Adam Larson: 00:05

Hi, and welcome to this episode of Count Me In. I'm your host, Adam Larson. And today, we explore the critical interplay of artificial intelligence and ethics in finance. Our special guest, Srinath Ganeshan, the director of finance and risk solutions at SAP, shares his insights on how AI is revolutionizing the finance industry. Throughout the conversation, we discuss the transformative potential and ethical challenges of AI, drawing on historical analogies and looking ahead at the need for robust regulatory frameworks.

Adam Larson: 00:35

Join us for a thought provoking discussion on harnessing AI responsibly in the finance and accounting sector. Sreed, we're so excited to have you on the podcast today. I'm really excited to be talking about AI and the ethics of AI. And I figured we could start the conversation by talking about, you know, maybe you can start by sharing your perspective on the importance of ethics and AI, especially in the context of the finance team.

Srinath Ganesan: 01:02

Hey. Thank you, Adam, and thanks, IMA. It's my pleasure as well to share my perspectives on this topic, which is very sensitive, you know, which is also on top of all different leaders as we speak now. Right? So I am a, took a right decision of taking this topic so that as financial leaders, we share our perspectives to the community and, bring that perspective.

Srinath Ganesan: 01:24

And see what I see, what I see from the perspective is this is we should not look at this as one more technology. Okay? This is this is, after Internet. AI is the most breakthrough technology that as humans we are facing. Okay?

Srinath Ganesan: 01:40

And as professionals, we need to gear up ourselves how we are adopting this AI to our maximum. Okay? There's nothing to fear about it, but how do we how do we adapt and how do we realize the potential of AI is very, very important not just for the all of the persons, but even for finance professionals, it is very, very important. And, needless to say, as Internet evolved, there were ethical considerations. Similar to it, AI will evolve and ethical will also be considering part of it, actually.

Srinath Ganesan: 02:12

So ethical ethics is embedded as part of the AI technology itself.

Adam Larson: 02:18

Mhmm. So as, you know, as a a leader in finance yourself, how do you think that AI is gonna transform the role for finance leaders? And I think it's a question that a lot of people have been asking themselves, and the role of a leader.

Srinath Ganesan: 02:37

Very good question, Adam. What before I answer that question, let us let us go back, some 30 years ago. Okay? When computer was created, then then then we were all using calculators. Right?

Srinath Ganesan: 02:50

Okay. We're all use when calculator came, people's mathematicians and accountants, where's CAD, whether calculators would take away, know the job of, accountant. Okay? And more or less like auditors, would calculate the help, calculator will be an enabler or a disruptor, actually. Okay?

Srinath Ganesan: 03:08

Then came Internet. Then when the Internet, then the computers came in computers, we got calculator. Okay? Just 15 years ago, the the best friend of, accountant, the Microsoft Excel came in. If you ask today, no accountant can live without Microsoft Excel.

Srinath Ganesan: 03:26

Right? So as technology evolved, as softwares came up, okay, the people, the professionals embraced up with both their hands. Okay? There were fears. There were concerns.

Srinath Ganesan: 03:38

There were disruptors. But for it, with every disruption, there was an opportunity. Right? And and that's all this opportunity, people suffered, survived. And I'm sure as part of AI also, we are definitely going to embrace it with both hands.

Srinath Ganesan: 03:53

We are going to make use of AI for the betterment of the account then. Okay? As we as we progress in the podcast, I will be happy to share lot of, use case examples how AI would help the finance professionals.

Adam Larson: 04:09

No. I think that's a great perspective. Just reminding us that how over time technology has always changed us, and so we just have to adapt as leaders, as professionals. We have to adapt as that's going along, and I think that's a really important thing to keep in mind that AI is another tool. It's a very powerful and important tool.

Adam Larson: 04:26

We can't forget that. Our jobs will change, but the the the whole foundation of our job is still the same as to be great financial leaders, to be great leaders in our in whatever profession we're in. And especially in finance and accounting, AI is just gonna be another tool that's gonna help transform and make us better at what we're doing.

Srinath Ganesan: 04:43

Yeah. Yes. Definite, Adam. You you touched the right point. It will be going to be enabler rather than a disruptor, actually.

Srinath Ganesan: 04:49

Mhmm. Okay? So as people embrace new new devices, new new methodologies. Right? New new regulations coming in.

