AI Strategies for Finance Leaders to Streamline Audits and SOPs Using GenAI with Natalia Toronyi

Welcome to the Future Finance show where.

We talk about treasury management on Mars.

AI is completely reshaping industry and all the departments, not only finance.

What's your thoughts in the treasury space.

As far as AI?

I think those processes will now be more blended and more merged because.

Natalia Tironi is a global finance leader with over 15 years of experience guiding companies through growth, change and complexity. She's helped major organizations to improve performance, manage risk and make smarter decisions. Whether it's leading M and A, streamlining operations or shaping financial strategy, Natalia drives results that last.

We definitely need to invest in digital education for our team, providing them learning tools.

If you're not going to do that, then don't waste a ton of money to bring in new technology.

We need to know what we expect from that tool to solve. Because if we just bring AI and it will solve all my problem, it probably will create more chaos and solve problems.

How has living and working across multiple countries shaped your approach to leadership?

It taught me that.

How do you see AI helping manage the audit process?

I think probably one of the first starting points which I would implement if I would start utilizing AI in multiple finance processes would be.

Future Finance is brought to you by qflow AI, the strategic finance platform solving the toughest part of Planning and analysis. B2B revenue. Align sales, marketing and finance seamlessly speed up decision making and lock in accountability with qflow AI.

Welcome to Future Finance. I'm one of your hosts, Glenn Hopper and our other host, Paul Barnhurst is with me here today. And our guest today is Natalia Taroni. She's an executive with almost 20 years of experience leading financial transformation across Fortune 500 global industrial manufacturing companies. Natalia is known for her sharp problem solving skills, curiosity and transformation mindset, especially when it comes to driving impact through AI, automation and data. She's led major restructurings, M and A and operational turnarounds, all while staying grounded in integrity and leading by example. She's also a passionate mentor and a strong advocate for people first leadership. Always focused on building trust, empowering teams and creating cultures where innovation and inclusion thrive. Natalia, welcome to the show.

Thank you for inviting the nice introduction.

Yeah, you sound like you are what Paul and I aspire to be.

I don't think so. I have a long way to go, so we are all learning.

I just aspire to actually be considered an adult. Glenn. I can get there.

That's why you have the beard.

You'll both laugh at this, then we'll jump into the question. So someone on LinkedIn the other day shared there was he was invited to speak at something and they listed him as Microsoft Excel Adult, which what they meant. He was. He's the winner of the adult category, not the college, but the way you read it is he was a Microsoft. He's like, I've never been considered a Microsoft Excel adult before. And we all kind of tease him like, welcome to adulthood. It's amazing what not having a dash or just that simple little things in grammar will do. Yep. All right, so let's start here. We'd love for you to share a little bit of your journey. I know you live in Ukraine, Budapest, you know, now in the US You've worked for several different companies. Just tell us a little bit about your journey and background and how you ended up where you're at today.

