-scope services, where everything is well-defined, T&M services can lead to uncertainties when trying to match invoices with the actual work performed.
Emily: That makes sense. So, how does an organization typically handle the verification of service delivery for T&M contracts?
Ayo: Ideally, a company should use detailed time sheets, service delivery notes, and performance metrics. Timesheets provide records of the hours worked, while service delivery notes confirm that the work was done. Performance metrics allow us to evaluate whether the service meets the agreed-upon criteria. The clearer these criteria are defined at the start, the easier it is to manage the project and process invoices later on.
Emily: Can you describe the process of matching T&M invoices with purchase orders and contracts?
Ayo: When matching invoices, organizations can use two-way and three-way matching processes. In two-way matching, you compare the invoice with the PO or contract to ensure the rates and terms align. For example, if the rate is $50 an hour for four hours, you confirm that both the rate and time match the agreement. Three-way matching adds another layer, incorporating service delivery notes and time sheets. You verify that the agreed-upon work was done and that materials were delivered as expected. This ensures the invoice amount corresponds to the actual work completed before you proceed with payment.
Emily: AI is increasingly being used in business processes. What role can AI play in matching T&M service invoices?
Ayo: AI can be incredibly valuable in automating data extraction from invoices, tracking time sheets, and analyzing service delivery notes. It can quickly identify discrepancies, like unusual billing rates or hours worked, and predict potential issues based on historical data. This predictive capability is powerful and reduces manual effort while enhancing the accuracy and speed of the matching process.
Emily: What do you think are the most significant benefits of using AI in this context?
Ayo: AI is faster, more accurate, and less prone to errors than manual processes. It can handle large volumes of invoices that would otherwise require entire teams of people. Moreover, AI can detect anomalies and flag issues based on historical patterns, which would take a human much longer to identify. By automating routine tasks, AI not only speeds up the process but also enhances its reliability.
Emily: One challenge that comes to mind is verifying service delivery in the absence of physical goods. How can that be addressed?
Ayo: One way is through service delivery notes that are signed by both parties and both the provider and the recipient of the service. This provides a document trail confirming the service was delivered as agreed. Additionally, using well-defined performance metrics and conducting regular reviews ensures that the hours billed and materials used match what was agreed upon. The person signing off from the company’s side ensures the verification is accurate.”
Emily: Have you seen any recent improvements or changes in the way T&M invoice matching is handled in your industry?
Ayo: Absolutely. We’ve seen significant improvements with more robust documentation requirements and integrated systems that streamline the process. For example, AI now handles a lot of the data extraction and anomaly detection. Traditional OCR technology has limitations, but AI can read even handwritten documents or unclear invoices. These advancements have really enhanced the efficiency and accuracy of matching T&M invoices.
Emily: Do you have any advice for organizations looking to improve their T&M invoice matching processes?
Ayo: My advice is to start with clear and detailed documentation in contracts and purchase orders. The more clearly defined these are from the beginning, the easier it is to process invoices down the line. Implement a rigorous verification process, with digital time sheets and service delivery notes wherever possible. Also, leverage AI to automate tasks and enhance accuracy. Regular reviews and updates of the process are crucial to identify recurring errors and work to mistake-proof them.
Emily: One last question: how do you see the future of T&M invoice matching evolving with advancements in technology?
Ayo: The future is bright with AI leading the way. I expect to see more advanced integration of AI in T&M invoice processes. AI will continue enhancing accuracy and efficiency while getting smarter at identifying acceptable exceptions. Over time, AI will learn from past data, making it even better at tailoring solutions for specific industries. For sectors like construction, where T&M contracts are common, AI will adapt to industry-specific needs and deliver more finely-tuned solutions.
Emily: Thank you so much, Ayo, for sharing your insights today. It’s been a pleasure exploring these complexities with you.
Ayo: Thank you, Emily. It’s always a pleasure.