Srinath Ganesan: 04:57

Right? So this is going to help it rather than just we get concerned about whether it is going to take every major job or etcetera. Mhmm.

Adam Larson: 05:04

So when we're thinking about AI, what are some key ethical challenges that will that leaders will face when they're implementing these technologies?

Srinath Ganesan: 05:12

Definitely. Ethics is, one of the biggest concerns today the leader space, not just the finance people, but across, the different spectrum of professionalism, their ethics is a major concern. Okay? But if you look at if you look at, the way, even without AI, probably, I'm just again going back, 2 decades back. We had very, very good use cases when, know where, where we had a SOX regulation coming in.

Srinath Ganesan: 05:39

Okay? Then we had some investment backing came across, you know, fraudulent cases coming across. Okay. Even though we thought this AI, even though we thought software, there were many multiple scenarios that organizations misuse the regulations. Okay.

Srinath Ganesan: 05:56

With AI, it is getting more concerned. Mhmm. How something can be easily farged or easily manipulated or in the technology world, bird, they call it deep fake. Right? Mhmm.

Srinath Ganesan: 06:09

It is not just human. Can the numbers be deep fake? Can the whole balance sheet, trial balance, profit and loss statements, or the fundamental compliance requirements for different regions? Can that be fudged? Mhmm.

Srinath Ganesan: 06:21

And and as a matter of time, there is some use case coming across some one of the organizations that this organization must be able to create a whole set of data, which is created by AI. Okay? We have seen AI creating emails. We have seen AI creating good images. We have seen AI creating movies.

Srinath Ganesan: 06:40

It is a matter of time that AI create a good accounting document. Okay? But for all this, what we need is a typical guardrail. Okay? Guardrail bad, the finance professionals coming together and create regulations, create quality, create very specific internal controls for AI programs.

Srinath Ganesan: 07:02

Okay? Today, very few organizations are thinking about these lines. Okay? And, I'm I'm pretty much sure, association like IMA, CPA, and major global bodies, no, brings up certain policies which are going to help in creating this guardrail.

Adam Larson: 07:18

Yeah. I think it's extremely important to create those guardrails because it it's almost like the wild west. People are putting that technology into their their they're adding it into their softwares that they already have or or individual employees are using it for their daily jobs. But if you don't have the that overarching guideline from a organizational perspective, you don't know what people are gonna use it for. And I think it can be very dangerous, but it also it can be exciting.

Adam Larson: 07:40

It's exciting to use new technology, but you have to you have to find those parameters. I and I think you're right on right on point with that.

Srinath Ganesan: 07:47

Yes. Definitely. You also touch a very good very good point, Adam. See, if you look at the technologies. Right?

Srinath Ganesan: 07:53

Today, if you look at, different different softwares come in Mhmm. For the enterprise, very specifically speaking about enterprises, we have, no ERPs. You have sale you have CRM. So you have recruitment solutions, which is all typically solution which is enabling the business. Mhmm.

Srinath Ganesan: 08:09

And if a is going to touch upon this enterprise applications, okay, which is the critical data of most corporates use it. Okay? The ethics part becomes very, very important for policy to be implemented. Okay? And that's where businesses need to be cautious, and especially if the CFO community or the finance professional community has to be doubly careful what they are signing up.

Srinath Ganesan: 08:32

Right? No. The when they're saying the balance sheet or they sign up the trial balance, they are doubly cautious that they are signing up without any major intervention from the platform. Mhmm.

Adam Larson: 08:42

Now do you think that things like bias in AI algorithms can impact decision making and the use of AI. You know, I know that that's been a a topic, and especially when you have when you have AI learning from all of the Internet and all those things, there are certain biases that are kind of underlining things that people may not realize. Are there things that we should be concerned about, especially when using AI with finance in the finance community? And are there steps to help mitigate those risks?

Srinath Ganesan: 09:07

Definitely, Adam. So if you look at bias, it's a very, very sensitive topic. As humans, we are biased. Right? Let let let it alone technology.

Srinath Ganesan: 09:16

Even as humans, we are biased, but we have come across that barrier by putting controls. Right? By proactive thinking. Okay? By creating policies with within the organization, how we could able to work them.

Srinath Ganesan: 09:29

Okay? Similar to this, AI is an evolving technology. Right? It is it is it has to be fed right to give us back. In technology, I'm sure you would have heard about it very often.