You know, I was born in Ukraine in a small town called Oshgorod, it's in western Ukraine. And I grew up during the very interesting time when Soviet Union collapsed. It was a very. The time of chaos. I. I lived through hyperinflation with daily currency revaluation. You know, people worked for six, nine months without getting paid until majority of the companies just completely collapsed and shut down. And everybody had to figure out how to survive and how to live. So when I'm looking back, I still don't know how my parents managed to put the food on our table every day. For us, it was just normal. We were kids, we didn't pay too much attention to it. But now when, you know, I think back, it always comes to my mind, you know, that was the great lesson to learn. No matter what's happening around you, giving up is not an option because you have to survive. So in my early 20s, I moved to Hungary. You know, I graduated from Uzhgar National University with a major in accounting and audit. And when I moved to Hungary, I realized I actually have to start from the very beginning, from the scratch, because not only my degree is from Ukraine and I need to now revi. Reevaluate it. I need to start the language from. From the very beginning, which is Hungarian is one of the most complex languages in the world. So I started to learn the language from the cartoons, which at that time my daughter watching. And the second thing I learned in very small details was the law about accounting and audit because I was ambitious and I wanted to continue my career or restart my career and I had to deep dive into how can I do that? So I revaluated, I had my diploma revaluated and I kicked of my finance career in Hungary in a small CPA office where I was the best employee because I could not participate in any other discussion than processing the numbers. But you know, that gave me an opportunity to learn the language and improve it every day. So shortly after I joined my first corporate company, Alcoa, where you know, with the help with the excellent teachers and mentors, I, I learned I first was exposed to use gaap. I was given a better visibility of what it meant to operate within global processes, what SOX compliance means and how to contribute to performance in of of the global corporate company. I think that company Alcoa was, had the best and the cleanest processes I've seen during my time, 20 years with a huge focus on SOD segregation of duties and SOX compliance. So that was my base which gave me a very strong step into finance. After this I joined multiple companies changing, you know, growing in my career. Through bp, Eaton and Signode, I led global finance teams, delivered numerous transformation projects, you know, implementing different automations. Now AI, I helped to build finance operations from the scratch, centralizing multiple departments into one, guiding finance departments through cyber incidents and fraud recoveries. And always in my work, I always champion innovation, automation, data analytics and better processes. So that's shortly my story.

That's amazing. And I think that the adaptability that you had to have in moving to a new country, learning a new language, learning accounting in that new language had to be just so much to work through. But it seems like what the takeaway from that is, is that you learn to be resilient, you learn to be adaptive. And that's, I mean, things that you would apply for the rest of your career. So, you know, putting in the hard work early and going through that, it seems like it served you well through the rest of your career.

It did. Now I can say that way back then, I probably didn't.

Yeah, at the time.

Yeah, yeah. Often the case right at the time you look at something go, why am I dealing with this now though?

I kind of want to watch Hungarian cartoons.

Well, go ahead, let's do that tomorrow.

Glenn, we can carve out.

Yeah, all right. Yeah, special episode. Well, going through all that, I mean I, you know, future of finance and Paul knows every time I get up, the first question I ask is going to be about AI. So as soon as you mentioned AI, I kind of locked onto that. And I'm wondering, with your journey through accounting and finance and all the transformations you've done, how are you seeing the latest generative AI and technology reshape the way that you work today? And will you work in the way that the profession is changing and will change.

I think it's completely reshaping industries and you know, industry and all the departments, not only finance, a lot of times people, people are asking questions, you know, which department will be impacted, which department will not be impacted. I can see even looking into finance organization, every department will be impacted. And we already saw a lot of automation in complete order to cash process procure, to pay process, GL cost accounting. I can see a lot of departments transitioning and merging where now they will be more complex and more connected. So AI is bringing opportunities, you know, to different analytics. It gives us visibility, it changes how we forecast. It's providing now a different business insights which before we didn't have. I think it's shifting the departments and changing the entire departments and how we do the, how we even process transactions.

Yeah, absolutely.

I agree. It's. You mentioned, you know, consolidation really maybe some complexity. There's just so much going on. And I'm curious, I know you've worked in treasury, what's your thoughts in the treasury space as far as AI? Are you seeing or do you think we'll see a lot of benefit around cash flow forecasting, you know, working capital optimization, FX risk?

We'd love to kind of get your.

Thoughts in that space of maybe, you know, what you've seen and what you think we'll see there.

You know, I mentioned a couple of minutes ago that departments will start to transform and change the way how we are pulling the information and analyzing that information. You mentioned cash flow forecasting, which historically was a Treasury function and working capital, which, which is ARP inventory management. I think those two processes will now be more blended and more merged because now we will not use only information from the bank statement to forecast cash, but we will deep into our ERP systems gaining the visibility of customer behaviors, vendors terms and how we schedule inventory demand. All those activities will be transformed and changed all on a more precise data point. We can now put incorporate macroeconomic indicators. We can build our models more precisely using all that information.