Moderated by Emily Digital Transformation Consultant at Hyperbots
Emily: Hey, everyone, this is Emily, and I am a digital transformation consultant at hyperbots today on the call with me. I’m extremely happy to have Anna. Anna Tiomina is the founder of Blend to Balance Llc, with over a decade of experience in senior finance roles. Anna is also the leader of AI innovators in finance and beyond a community dedicated to merging tech innovations with traditional finance.
Emily: Really happy to have you, Anna.
Anna: Thanks for having me.
Emily: Excited to hear your insights on how AI is revolutionizing the detection of fraud and anomalies in vendor payment. So let’s dive right in as a CFO. Anna, how do you see the importance of detecting fraud and anomalies in vendor payments?
Anna: Yeah. So detecting fraud and ensuring compliance is one of the key functions of financial operations. In recent years we see much more fraud in this area. So it is challenging for CFOs to keep up with the technology and to be always ready to react to the new ways. The fraud actors are trying to reach the companies. So it is a really critical and very challenging task nowadays.
Emily: Correct. So, Anna, what are some of the most common types of fraud and anomalies you’ve seen or heard in vendor payments.
Anna: Yeah, so there are simple ones like replacing the bank account number on an invoice with a fraudulent bank account number. It can be as simple as sending the invoice that was never approved for payment, and the service or product was never received. It can also be inflated invoices, either through the pricing or through the quantities of products or services on the invoices or for example, demanding a payment before the product or service was delivered or received. So these are the most common risks.Listed vendors, and sometimes, if the company has some processes in place, the requester. The payment requester splits the invoice to get to a lower approval level. Sometimes it is a fraud, and sometimes it’s just a mistake or an attempt to speed things up so it can really vary. But each of these events represents a risk.The funds that the company is mistakenly or fraudulent to send cannot be revoked in many cases. So I mean, that’s a huge thing for the company to be able to keep things in order in this space.
Emily: And how can these frauds and anomalies be prevented with traditional methods per se?
Anna: Well, so what companies do they implement internal controls? They implement processes. They implement things like freeway mention. Right? So you have a PO that has to be approved. Then you have an invoice that has to be made to the Po, and then the invoice has to be approved on a different approval. Flow? Some companies don’t have POS. They have things like for ice principle, for example, like no payment, gets released until at least 2 people take a look at that. So you need 2 approvers on any payment going out. Also, companies try to make sure that the processes and these rules are followed. So there are things like internal audits. Kind of like processes that make sure that the forest principle is followed. For example, right, or the person that is sending the fund does the verification of the vendor before the funds are being sent.Still, all of this is very time consuming. This is prone to human error. This involves a lot of people in the company, and it doesn’t guarantee that the fraud or mistake doesn’t happen.
Emily: Got it. Got it So, Anna, how does AI enhance the detection of these frauds and anomalies compared to the traditional methods.
Anna: Oh, yeah. So the way I look at that is that AI is another pair of hands or another pair of eyes on your team that doesn’t get biased. That doesn’t get tired. That doesn’t cheat right? So this is another level of control that really helps to correct the bias that your team might have or spot the patterns that can be missed by humans. So AI, for example, can detect subtle differences in the invoices or flag, the duplicated invoices or spot the difference between the original purchase order and the invoice or compare the current, invoice with the historical data, and make sure that the mistakes that happened in the past don’t go forward into the future. So, having an AI complement, your team is a really really helpful tool.
Emily: Got it understood. And can you please help me understand, you know how AI can help prevent duplicate payments and overcharging and vendor invoices?
Anna: Yeah. So that’s a great question, because duplicate payments are a little bit hard to catch, because the invoice looks correct, right? And unless you have really really good controls in place. You might miss that. This is the duplicate invoice, and paid twice, either by mistake or as a result of fraud. So AI can compare the invoices and identify these duplicated invoices better than the humans can do. Also, AI is really great at comparing the invoice against the PO. If the company has a PO or the contract, or the sow, making sure that the vendor hasn’t overcharged the company, and that the agreed terms in the original documents are followed. This can be a very time consuming task for people to find the correct document to find the right line on this document, etc. So AI really shines here, and it saves a lot of time and effort for the human team.