Srinath Ganesan: 09:41

It is nothing but garbage in, garbage out. It's called the Gigo. Mhmm. Right? What you fed is what you get.

Srinath Ganesan: 09:47

And with LMS, with FLMS, with, multiple language layer coming across, AI may act little smart, may have some bias, but it is up to us who the people who are going to codify the AI. What algorithm that we ask. Okay? What other what is that we wanted from AI is for us to define. Mhmm.

Srinath Ganesan: 10:11

Okay? And especially from the finance perspective, since finance is a very wide topic, let it it touches support investment banking. It talks about insurance. It talks about global trade. It talks about compliance.

Srinath Ganesan: 10:24

Okay? Bias would help would come in good would come across. Okay? But how far we are good or adapt on adopt this non biased attitude towards AI platform will set set apart. Okay?

Srinath Ganesan: 10:38

So technology like ChargeGPT or Jiminny, whichever is coming across, are day by day evolving and removing these barriers 1 by 1. Mhmm. And, and and definitely, as days goes by, this not only bias, but the intelligence of AI would make it more, smarter for us to use.

Adam Larson: 10:58

Yeah. And the smarter it becomes, the better it is, the better of a tool it'll be for us to use it. Now do you think it's important that technology companies have transparency on what services and what elements within their technology is using AI? Do you think that it's very important that they use that transparency? Because, you know, people have been using machine learning and those types of technologies for many, many years now, and people didn't may not have realized, like, the code behind the the the technology in the past.

Adam Larson: 11:24

But now with it's such a with it being such a prevalent thing, is it important that they have that transparency? And is there an important relationship between that that and trust?

Srinath Ganesan: 11:32

Yes. Definitely. And that's a very good sign also, Adam. So if you look at today's large organizations, right, that it be Google, Apple, SAP, Oracle, or, no whichever organization which comes across as a very large players. Right?

Adam Larson: 11:47

Mhmm.

Srinath Ganesan: 11:47

Even before they bring the AI to common use. K? They have taken steps to be more ethical. Okay? And they are they are they are responsible organizations in creating these guardrails, creating policies, creating creating such a kind of software, which is only for a betterment of a community.

Srinath Ganesan: 12:08

Right? Rather than rather than thinking about coding, rather than thinking about the end use of this application. Okay? They have actually thought about it as a very responsible organization as I mentioned earlier, and they have put this practice in coding itself. Mhmm.

Srinath Ganesan: 12:22

That's where if you see Microsoft, Google, SAP, or large organization, they have created AI policy, AI ethics as part of their coding. The a, no quality policies, AI standards, before release. Okay? And this is going to help not their own companies, but also the users of this platform. Okay?

Srinath Ganesan: 12:42

For example, you and me, when we are going to use, a platform, today, we don't think twice before asking certain queries. Do we think we just we just read it. Right? Thinking that the answer would be right. The results would be right.

Srinath Ganesan: 12:57

Okay? Unless until our intention is bad to get something to a number. But from their side, often the coding perspective, from the technology invention perspective, those things are taken care of it. Okay? That could be one of the exceptions, but largely large players, they have their own regulations.

Srinath Ganesan: 13:15

Okay? Not really from this perspective, from a regular perspective, let it be the US government, let it be the European Council, or let it be the UN large financial bodies. Like, even in fact, IMA or if you take IFRS, they also have brought a ethical standards, a kind of a booklet, a kind of a policy guidelines to be followed. Okay? And such things help AI to be more regulated, okay, and more intelligent for the, business and the finance and especially for the finance professionals going forward.

Adam Larson: 13:49

Now how important do you think regulations are from a governmental standpoint? Like, whether it's the US, the European Union, the UN, you know, India, whatever wherever the listener is, how important do you think regulations should play in the development of AI and especially AI practices? You mentioned a little bit in your last your last answer, then you talked about how organizations individually should have their own AI policies. But how important do you think it is that that you have the overarching governmental, what kind of regulation, whether it's a whether it's a body like IFAC or or IFRS or or, you know, different regulation bodies? How important is that?

Srinath Ganesan: 14:21

It's very, very important. Okay. See, in fact, if you look at, I'm just going back again. When Facebook came or when the social media, I know, there's a boom of social media. Nobody regulated.

Srinath Ganesan: 14:34

There was no regulations. Right? Mhmm. It evolved, actually. Over a period of time, organizations, the governing bodies, the regulated bodies woke up.

