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Advances in Risk Technology – Commodity Risk & Finance 2024

todayJanuary 22, 2024

Background
  • Are CTRM/ETRM systems keeping pace with traders' needs in today's markets?
  • How is AI being used to help assess and model risk and make robust business decisions?
  • The changing face of data management and security

SPEAKERS:

Alvaro Mariani, Senior Risk Manager at RadarRadar
Glenn Labhart, Partner at Labhart Risk Advisors
Jacqueline Hallmark, Manager, IT Cyber and Information Security at Just Energy
Kaley Crane, Managing Director at Ernst & Young

Transcript

HOWARD WALPER, CEO AMERICAS AT COMMODITIES PEOPLE

Hey, folks, welcome back to the second.

In our series of today's webinars, which will be focusing on risk technology. Once again, if you weren't at our last session, I'm Howard Walper, CEO for the Americas for Commodities. People, we're right in the middle of our focus day on commodity risk and finance. So without further ado, I'm going to turn the floor back over to Glenn Labhard from Labhart Risk Advisors. Glenn, the floor is yours, sir.

GLENN LABHART, PARTNER AT LABHART RISK ADVISORS

Thank you, Howard. Welcome, everyone this morning to risk and our advances at Risk technology. We've got a really good panel here today, quite diverse to address the circumstances surrounding technology. We'll follow along with some different comments, but first, let me introduce the panel. As you're seeing us from left to right, let me introduce Kaylee Crane, one of our sponsors from Ernst Young. She's been in the business quite a while with Accenture previously, but more in her career as a managing director with Ernst Young, focusing a lot of her time on the global development in commodities with regards to processes, people, technology. Very experienced person that you're going to be speaking with today, Avaro Marini, I hope I said that correctly, is a senior risk management at one of our sponsors, Radar. Radar. I like that name. I love that name. He's transitioned from the banking sector, so he's been with us on the energy side. I would say what we've been here now six years. Good for you. It's always hard to go from banking to here. So focusing on a lot of his challenges in market risk, on value at risk, he plays a very pivotal role in the expertise that his company provides, helping clients with processes and tools, a lot of advanced work. So we'll hear a lot from him on his expertise today as applicable to the technology. Jacqueline, she is the manager of IT cyber and information security for just energy. She is very impressed. We spoke yesterday and kind of always pre interview everybody on these things. She's got a really good background with an MS in focused on computer and information systems. And I think that she'll be able to give us a really good flavor as to, not so much as we talk about on the panel of just technology, but a whole lot of things related specifically to cyber and IT security and things of that nature as we move ahead. So I want to thank all the panel members and we'll go ahead and just jump right into this. Let's just talk about the first one right now. Let's just kind of grab it and put it in the box here and talk about just ETrN systems, are they keeping pace right now? Do we have what we need? Are they on pace with what the company or. It's two different questions, I think to say it's in the company or the traders needs. So that may be two questions. I'll let you answer it that way. As you please. Katley, why don't you take the first question for us?

KALEY CRANE, MANAGING DIRECTOR AT ERNST & YOUNG

Happy think. You know, from an ETRM cTRM perspective, we went through this period of time where everybody was highly customizing their systems to meet their needs. And I think we're coming to a period where now they're having to upgrade those systems and they can't upgrade them, or they're very complex and very expensive to upgrade. And so turning to newer solutions that are coming on the market. So we're seeing a lot of newer, more modern, next gen kind of eterm systems out there. Some software as a service platforms that you're paying subscription fees, not licensing fees, moving to the cloud, which was propelled by Covid and being able to work remotely, and then just the availability now of all these digital tools. So we're seeing core etherm out of the box, enabled by digital tools around that core etherm system, really kind of modernizing the entire.

GLENN LABHART, PARTNER AT LABHART RISK ADVISORS

Okay. Okay. Let's put perfect segue for you. Alvaro, you've got a product here.

ALVARO MARIANI, SENIOR RISK MANAGER AT RADARRADAR

Yeah.

GLENN LABHART, PARTNER AT LABHART RISK ADVISORS

Let's talk about the systems keeping pace with there. This is your plug.