Yeah, and you know when you talk about bringing in macroeconomic data and sort of pulling in data other than whatever drivers you have internal to the company, that makes me think back to, I guess we'll call it classical AI. The more machine learning what's been around for years and a lot of people just today are just talking about generative AI and of course that's taken the world by storm and it's made classical AI more approachable and accessible because you don't have to get through it to it through Python and coding and all the barriers to entry we used to have. And as I travel around and talk to different groups, an area that is, I was going to say near and dear. I don't know if that. If audit is near and dear to anyone, but it certainly.

I was going to say when is the audit near and dear? I usually run from the auditors. I say that out loud.

So near and dear was the wrong choice of words. Audit is something that anyone in, in the public company space certainly is very familiar with and it's an area that is very time intensive and very, you know, a lot of the work that we're doing in an audit is or for on the auditor side as well is very. It could be repetitive and it's complex. And I get asked all the time, is AI going to help with this? And the flat answer is AI is going to help with everything. But I don't know, you know exactly when. But I'm wondering from your perspective, how do you see AI helping? I don't manage the audit process. Do you have tools that you're using today and that could be generative AI or even, you know, classical machine learning?

I think probably one of the first starting points which I would implement if I would start utilizing, you know, AI in multiple finance processes would be internal audits and I would start with creating well defined written processes and controls. Probably the first option which comes to my mind would be genai through OpenAI, creating the GPT, uploading the clear defined processes, SOPs into that AI agent or assistant and starting to create the instructions for all the departments and based on that also utilizing the same document created and cleaned for internal audits or for, for pulling information for the audits. I can't even say that it would be annual audit now because before we would create some, you know, processes where we would use random samples selected for auditing. Now this, quick, fast tools, they give us an opportunity to, to test not only samples, so not only 30 or 50 samples a month, but we can test, you know, 30% of the samples or 50% of the information to look for deviations, to look for exceptions and only pull those which don't align with those clean defined processes and SOPs. So I didn't see, and I don't, I can't mention any AI tool which is helping with audits right now. But WDA probably my main focus because from there you can build all the processes correctly without, you know, that's your base.

Yeah, it goes hand in hand. With. With controls. And it's funny, as I talk to people, I don't know what it is. And Paul's probably heard me say this before, but I would go and I'd talk to a room full of CFOs, controllers, auditors, you know, just all across finance and accounting. And it was always an auditor who came up to me and would say, AI could never replace my job. And I always think, is there anything more rule based than audit? You are perfectly set up to be replaced by the bots. And if, Paul, if you can, let me get up on my soapbox here. What? What?

I love that you said, go ahead, get on your soapbox, Glenn. It's been a while.

Natalia. I loved what you said about documenting processes. So I got my career start in the military, and in the military you had to have standard operating procedure for everything you did. And I have, every role I've had, I'm documenting what I do. And then when I had direct reports and all the way down through my departments, we're going to document everything. And now, you know, seeing where we are with AI, I feel like. Well, that was a really prescient approach. If I do pat myself on the back here, because the same. The same SOPs that we would use to train new employees, well, guess what? Those are going to be used to train agents that are going to be doing this job in the future. So if you haven't put your SOPs together, this is my soapbox, Paul. If you haven't put SOPs for everything you do, do that now, because in the very near future, we're going to be using those SOPs, not to train new employees, but to train the bots who are going to take our jobs, I guess.

Yep.

So if your SOPs are not correct, the AI will generate the full cows everywhere.

So I shouldn't admit my SOPs are a mess. How good are your SOPs for your business of one, Glenn?

I didn't know you had a procedure for anything, Paul. I thought you were just winging it from show to show.