Srinath Ganesan: 14:43

What is the power of the social media? And they went back to the whiteboard, created policies, created ablations, how of how this could be used, how if there's a misuse, how it has to be controlled. Yeah. Right? And all and similar way, AI is also evolving, and it is a matter of time that there's a big regulatory body or arching arching body, which comes out in a bit standards, how to use, what not to misuse, how it can be done.

Srinath Ganesan: 15:11

And not only from a global way, every individual countries have now started to create regulations. Okay. If you look at India, we have the we are now in the digital wave. Okay? So we have a regulatory body for finance, regulated body for, social media, regulatory body regulatory body for AI, ethics.

Srinath Ganesan: 15:30

And, like we are speaking now, people are breaking up how ethical or how what what kind of guardrails from a regulatory standpoint of view is needed to manage the AI available?

Adam Larson: 15:42

Yeah. I think that's really great because it's almost like you kinda need the technology to start. You need the the regulation bodies need to see how it's being used, and they need to understand themselves. So it kinda needs that you need that transition period of of people watching it, seeing how it's using, and then they can make their policies.

Srinath Ganesan: 15:57

Yes. Definitely. It's it's like a new, regular financial regulation. For example, if you look at international trade, no. Your trade between Europe and US, but a free trade.

Srinath Ganesan: 16:08

Okay? Then slowly when, when the situation started to move across, they started to create some embargo. They started to create some controls. Right? Same way that South America was Europe.

Srinath Ganesan: 16:19

As the as a like a trade, even this is, like, another trade. Okay? So it has to be observed. It has to be, created new policy to be created. And and, it's a matter of time that comes, you're going to come across globe, actually.

Adam Larson: 16:33

Mhmm. No. It makes a lot of sense. Now as you're observing the the emerging technologies coming out, especially in the finance sector, are there any certain ones that are kinda raising new ethical questions that you that we haven't asked in the past?

Srinath Ganesan: 16:45

Okay. Actually, to be very honest, we were able to compare with the, I'm sure you have heard about it, the elephant story. Right? Mhmm. Five blind men touching the an elephant, one touching the tail, one touching the trunk, one touching the leg.

Srinath Ganesan: 16:58

Feeling this is a different different animal. Right? One one is still one is touching a tail and calling it a snake. 1 is telling touching the trunk and calling us a different animal. Right?

Srinath Ganesan: 17:06

Same way, what is happening for AI is also everybody are touching different different parts of AI. Right? And their perspective is getting based upon their perceptions. Why I'm giving this example is unless and until everybody who are part of the AI Council or AI users or a developers come together and create a kind of, ecosystem that this is how AI has to be used. Right?

Srinath Ganesan: 17:35

It it needs a it needs a common platform. Today, like Internet, I'm, what I told no. Like, Internet, there's a one one general body across global. AI also need a general body to manage it. Mhmm.

Srinath Ganesan: 17:47

And, definitely, finance professionals from IME, CPS, low well, professionals has a saying how this has to go in to get affected for the finance. Right? Mhmm. Why am why am I supposed to think about finances? People are more concerned on their investments.

Srinath Ganesan: 18:05

Right? People are concerned about their stocks. Right? And, I'm sure you know we we are small bad news, about a stock listed company will create a ripple effect on its revenue. Yeah.

Srinath Ganesan: 18:17

Okay? And a there's a very, very important role of how such thing doesn't happen for a list of organizations.

Adam Larson: 18:24

You know, I think you bring up a really important point, especially with your example, the elephant example. I I have heard that in the past, but it's been a long time. So that brought a smile to my face because it highlights the importance of the diverse the the importance of diversity of thought because everybody has had different experiences growing up. They've had different experiences whether with the jobs they've had, with their environmental, where they live, the people they've interacted with. So when they see something new, when they see a new technology like AI, they see it from a their perspective.

Adam Larson: 18:51

And unless you bring a number of different perspectives to the table, you cannot have great regulations. You cannot have a well rounded perspective on how this new technology is gonna impact us and and how it should be regulated, how it should be used in all those different ways. And so I think you bring up a really great point that diversity of thought is so important when we're dealing with new technologies or actually anything within business within our lives. Diversity of thought is extremely important.

Srinath Ganesan: 19:15

Yeah. Definitely. Yes.