ALVARO MARIANI, SENIOR RISK MANAGER AT RADARRADAR

Thanks. Thanks, Glenn. Yeah, I agree with Caleb on the general direction. I think we've seen a lot of progress. Right. And we've seen a new generation of ctrms that just can handle much more. We still see some challenges, however, on what I call that, perhaps crms are still in some sense, very accounting centric. Right. And when you start to move to more risk management, especially when you're looking for more, for daily reporting, at least an end of the reporting, perhaps we still see some challenges there. So just to be concrete, right. So, for example, Martin markets a classic, just really a starting base for risk management. And you see a new generation of CRM that can handle absolutely that from an accounting point of view and can actually produce good data. But when you try to, can I look at the pricing complexity and the logistical complexity that is in that March market to come up with a risk exposure, there is still a gap, perhaps there. And that's where you're seeing a lot of clients just asking us, okay, we have that data. Can you translate that into something that the business can really use? And having just that data model and that experience has helped so I think that is one thing that is important to keep in mind. And then once you have that right, when you have that risk exposure well resolved and you have your mark to market, connect to that, then you can start stack layer of more advanced risk management, like risk metrics, like valid risk option analytics and stress test and so on, so forth. So that's a lot of what we see. We see that crms did a lot of work, but there is one layer that's perhaps it's really not their core. And perhaps it's also worth mentioning that for big clients, for example, there's still system fragmentation, right. And part of it, it's natural because you have different business, you have an origination, you have an export, you have a trading, and you always want the best tool for every situation. So having something on top that can aggregate all these different crms and produce one logical view, we definitely still see the need for that.

GLENN LABHART, PARTNER AT LABHART RISK ADVISORS

Okay, very good. Jacqueline, your opening statement. Is everything keeping pace from your end? You have an interesting occupation. I'm very interested to hear your comments.

JACQUELINE HALLMARK, MANAGER, IT CYBER AND INFORMATION SECURITY AT JUST ENERGY

Yes. So for our business right now, I would say no. There's a lot of transition that still needs to occur. Transformation from on premise to cloud infrastructures. There's a lot going on with proprietary data that utilizing these new cloud based systems that have AI integrated in it, you have to train these models. And I think that we're probably going to see more on pace within the next five years. Right now, we had that big push, like Kaylee said, because of COVID where you have a lot more people working remotely, you have people accessing systems, you see a lot more of software as a service coming out, but it's still requiring the company to keep up to pace with those. You still have to feed the information into the systems, gathering the information, making sure it's accurate, checking the validity of it, checking the integrity of it. Is it outdated? How do we get to where we need to be with these new systems in place? So I would say that we're not quite where we need to be just yet. There is a lot of advancement in technology, and it's outpacing the way that the market is going right now. But I think within the next five years, we'll start seeing more of a cohesive structure with the change in technology to how businesses are using to adapt and to drive those business decisions.

GLENN LABHART, PARTNER AT LABHART RISK ADVISORS

Haley, do you think we're there? We got a lot more work to do. Is it going to take five years?

KALEY CRANE, MANAGING DIRECTOR AT ERNST & YOUNG

Yeah.

GLENN LABHART, PARTNER AT LABHART RISK ADVISORS

Jacqueline just said.

KALEY CRANE, MANAGING DIRECTOR AT ERNST & YOUNG

Yeah, I completely agree with what Jackie said. The technology is there. We're getting there. I think we have a lot of work to do to get the systems up and running, the more modern systems in place. Get onto the cloud, get our data right, consolidated right, get all the integrations right. And I do think probably five years, we'll start seeing that and be able to enable the more advanced analytics, the AIS, the machine learning technologies that are out there.

JACQUELINE HALLMARK, MANAGER, IT CYBER AND INFORMATION SECURITY AT JUST ENERGY

And it's a learning process, too. With AI coming out, everybody's like, oh, what is this? Let's jump on. It's a new shiny toy. But as you start getting into it, how do you know that the data being generated out is accurate? You have to have people that still understand the basis and the foundation to check that the authenticity and integrity of it is accurate. You'll start seeing companies start putting more guardrails in place. How do we know that the information that we're feeding into these AI models are staying within our premises and not being shared through third party agencies or going out into the wild, the cloud. And so I think that companies will start taking a step back and putting in some controls as they review. This is uncharted territory for majority of the people. So it's a learning process as we go.

GLENN LABHART, PARTNER AT LABHART RISK ADVISORS
So we're kind of identifying here, people, processes, and systems. We talked about this in the prior session, and certainly people is, hey, people have been working remotely. Does the process work to get it all into the system properly? And does the system compute it? So I'm going to come back to you, Alvaro. You mentioned a lot of things you've looked at where some people obviously need value put together with which to communicate in a working document that goes to a financial statement of level one, two, or three, or any kind of financial disclosure and market risk. Do you see this as something where the industry's got to do a better job, or is it adequate? Can you comment from that angle?