That's why I don't have any SOPs. Yeah, they kind of go together. So, you know, we've talked quite a bit about AI, a little bit in Treasury Audit, you know, different areas in finance, you know, but I think something a lot of leaders struggle with, and I've had them ask me, is how do you distinguish, you know, between what's real and what's hype? I think I saw the other day, in the last two, two and a half years, whatever it's been now two and a half since, you know, version 3.5 of ChatGPT came out. There's been 75,000 AI native companies start now. Not all those are in finance, but just think how much that is, right? I think people are just overwhelmed. So how do you kind of look at that and evaluate technology? What advice or thoughts would you give for somebody who just kind of looks at it all and goes, I don't know what's real, I don't know where to start. They're just overwhelmed. Ever feel like your go to market teams and finance speak different languages? This misalignment is a breeding ground for failure, impairing the predictive power of forecasts and delaying decisions that drive efficient growth. It's not for lack of trying, but getting all the data in one place doesn't mean mean you've gotten everyone on the same page. Meet qflow AI the strategic finance platform Purpose built to solve the toughest part of Planning and Analysis, B2B Revenue. QFlow quickly integrates key data from your go to market stack and accounting platform, then handles all the data prep and normalization under the hood. It automatically assembles your go to market stats, makes segmented scenario planning a breeze and closes the planning loop. Create airtight alignment, improve decision latency and ensure accountability across the team.

It is and you know, it's a great question. It's very easy to get lost with all the solution offered. Right now pretty much every second company is offering some AI solutions which in a lot of cases it's not even AI, it's machine learning which was there before. So we need to make sure that we distinguish well between you know, marketing tool and real AI and machine learning involved in the processes. But I always come back to three things. Does it solve the problem, the real problem I currently phase is it scalable and can it be measured? I look for solutions that either save time, bring some efficiencies, reduce some risks, or help in decision making in different processes. If it just adds the complexity to already existing processes and it requires additional multiple steps and we don't have clear return on investment, it's a no go. Another test would be probably how that particular solution plays with our existing systems and how also very important how it comply with our security requirements and SOX compliance requirements. In the past those solutions often required replacing or upgrading legacy systems, building very complex integration, cleaning data, migrating data which would lead to high infrastructure cost. I'm not an expert, I'm not technology person, but based on what my research is, it seems like with AI, it's changing because now AI, especially if we use different, you know, gen AI rpa, it reduces the need of full system implementation. So it, it breaks, brings potential solutions to the companies which don't want to invest into ERP re implementation or bringing new ERPs. And it still can bring efficiencies into the processes you need to know. Again, going back to clean processes and SOPs and defined, you know, rules, we need to know what we expect from that tool to solve. Because if we just solve, think, oh, I'll bring AI and it will solve all my problem. It probably will create more chaos than it solve problems.

I guess before I go into, I think you're spot on with all that. And before I go into my next question, an update. So I got interviewed by CFO Brew the other day and they asked me, I was thinking about tools that have hype and you know, everybody's talking about AI agents right now and everybody wants to pretend they have agents. And I just, all the ones that I've used. If you're dealing with a low stakes part of the company, if you're doing something that's not mission critical, it's interesting to use these agents and see what they can do. But in finance and accounting, there's no gray area. We have to be spot on and. Right. And we can't adjust for hallucination.

You mean half equal credits? Glenn?

So CFO Brew, Jesse Klein, the reporter from CFO Brew that interviewed me, was asking me what I thought about agents. And I was just bluntly clear. I was, I've said they're not ready for prime time. Everybody wants to say they have an agent. I wouldn't put an agent anywhere near my accounting. I wouldn't let an agent reconcile my accounts at this point. Just they're not ready for prime time. Well, this morning CFO Brew came out with the article and, and it's me and some executive from Salesforce. So I thought, great, now I'm at war with Salesforce because, you know, they've got their big agent force and all that. But it's, you know, and I don't know, they may be doing agentic workflows and obviously they're working through hallucinations and certainly with the capital and resources they have behind it, I think Salesforce is going to get there. But they're just two people quoted in the article, you know, some big wig from Salesforce and then me over there just saying it's all hype. But it is. I mean it's, you know, We're, I think all three of us are evangelists around AI and what it can do, but we also have to be practical about it.

