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 pleased to have Claudia Mejia on the call with me. Claudia is the managing director at Ikigai, and the topic that we’d be discussing today is that why the industry is struggling to achieve straight-through processing of invoices honestly, there could have been no better person to speak about this. So glad to have you on board, Claudia.
Claudia Mejia: Thank you, Emily. It’s a pleasure to talk with you this morning. Thank you for having me.
Emily: Amazing. So to quickly start things, Claudia. Let’s start with the 1st question, What is the straight-through processing of invoices?
Claudia Mejia: Well, basically, it’s the process where the invoices come in. And then we automatically can process them to the ERP system. It includes not only the data capture of the invoices but the validation of the data and also the integration with the accounting systems.
Claudia Mejia: So it’s usually in a conceptually, I see process, but it doesn’t work as simple as it sounds.
Emily: Understood. So, Claudia, have you seen anywhere wherein, straight-through processing of invoices is being achieved?
Claudia Mejia: Honestly, with my experience, I usually consult small and medium-sized companies, and I have not said a thorough end-to-end process that is seamless, it usually is fragmented. You have various stages to the process, and you have a lot of manual manipulation and validation of the data. So it has been one of the challenges that I have seen with the CFOs. The procure-to-pay process is challenging and very manual. It requires a lot of effort. However, with hyperbots, we have seen that this is the solution that has been able to bridge all these gaps and bring the invoices from beginning to end very seamlessly.
Emily: Great. So because you mentioned, Claudia, that the process is a little fragmented, especially in the small to mid-sized businesses. What are the primary challenges that you have seen in achieving straight-through processing of invoices?
Claudia Mejia: Well, there are several issues, right? When you receive invoices, you receive them from different sources. You have portals, you have email IDs, all kinds of sources of information, and different types of formats which means you have structured data, and in structured data, it is very hard to control the variability in one aspect, and taking all that data and integrating it into legacy systems that they are not flexible. And so those have been some of the challenges, and on top of that, you have the resistance to change. Corporations don’t want to change their workflow. They’re fearful of technology. And the new technology that we see with AI is new. But it’s very powerful. I have seen it and is amazing for this process but those are the challenges that most companies have regarding it.
Emily: Understood. So, Claudia, if any organization is, say, PR-PO driven. Is it a better fit for straight-through processing of invoices as in what should a company do, if most of its purchases are still without a purchase, requisition, or purchase order?
Claudia Mejia: Well, PO, some PR structures are very important for this process. The more you can standardize this process at the beginning of the process the better it’s gonna be on the data validation through the process. So we want for that process to be very standardized, the templates, the formats but it’s not as easy, right? But my recommendation for the companies that don’t have a PR structure is just to try to standardize those processes, because once you bring the technology, on top of that, then it will make the whole process a lot easier.
Emily: Understood. So, Claudia, since the chart of accounts and GL codes in each company is different, you know. GL coding of each invoice is difficult to automate. Why is it so? And what can be done to handle it?
Claudia Mejia: Well, deals have all kinds of structures for different companies right, so it’s very difficult to just standardize one charge of accounts but the solution that now we have with Hyperbots is that the system now can learn by itself, so something that invoice, we can code in particular GL accounts. The system will learn that over time, and it will be very accurate and will place that spending into that GL account in the past with other processes. This is not as simple you will require manual manipulation and somebody validating that particular GL code. So the technology is there, let’s use it.
Emily: Got it. Also, I’ve seen there are so many solutions in the industry specifically OCR. Why do you think the current OCRs are not, you know, sufficient to understand the content of an invoice and is it a big handicap?
Claudia Mejia: Well, it is. Let’s describe what OCR is, which is optical character recognition. This technology is very good for converting PDFs and images into text but it has a little bit of a struggle with consistency, on the other hand, natural language processing is not only able to recognize and transfer the images to text but also understand the context behind that images on text, so it can learn by itself, which you will never find in the OCR technology, because it’s not. It wasn’t meant to be like that. So that’s what, now with AI we will be able to kind of do the end-to-end process in a way that is not as fragmented as we talk about.
Emily: Got it. So you know, diverse formats, unstructured data and lack of standards is it the reality? So is that the primary challenge for straight-through processing, and what exactly can be done to address all of these?
Claudia Mejia: Well, you have. This is something that I say. I am a process person, usually. So when I look at coordinate states or processes. I always start with the process and then we bring the technology that can fix the process. Okay, help the process not to get fixed process. But in this particular case, the technology is the one leading the process because of the technology. Now we’re able to push through the data from end to end and so my recommendation is, to make sure you understand your processes in the beginning and standardize those formats, making sure your vendors understand those formats, and then use the technology to push through the data, validate data, capture the data, and make sure it goes directly to the ERP without much manual intervention, unless you want it to be right. There are pieces that you say no, I don’t want to go directly to my ERP until I approve certain expenses so those are the main points that you can put through the system to make sure that you have the controls that you want.
Emily: Got it also a few obstacles for straight-through processing of invoices are inaccurate data in the invoice, or, you know, supplier side error, duplicate invoices. How to address these challenges?
Claudia Mejia: Well, the beauty about hyperbots specifically, because I have seen it is that the technology can not only read the data, understand the errors make sure it stops any invoices that have the errors, and then also provide recommendations. So there are a lot of good stages through the process that somebody can say, Oh, here I have the error, here I have inaccuracies. So that’s the beauty of having 1st a robust standardization, but also a good process through the book.
Emily: understood and from a regulatory standpoint, Claudia, you know what regulatory and compliance aspects should be evaluated for straight-through processing of invoices?
Claudia Mejia: Well, from an accounting point of view, there are a lot of controls that you need, right? So you need the all details, to make sure there is transparency in the transactions. You need the tax regulation that when you have invoices from different countries and different tax regulations, the system also has the flexibility to grab those types of regulations, and any inaccuracies through the process also can grab them or stop them. right? and data security. We are all concerned about data security, and make sure that all the data that goes through the system is secure and protects sensitive information.
Emily: Got it. And just to wind things up, the last question that I wanted to ask you, Claudia, is, what advancements in AI can help achieve straight-through processing to the highest possible degree?
Claudia Mejia: Well, AI has different levels of technology, right? So we have the machine learning algorithms which will help extract the information from the invoices, then we have the natural language processing which will be able to learn by itself and predict, and make recommendations and so does the magnificent view of this technology, right? This is something that we were not able to do before. And then we have the advanced analytics and so now we combine all these factors into a system like hyperbots, and we will be able to truly do it end to end. That’s what I said in this particular process technology leads it and I’m very happy to see that Hyperbots has been able to put it all together for us, and you’ll see the ROI come through.
Emily: Alright. Thank you so much, Claudia, for talking to us about the different challenges that the industry is facing with the straight-through processing of invoices, and also suggesting a couple of different measures. It was a fruitful discussion, an insightful one. So thank you so much for joining us today.
Claudia Mejia: No, thank you, Emily, thank you for having me.