ALVARO MARIANI, SENIOR RISK MANAGER AT RADARRADAR

Yeah. So I think one takeaway, perhaps, that we could give is we always try to advise our clients against the approach of having simply saying, let's have a representative of the business in the IT project, right? That really hasn't give the best results. And the best results is when you have the technology people really curious, right. And really engaging and themselves trying to understand the business, if not the business driving the technology, which is something that we can discuss, perhaps more later. So that's one takeaway that we'll definitely take. Avoid the idea, oh, let's have a technology project, and then I'll have someone of the business to just chip in. That's not the way to go.

GLENN LABHART, PARTNER AT LABHART RISK ADVISORS

Okay. It's interesting in technology or just information in and of know. I come from a background where I've worked in a company that had the early stages of what was now, I guess it's now known as endure. We called it then open link and then we called it abacus. Back in my days at Diaz and I've watched this system morph and other systems develop off of that. Just from a perspective of architecture before we move know, a holistic system that has a one stop shop of data entry into a bigger system that processes everything. Is that realistic, Kaylee, for somebody to be able to put something like that? Or is there a problem having two or three different systems that do everything? I've been asked this questions many times, so I'm just kind of curious.

KALEY CRANE, MANAGING DIRECTOR AT ERNST & YOUNG

Yeah, I think the endurers of the world still have their place in the market and companies that it makes sense for, but we do see a lot of clients kind of moving more to kind of best in breed. Right. So certain systems for certain commodities moving that direction. I think the key there is that's doable, that's great. It gives you the functionality you need. You just have to focus on the integrations between the systems and between consolidating all that data, as kind of ovaro said earlier, so that you can do all the risk monitoring and reporting off of.

GLENN LABHART, PARTNER AT LABHART RISK ADVISORS

Know, I would say, look, as the client base that I serve, I've seen a lot of different books on a lot of different systems and it's interesting, but it's a matter of does the company have the architecture with which to support the views and can it capture all the risk and can it capture it properly? Certainly from a market and credit risk perspective, which obviously then feed to financial statements and then the other elements of it, as Jackie can allude to. For us here in a second, a little more about the cyber and everything being of quality. So let's move into that for just a second about changing face of data management and security. Let's focus on the it changes of cyber a little bit. Jackie, why don't you lead us into that topic? Would you do that 

please?

JACQUELINE HALLMARK, MANAGER, IT CYBER AND INFORMATION SECURITY AT JUST ENERGY

Yes, absolutely. So one of the biggest challenges that we see with the changing landscape of data management and security is around cloud adoption and the integration with the advanced technologies. So as you start integrating in the CTRM ETRM systems, to your point, going through best in breed across multiple systems, you need to have an API manager that's going to connect and bring all of the relevant information into like a single pane of glass, if you will. And so with that, you need to validate how these systems are working together. Some of them may not even know about the other, so you've got to bring them all in house. But there's risks that come with that. The exposure that we're seeing often, more often than not, is around third party risk association, making sure that you have data privacy covered, that there's regulatory compliance, how you're utilizing the data and validating it, and making sure that you're protecting and putting guardrails in place to prevent or mitigate the cybersecurity threats. One of the biggest threats, of course, is phishing. And this is how most of the threat actors come into the environment. And so you want to have monitoring in place to make sure that your data management and the security is following the traditional CIA, the confidentiality, integrity, and authenticity and availability of that data. And so that's really what's going to set the standard going forward. Whenever you are integrating into these new SaaS platforms or new cloud adoption systems, is just making sure that we are tying all of those pieces in together. Security is often an afterthought. Most companies tend to be reactive when it comes to security, and it's a breach that's happened or an issue. My recommendation for companies is to ensure that you include security when you're designing these ETRM CTRM system upgrades, integrations, and making sure that you are looking at it every step of the way to ensure that you have some type of risk strategy associated to how you're going to manage those risks going forward.

GLENN LABHART, PARTNER AT LABHART RISK ADVISORS

So let's take that a little bit of a different thing. I'm going to do a little follow up with you here. You got the whole industry out here developing new products, apps, different platforms where people are executing transactions, WhatsApp directly to ice brokers, so forth, so on. All these new products are available here, sitting behind your desk and looking at all this. How do you manage something like that? So that it's kind of like, like you want to make sure you edit what's in Santa Claus's bag, so not everybody gets what they want. You give them what you need so you don't blow the company up. Parallel to that for me, just a little bit as to how you handle that in your organization or in the industry.