And I can add to that. You know, I was the similar opinion as what you just described maybe two months ago until I started to work helping some startup company implementing or setting up AI agents. The capabilities of those agents are just super, super good. I do think we can implement AI agents in finance, but what we need to keep in mind we need to set up them based on segregation of duties. So there should be one agent for process following only that particular scenario and they should not be overruling each other because there is a process problem with that. When you give the full exposure to your AI agent to all different tools. Like for example, you know, compensation data should not be accessible to AI agent because otherwise it can expose that information to the people who should not have access to that information. It's possible and it evolving with every day, not even every week. But we need, as finance as you think everybody should be cautious and measure where it's reasonable and where it's too, too soon to implement them.

Yeah. And you know there's a difference between a truly agentic tool versus agentic workflows. Now the workflows, I build those all the time and that's, that's what I'm saying. Yes, we can use those every day. I, I, I told a client this morning, give me any digital process in your company and I promise you I can automate it. And that's, but that's not just flipping on a bot and saying go do this. Even with that sop, it's still you have to define the steps and keep it in those guardrails. And I'm sure that's what Salesforce is doing as well. I haven't had an opportunity to use any of their tools yet. And I guess with all that, that kind of leads into my next question of we are seeing as these agents get better, it is going to change the workforce. And Natalia, I know you said before the show that you know, companies need to rethink their talent retention and development and, and just obviously automation has, has done a lot over the years, but we're at a whole new level now. So tell me, tell me your thoughts around that.

Yeah, we as leaders, you know, we are responsible to how we shape our talent and what to look for now knowing what is coming our way, that the, you know, the talent is changing, the required skills are changing. There no way back. So you know, if before attention to the details Excel knowledge and you know, being precise were very valued in finance background. Today we need to pay attention to the critical thinking. How they can, you know, do a strategic judgment, ability to translate the insights provided by AI, making sure that the information is correct, making, you know, like how do they decide if what they receive from AI is correct or not? They need to know where to checkpoint that information. We need to definitely to introduce our teams and give them an opportunity to work in a transformation projects and digital projects so they are not scared to work with AI tools with machine learning. But definitely it changes who we hire and how we develop the talent within finance organizations. How do we ask questions correctly? What exactly do we ask?

Yeah, it's going to change the rules a lot. Like you said, the questions we ask, how you validate things, how you think about projects. You know, there'll be many cases where, you know, you might be able to ask an AI to do the Excel.

Part for you, but you still have.

To be able to validate it. You still have to be able to think through that and means you have to understand it, but you also have to think and do things in a different way. So it's going to be really interesting to watch how it changes roles and like you said, retaining and developing talent and hopefully I think we've all, you know, see this coming. It will really help people be more of thought leaders and strategic and less of the, the drudgery that we've all dealt with. How many of us have spent a day cleaning data? Right. And it's not to say AI is going to eliminate the need to ever clean data. I don't, I don't think that's in the near future. Maybe I'm wrong, you guys can disagree with me, but it's definitely going to help for sure. And so as we think about all of this and bring it together, what's your perspective, say five years from now, where do you think we'll kind of be with AI? Realize none of us have a crystal ball, so it's just kind of your thoughts. But where do you see us heading and maybe what are some of the things you see changing as the role of AI continues to increase in the.

Office of the cfo?

Well, as you said, we definitely need to invest in digital education for our team, providing them learning tools so they can utilize those tools and test them. But in five years, I can envision that, you know, AI will be as a personal assistant not only for executives, but for each employee in their work. It will be not just one person, it will be a person. And that particular, you know, AI agent or whatever we call won't probably replace leadership judgment and business understanding. That will be still required skills from, you know, from leadership from executives. But it will definitely dramatically improve decision making accuracy. We will have a more real time data for all the forecasts. And you know, now if we have information on a month end close quarter end close, we probably will have every day close information because it will be updating on a daily basis versus just closing the months.