Adam Larson: 19:17

So how do you envision the evolution of ethics and AI and the impact on the finance sector as we look into the future, as we look into how things are changing? And it's changing very rapidly. Like, if we have this conversation 6 months from now, your answers, your our conversation would would probably change slightly. And 6 months after that, it's gonna change again, and it's rapidly changing. How do you think how do you envision this evolution as we go forward?

Srinath Ganesan: 19:38

Yeah. There could be multiple visions of AI coming in, like Chargebee 3.54.0 coming. Yeah. You'll also have a different versions of it, different avatars coming into picture. Okay?

Srinath Ganesan: 19:50

But from a finance sector, what are the view that I'm, I'm having is this is going to be a platform on which we could trust our instincts on it. Mhmm. Earlier, if we look at, earlier, we we used to depend on a small small softwares like Excel. Then it came ERPs came in. Mhmm.

Srinath Ganesan: 20:10

ERP ERP became a very collaborative platform between multiple functions like the way SAP works. Right? So similar ways, it it's a new platform. A will also become a platform on on data which we can trust. The reports for this coming on from AI, we can trust.

Srinath Ganesan: 20:28

Okay? It is going to be a it is going to be a, like, a tool, which is going to be my go to platform. Yeah. Today, if you are today, the way how we are handling mobile. Right?

Srinath Ganesan: 20:37

Today, we can't live without mobile. Today, we can't live without, enough food. Okay. A basic the our basic instance go to handphones. Right?

Srinath Ganesan: 20:46

Like that, AI softwares or AI platforms would be, would be the go to platform for any kind of activities. Mhmm. Let it be our basics like, no, emailing functions or record keeping, bookkeeping, or do a very holistic analysis of reports. I'm sure I want just want to take this opportunity to give an example. Right?

Srinath Ganesan: 21:09

How already our relations are using AI from the finance side? Example is if you look at annual report preparation or trial balance preparation for a listed organization, preparing an annual report of, say, 100 pages, okay, would take minimum, say, 7 to 10 working days. Even with the wordless software, book closures, plus also preparing that booklet, preparing an auditor statement takes time. Yeah. But even the advent of AI, with the data available, AI is becoming, as a very good assistant in preparing the document in a matter of, say, 60 minutes.

Srinath Ganesan: 21:46

Mhmm. Just imagine how much productivity I would have gained. From 7 working days to 60 minutes, the finance CFO's productivity has gone up by huge percentage. This is one one way. 2nd practical example I could tell you is the stock traders.

Srinath Ganesan: 22:03

No? The investors. If they want to read a company's annual report. For example, tomorrow, I want to invest in a a New York Stock Exchange. I want to talk about, say, a a large organization.

Srinath Ganesan: 22:15

Let us take Nvidia. Okay? This is the top of the town today. Nvidia, that is, if I want to invest in Nvidia and I want to know the balance sheet, okay, I I if I'm going to read, you know, it may take some some hovers together. But if I give it to a in a decision and summarize me how this stock could be able readable, it can it can summarize and tell me, yes.

Srinath Ganesan: 22:37

This is the go to company. This is the go to stock. Yeah. So and it's it helps me in summarizing. It helped me in digesting the facts, and, it is going to help me how how the, you know, future of of this company, future of this technology is going to help me out.

Adam Larson: 22:53

I think those are some really great examples. And I think as we continue I think this is a conversation that's gonna have to continue as we go forward, as we observe what's happening in the industry. I think we're gonna have to keep having these conversations as leaders. On this podcast, we're gonna keep trying to have this conversation because it's gonna not stop. It's not gonna end.

Adam Larson: 23:08

It's gonna continue to evolve. And so I really appreciate you sharing your insights with our audience today, Sri. And and I'm really excited to see where this conversation goes as we go forward.

Srinath Ganesan: 23:20

Sure, Adam. Yep. Thank you. I think I think, thanks to IME. Thanks to Adam for asking, no relevant questions, which triggers me.

Srinath Ganesan: 23:27

Right? It is not the examples which I say, but the the question that you ask regards my thoughts. And that ideas flows automatically because we, day in, day out, meet lot of, finance leaders, lot meet lot of finance champions, CFOs. And as a common platform, we all discuss in multiple forums on how how to safeguard Mhmm. Not just a profession, but also the, you know, the whole ecosystem of finance.

Announcer: 23:53

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