JACQUELINE HALLMARK, MANAGER, IT CYBER AND INFORMATION SECURITY AT JUST ENERGY

So at first, my immediate reaction is block it all. But we know that that's not feasible because people are going to find ways to get around it and use the systems. And so we try to incorporate. What are the feature sets that you're looking at when you're using these third party apps? What is it that you're tying in that we need to ensure that you have in your environment? We don't want to disable the workers from being able to do their jobs. We want to ensure that we're helping them and we're also maintaining that secure environment. So our goal is just to put some controls in place, put some guardrails, set some standards regarding acceptable use policies, and making sure that they're being enforced. Like if they're using WhatsApp or they're using these third party chats, making sure that information isn't sensitive or proprietary to the company that could be infiltrated by another person. And so we try to look at product sets as well. And AI has definitely thrown a loop for us because it spreads like wildfire. Once somebody has a shiny new toy, everybody else wants to jump on the bandwagon and be like, oh, I need that. But you have to be very careful because a lot of these third party companies, again, can do whatever they want with your data. And if you're not reading the privacy agreements, you're agreeing to give them access to act on behalf of you. And so we saw this recently with read AI as a product set. It acts as a virtual assistant, goes in, records your meetings, it gives you summarized notes. It's fantastic. It's a virtual assistant. However, that virtual assistant can also act on behalf of you in setting up meeting invites, sending out information, reading your emails, reading your transcripts, and also utilizing that data through subcontracted parties and processors that now your data has exited out of your internal environment. And so when we look at that, okay, this is a new feature that has come out into the market. What do we need to do to enable our employees to be able to utilize that? Because Microsoft may already have something that we can use and keep it and contained in our environment, and then just making sure again, that the employee awareness and training is there so they understand the risks that they're undertaking. I know a lot of people like to do it and then ask for forgiveness later. But when it comes to your company's data, that's gold. That's your asset right now. And if you're not doing everything you can to protect it, then you're creating bigger problems in the long run.

GLENN LABHART, PARTNER AT LABHART RISK ADVISORS

Yeah, you're increasing the risk as opposed to managing it. And the way you describe that in my head, it reminds me of the skit in Saturday night live years ago with John Belicia, the thing that wouldn't leave, you attach yourself to that system, you can't get rid of them.

KALEY CRANE, MANAGING DIRECTOR AT ERNST & YOUNG

You chase them down forever.

GLENN LABHART, PARTNER AT LABHART RISK ADVISORS

You spend your whole day figuring out how they're in your system, how to get rid of or as opposed to an inbound transparency with the blocks controls, all the things you've mentioned, Avaro, on your case here, changing with data management and security, how's that affecting this as far as marketing credit risk requirements that need attention? Can you be specific with us 

and talk to us a little bit about that?

ALVARO MARIANI, SENIOR RISK MANAGER AT RADARRADAR

Yeah. So as you say, as we've been discussing, right. We have a wave of new technologies coming in and we definitely always want to understand which problem we're trying to solve before adopting any technology. I would be general advice, be careful with just following the buzzword, right. You want to have that clear understanding of the problem that the technology is supposed to be resolving. And in that sense, just having technology partners that understand the problem and not only the technology makes a lot of sense, but it is an exciting new world. And yeah, we also have a lot of projects related to AI and this type of new technologies.

GLENN LABHART, PARTNER AT LABHART RISK ADVISORS

Haley, why don't you take that question as well with regards to the changing of data and security and kind of from your angle as you're looking at something, what's the biggest thing you're looking for? To make sure that data management and security is adequate in any kind of project that you lead.

KALEY CRANE, MANAGING DIRECTOR AT ERNST & YOUNG

Yeah, and I think Jackie kind of mentioned this earlier, but I think the key coming from a consulting firm, because we look at a lot of things that do go wrong or try to prevent things from going wrong, it does come down to all those controls in place. So one, making sure you've got the policy written out, the training there for your people, putting in place the adequate controls to make sure you know what's going in and out with your data, but then also the monitoring of it. Right. So how are you monitoring that on an ongoing basis to detect anything that may intentionally or not intentionally be going wrong within your data. So a lot of that, yeah, data.