Emily: That’s pretty incredible. So, Anna, what role does AI play in ensuring that payments are made only after you know the goods or services are received?
Anna: Well in a classic case, right, You would have a 3 way match process, and the Requester would have to push some button in your software that you’re using to confirm that the goods for services have been received sometimes. This process doesn’t work. Sometimes the requester wants to really push the payment forward to enhance their relationship with the vendor, or like for other reasons. So AI can really track the history of relationship with the vendor and also make sure that I mean, if there was a certain amount of time where the service was expected to be delivered, that these all timelines are followed. So again, this is another level of control, another pair of eyes that can be really helpful.
Emily: Got it and how does AI help in detecting payments made to unlisted or fraudulent vendors per se?
Anna: Well, yeah, that’s an excellent question, because like, usually, the companies have some controls in place to make sure that the payment doesn’t go to an unlisted vendor, and you will have to add each new vendor manually. But what sometimes happens is that you have, for example, an improved vendor. But then the invoice kind of duplicates the name, but that has other payment details. And this is how you send the funds to the wrong account. Number right, so AI can help verify that the original payment details are corresponding to what you received from your vendor when the vendor was listed and approved. Also there are public databases of fraudulent vendors. So AI is great to, you know, to be tasked with monitoring these databases and flagging.You know the fact that you might be paid to someone who is not on your approved vendor database. So again, because there is such a rise of fraud nowadays it is very difficult to keep track of everything that’s going on. So having technology as a compliment, your team is really really helpful and increases the team efficiency, too.
Emily: Got it and just to summarize everything, Anna, you know, looking ahead, how do you see the role of AI evolving in the area of vendor payment management?
Anna: Yeah. So I think that now we see just the beginning of AI complementing the Ap teams, I think that it’s gonna be used more and more, because this is just so efficient and handy, and also honestly, because the fraud actors are using a lot of AI. It is impossible to really like, offset this effort without having technology on your side too. So it’s like a race of technologies in a way. And I think that at some point it’s gonna be like a must have for the companies to have some level of AI in internal fraud. Detection process.Not immediately. But we are getting there.
Emily: Definitely. Thank you so much, Anna, for joining us today and talking to us about, you know such an important topic. Thank you for the valuable insight. It’s clear that AI is transforming the way we manage and protect our financial operations, and how, especially in the realm of vendor payments. So thank you once again.
Anna: Thank you for having me.
Moderated by Niharika Sharma, Head of Marketing at Hyperbots.
Niharika: Hi everyone, this is Niharika and I take care of marketing at Hyprbots. Today we have with us Anna Tiomina, who’s a CFO with Blend2Balance currently and has been operating in the finance domain for over two decades. Hi Anna, how are you doing?
Anna: Good morning, thanks for having me. Doing great.
Niharika: Lovely to have you, Anna. We are so excited to have you here. Before we begin with the topic, which is ROI on AI-led automation initiatives, it would be great if you could take us through your journey, your roles, and past experiences as a CFO, and how you’ve seen the finance domain evolve over the years.
Anna: Okay, so I’ve been in finance throughout all of my career, which is almost two decades by now, which is unbelievable. I’ve progressed from controller to senior controller to CFO. I’ve served as a CFO for more than 10 years, and I’ve worked in different companies and smaller companies in big multinational companies. So I think I have a pretty good understanding of the financial environment and the challenges that companies face in this sphere. My biggest goal is always to ensure the financial health of the organization but also to drive all the finance-related processes because finance is responsible for a lot of important things, you can’t drop any of them. In a way, a person who guards their organization from getting into trouble.