I love the one of the continuous close that you said there. Right. Something we all want to see. It's been a dream of every finance person for a long time or at least a day one close, probably even a day two for most of us. Glenn, how long did it usually take you? I know you've worked a lot of small companies to come close those.

Yes. I mean so that was one of my. When I'd come in as a cfo, I would usually when I came in companies were like on a 30 day close cycle and I'd say how about I get us down to 10 and I think we ended up at 7 at one company. But yeah, it's, yeah, we small companies don't have the budget for blackline, you know.

Yes, but so my best month on close is probably two and a half, three days. But that starts with a lot of pre work which of course can be implemented because those are repetitive task, repetitive journal entries. Those can be all automated and posted by AI in future. So even that 3 day can be probably changed. But I can envision everyday information being available. We would just need to, we need to rethink all the processes. So entries which are posted, you know, once a month, like I don't know, payroll or some other information, we can divide them and post them every day to have that visibility on a daily basis.

I think we're heading that way. And you reminded me of a favorite quote I have kind of this conversation. We've talked about processes and technology. It's a quote out there that says new technology plus old processes equals expensive broken old processes.

Yep, yep.

You know, and it's going to require rethinking how we do everything. If you're not going to do that, then don't waste a ton of money to bring in new technology.

I agree and that's why I'm saying if I would start implementing robust AI solutions in finance, I would start with SOPs and clean line processes. Following stocks compliance, following whatever rules the company decide to follow. If it's not a public company but that where it starts. Because if your input is wrong, your output will be wrong too.

Yep. Garbage in, garbage out. Always has been, always will be. All right, so we have this section where it's kind of our fun little section. We use AI here. So we fed AI your the questions we had for you. You're a LinkedIn profile and asked it to come up with 25 personal questions to ask you. And so we, Glenn and I both take a different approach on how we ask the questions. So I'm going to give you two options. There's 25 questions. You can pick a number between 1 and 25 and I'll ask that question, or I can go to the random number generator and let it pick the number.

You can go to the random number.

You're like, it's all the same. All right, let's see what we get. It says 15. Not even sure what 15 is. Let's see. This is a, this is a good one. What advice would you give your younger self starting out in finance?

I would probably give an advice. Be open to the criticism and other people opinion and listen to what people have to say, not take it personally.

I had to learn that, you know, you're not alone. I had to learn that one too. That's great advice. All right, Glenn, your turn.

All right, so I take a different approach. I just completely turn everything over to the bots. And since we have AI generate the questions, I just ask it to pick one of them and give me one.

Sec, I'm already scared.

Okay.

Yeah. Oh no, this one, actually this would have, this would have been a follow up question that if we had a longer, if we had like Lex Friedman length podcast, I probably would have asked this anyway because it kind of goes with what you were saying with your origin story in the beginning. How has living and working across multiple countries shaped your approach to leadership?

It taught me that I need to accept different people, different cultures, the way they are. And I cannot measure people just using who I am. I need to accept them and learn who they are and allow them to be their true selves, which, which is difficult at the beginning when you start to be a manager because you, you just measuring everybody by like what, you know, what your experience is. So for me it's probably just just being open to different cultures, different opinion, different diverse environment and, and accept people as they are. I like to say, you know, my son plays soccer, so I usually use a soccer comparison. You cannot build a team of 11 goalies or 11 strikers. You need to have a team of different people and different talents. And it's my responsibility as a leader to place those people and those talents where they belong and develop them where they are the strongest. So that what I had to learn during this whole transition and changing the countries, moving through different countries and areas.

Perfect. Perfect. I love that answer. All right, well, this flew by fast. So we've covered everything we set out to and I think that some great insights. And Natalia, really, really appreciate you coming on the show.

Thank you for inviting. It was very interesting to share my perspective.

Appreciate it. Thank you again for joining us. It was a lot of fun and we look forward to having our audience get the opportunity to listen to this. I'm sure they'll love it as much as we did. So thank you, Natalia. I really appreciate it.

Thank you.

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