Niharika: Thank you so much for explaining that, Anna. I’m sure this conversation is going to be very valuable for all the listeners and viewers that we have. Your experience in the finance domain is going to enlighten us with what kind of decisions one should make when considering introducing AI in their finance processes. To begin with, I would love to understand from your vantage point, how you perceive the current landscape of AI-led automation in the finance industry.
Anna: Yeah, I might say this is a very exciting process right now. A lot of new things are happening in the area. It looks like AI automation would help finance professionals streamline processes, reduce errors, provide insight, and help us avoid manual tasks, which I think is the most unpleasant part of what we people in finance do. From the perspective of a finance executive, I see that this topic is on the agenda for many CFOs and organizations. It’s important to stay on top of this process for everyone who wants to progress in their careers and lead their organizations to success.
Niharika: Lovely. I’m sure this is going to be very insightful for all of us. From your understanding, what sort of investment do you anticipate when someone is thinking of implementing AI?
Anna: The first thing to mention is I’ve read research very recently, and it shows that finance is not among the top areas for AI adoption and implementation in industries. Companies usually start in areas such as customer relations, marketing, sales, software development, and R&D. Finance is somewhere at the end of this list. My understanding is that because finance is a very risk-averse area, this is not the first place where you would put innovation. Many companies are not ready for AI adoption because the data is not integrated. There is no single source of truth in many data points, and the processes are not smooth enough to implement automation. Implementing AI in finance is a substantial investment. We finance people always think about ROI, so when starting any effort, we think about what we will get out of that. When we talk about investment in implementing AI, there are three main areas: financial investment, time, and effort.
Niharika: Absolutely.
Anna: The most obvious is the financial investment: the cost of software, the cost of maintaining the software going forward. The second is time because there is not much experience in this area, and sometimes it’s hard to understand if it would take a lot of time or not to implement and adopt any technology. Let’s not forget about effort. I’ve always worked with very lean organizations where every additional process stretches the current team. I’m always very mindful of what I put on the shoulders of my team. So the three main areas of investment time, effort, and money are what it gets to if we talk about investment.
Niharika: Absolutely. When it comes to transactional data, value associated with money, and ROI, it’s good to be very mindful of where you’re investing concerning AI. Of course, AI is created by humans and it was not 100% accurate when it was introduced. After having it tested and tried in various domains, the application of AI in finance sounds like a good decision. At the same time, it’s very opportunistic in terms of what it has to offer shortly.
Anna: Yeah, I mean, it sounds exciting, right, in the beginning. But with any new technology, you need to assess some kind of ROI when making this decision. If you’re presenting this as an offer to a board or management team, you also need to put some kind of calculation behind it. When we think about returns that companies can expect out of this whole process, it turns out it’s not that easy to quantify at this point. We can think about measurable KPIs like productivity increase, cycle time reduction, fewer errors, being able to do more with less, reducing manual input, and customer and employee satisfaction. But to quantify those, you really need some kind of experience and data based on previous implementations. We don’t have that now, so we can run some kind of very high-level calculation. At this point, I think it’s wiser to focus on long-term goals rather than pure mathematical ROI calculation.
Niharika: Absolutely. Agree with you on this, Anna. Let’s say an organization has already introduced AI in its finance section. What sort of insights derived from data-driven by AI can impact strategic decision-making within the finance function, as per you? What are your thoughts about it?
Anna: Well, in my career, I was always developing my time around data preparation and then data analysis and getting the insights from the data. It would be great to get rid of this first part and get straight to data analysis. It is amazing to see sometimes what you get out of working with data. Sometimes, you have one perception of what’s going on, but then you run the analysis and you see a different picture. So, of course, having the ability to process more data, having AI do all the operational work for you, and not spending too much time organizing tables or preparing the data, is amazing. I think it’s an amazing transformation going on in the industry. A lot of valuable insights can happen out of data-driven processes.
Niharika: Absolutely. As we evolve in introducing AI to different organizations, it will surely give us some impactful outcomes sooner or later. As we are almost approaching the end of this conversation, do you have any advice for CFOs or finance leaders considering AI-led automation initiatives to enhance their ROI?
Anna: Yes, I have some advice to share. First of all, this is very unusual advice from my side, but don’t focus on ROI in the first steps of implementation. Think more strategically and focus on long-term perspective rather than short-term. Second, invest in proper training for your team. Experiment a little bit with some smaller processes. Every finance organization has some ugly data processing tasks they hate, so try to start with these smaller parts and then move to bigger processes. Establish a robust data management framework because as soon as you move to AI and start to utilize more AI-driven functions, the quality of data becomes paramount. Make sure the data is structured, consistent, and has a single source of truth.
Niharika: Absolutely. You rightly mentioned that each one of us who interacts with AI in the finance domain should be very mindful of the decisions we are making. Thank you for that. I think these were some great insights that will surely help future CFOs. It was great having you on board and having this conversation. I had a lovely experience, and it was very insightful for me as well. I’m looking forward to having more sessions with you. Thank you so much.
Anna: Thank you for having me.
Finance and accounting (F&A) are critical to the operational efficiency and strategic decision-making of any business. The advent of artificial intelligence (AI) presents a transformative opportunity for these functions. This article analyzes manual, analytical, and strategic activities within these functions and determines the most optimal AI adoption roadmap.
The following table estimates the volume of manual, analytical, and strategic activities in these functions as high, medium, or low:
| Functions | Manual | Analytical | Strategic |
| Procure to Pay | High | Medium | Low |
| Order to Cash | High | Medium | Medium |
| Expense Management | High | Medium | Low |
| Tax and Compliance | Medium | High | High |
| Treasury | Medium | High | High |
| Financial Planning & Analysis | Low | High | High |
| Mergers & Acquisitions | Low | High | High |
The next-generation AI technologies are mature and can be applied well in Finance and Accounting with a significant financial impact. We recommend prioritizing the Procure-to-Pay, Order-to-Cash, and Expense Management functions for AI adoption.
AI techniques for interpreting unstructured data have advanced significantly in recent years. These techniques now permit what was previously considered human-level intelligence tasks.
Transformer-based frameworks allow for unstructured content understanding, language generation as well as predictive tasks. Large Language Models (LLMs) accelerate the ability of AI systems in language understanding, information retrieval, summarization, text generation, and conversational AI. Data-driven econometrics models for forecasting and trend analysis enable numeric and financial data analysis.
In finance automation, this is how these AI techniques can radically transform each of these tasks:
The structured and orderly nature of finance processes, underpinned by a robust ERP knowledge base, provides a solid foundation to leverage sophisticated machine learning and AI methodologies. Now is an opportune moment to invest in the adoption of AI-native strategies for a substantial positive business impact.
The P2P function involves numerous repetitive and manual activities where AI can significantly increase efficiency and reduce errors.
| AI Capabilities | Readiness |
| Uses machine learning and LLMs to achieve straight-through processing for 80% of invoices. This includes automated invoice extraction, understanding, validation, matching, GL coding, and posting | Short-term |
| Uses forecasting systems to automate accruals | Short-term |
| Uses predictive and prescriptive models for optimal vendor payment timings | Short-term |
| Uses advanced ML techniques to detect fraudulent and duplicate invoices | Short-term |
| Uses classification techniques to classify expenses for capitalization | Short-term |
| Uses AI models and tax dictionaries to verify the sales and other types of applicable taxes | Short-term |
| Builds company and F&A-specific conversational AI models to provide chatGPT-like analytics | Medium-term |
| Optimizes vendor selection using predictive analytics | Medium-term |
The O2C function is also highly manual and prone to AI automation.
| AI Capabilities | Readiness |
| Uses machine learning and text processing techniques to extract and validate purchase order information from customers PO documents and contracts and auto-uploads information into the ERP system, resulting in 95% plus automation | Short-term |
| Uses advanced AI techniques to generate customer invoices based on purchase orders, customer master, inventory, and shipment information to generate 100% First Time Right (FTR) invoice. | Short-term |
| Uses recommender systems to create a daily/weekly priority list of customers for collections. | Short-term |
| Uses dynamic models to enhance customer credit scoring | Short-term |
| Uses advanced data science techniques for cash management including discovery of discrepancies, over and under-payments | Short-term |
| Uses generative AI to automatically communicate with customers on invoices and payments, including follow-ups | Short-term |
| Uses generative AI for conversational analytics on O2C data | Medium-term |
Employee expense management continues to be tedious for employees and the finance teams. This process can make use of AI to achieve a very high degree of automation.
| AI Capabilities | Readiness |
| Uses image and text processing techniques to automatically extract information from receipts and bills, and validate and auto-create expense reports for employees. | Short-term |
| Uses machine learning techniques to verify expense reports against policies and proofs. | Short-term |
| Uses advanced ML techniques to detect fraudulent and duplicate expenses. | Short-term |
| Uses classification techniques to identify the correct GL code for each expense | Short-term |
| Uses generative AI to communicate and answer employee queries | Medium-term |
AI has a high potential to optimize and streamline the tax and compliance function.
| AI Capabilities | Readiness |
| Automates collection and validation of data required to file tax returns, ensuring higher accuracy and reduced human effort | Medium-term |
| Applies the correct withholding rates based on payer and recipient jurisdiction, reducing errors | Medium-term |
| Helps organize documentation related to taxation for audit purposes | Long-term |
| Tracks applicable sales and use taxes across jurisdictions, ensuring accurate application to transactions | Long-term |
| Uses generative AI to map financial statements to the latest reporting standards. Facilitates SOX compliance | Long-term |
AI can provide substantial value by automating routine activities and improving decision-making in treasury management.
| AI Capabilities | Readiness |
| Machine learning models analyze historical cash flow patterns to predict future cash needs. | Medium- term |
| Monitors cash balances across accounts and recommends the most efficient pooling techniques. | Medium- term |
| Compares fee structures across banks, helping to negotiate better terms. | Long-term |
| It uses advanced predictive models to assess market risks and helps optimize long-term portfolio allocation. It also recommends low-risk, high-return, short-term investment opportunities. | Long-term |
| Predicts currency fluctuations to help develop effective hedging strategies. Identifies forex arbitrage opportunities. | Long-term |
| Builds models to identify market and operational risks using various internal and external debts. | Long-term |
FP&A involves many analytical and strategic activities. AI can help improve decision-making for these activities.
| Automates the data extraction from structured and unstructured sources like documents and ERPs | Long-term |
| Analyzes the historical data to build predictive budgets and rolling forecasts | Long-term |
| Simulates scenarios and recommends outcomes | Long-term |
| Helps in variance analysis between planned and actual budgets | Long-term |
| Analyzes capital allocations and predicts ROI using historical data | Long-term |
| Predicts future cashflows based on historical trends | Long-term |
AI can play a significant role in M&A, improving efficiency and strategic decision-making.
| AI Capabilities | Readiness |
| Analyzes financial reports and news articles to assess potential targets. | Long-term |
| Builds sophisticated financial models using machine learning to provide a more accurate valuation of the target companies. | Long-term |
| Analyzes contracts and other financial statements for risks and liabilities. | Long-term |
| Identifies and predicts potential risks. | Long-term |
| Provides data-backed insights into potential negotiation points. | Long-term |
Now that we have analyzed the specific AI-based automation of the above finance functions, we can estimate the financial impact it can create.
Having evaluated the financial impact on all F&A functions, we can recommend the AI adoption roadmap.
The next-generation AI technologies are mature and can be applied well in Finance and Accounting with a significant financial impact. We recommend prioritizing the Procure-to-Pay, Order-to-Cash, and Expense Management functions for AI adoption.