GLENN LABHART, PARTNER AT LABHART RISK ADVISORS

Integrity, I think you're hitting the nail on the head. It's everything. And you've almost know what I think Jackie pointed know, you've got to keep people from being a victim to themselves to a large extent have training, communication, KYC things. We're kind of getting into the compliance area a little bit, but these are very highly important areas because once they're in and then trying to maintain a flow of constant data, especially if you're on a large scale can be very difficult, and two or three days can really jolt what you're trying to do in an industry if you have one little problem like that gone wrong. Is there anything. One thing in particular. I'll just ask this of everybody that you look for. Since I asked you that question, I'll go over to Alvaro for a minute. Alvaro, kind of, as you're seeing something from your side, what's the one thing that you're looking for that kind of gets your radar going? I can't help you install my system because of this. What are you looking for?

ALVARO MARIANI, SENIOR RISK MANAGER AT RADARRADAR

Can help me install? Yeah. So I think one word to keep in mind is integration. Right? Really? The word is, give an example. Data lakes. Right. So they're fascinating technology. We integrate really well with data lakes. Right. But just having every toy in the same pool doesn't necessarily let you play. Right. You really want to make sure that the data still talks to each other. And we go back to classic concepts like a data model, powerful data model that you can ask questions to. So just have a sophisticated view on integration.

GLENN LABHART, PARTNER AT LABHART RISK ADVISORS

Okay, Jackie, what about you? What's the one thing.

JACQUELINE HALLMARK, MANAGER, IT CYBER AND INFORMATION SECURITY AT JUST ENERGY

The one thing that we're looking at know, again, to Alvaro's point, the integration piece of it, how well does the system play with our current enterprise systems and how that data is being used? Really? That's the flow that I'm looking at is where it's originating from, how it's being processed, and what's output. Where is it going? Once we understand that data flow and how it's being utilized, then that helps us make decisions on how we want to integrate going forward.

GLENN LABHART, PARTNER AT LABHART RISK ADVISORS

Do you have to say no a lot?

JACQUELINE HALLMARK, MANAGER, IT CYBER AND INFORMATION SECURITY AT JUST ENERGY

Yes, I get that. I say no too much, and I've gotten back away from saying no. Let's review it. But sometimes it may necessitate that we have to find another solution or we need to keep looking, simply because not everything is going to be best fit in our environment, depending on what it's being used for. A lot of stuff does go through legal as well, because legal has regulatory compliance requirements that they're looking at. And we want to make sure that whichever third party we're bringing in is abiding by our requirements as well, because ultimately, we're the ones responsible. At the end of the day, it's not going to be the third party company. We agreed to bring them in on board. So if there's a data breach, we're the ones that are going to have to answer to.

GLENN LABHART, PARTNER AT LABHART RISK ADVISORS

I agree. You know, I remember back in my day when my company bought Enron and we were going through a lot of interviews with the regulators and they commented on a lot of things that we may have touched on in the course of that, and they said, but excuse me, it's your data and you own it, so you need to be able to answer to that. I remember that very clearly and distinctly. The regulators telling us that, Kaylee, what's the one thing from your end? Is there any one thing that stands out in your mind? I know you guys have those big checklists y'all go through, but not what's in the red, but what's the number one red one.

KALEY CRANE, MANAGING DIRECTOR AT ERNST & YOUNG

Yeah, I mean, for us, it's governance. Right. And that's governance of the tools that are processing your data, but governance of the underlying data itself. Right. Making sure you have that single source of truth that's clean and that's as expected.

GLENN LABHART, PARTNER AT LABHART RISK ADVISORS

Yeah, I'll offer this. We do a lot of the similar type of work. And I agree with you. I think when you are looking at a holistic technology environment, it's of course what's going into the technology, then you back into it. What kind of transactions are we doing? Do we know everything's been captured in the system properly and accounted for. So I tend to look into governance as a policy. One is, have they weighed in at the top to say, we need to have anything that's not an approved product? Has somebody gone through the stages of checking all the boxes? Credit market, legal, it systems, regulatory compliance, HR, have all those boxes been checked? Whenever we put something in new and can we account for it? Because if you can't, it's not like it's a crime, but you need to have gone through that to be able to identify where your breaks are, because you may be on a budget year of a technology budget that says we can't do that. So if you can't do it, do you need to fix it? And how material is that too there? So it's really kind of a 50 50 answer to the governance level or the risk committee or the executive committee or the board to say, what are you going to do? And can you shift gears if you're going to do this? And I think a lot of times people, some companies I've seen take these by example, when they merge companies, they just let them operate on their own and do the risk over the top to keep any of the components from being marred or otherwise. It's better to leave them alone than it is to try and integrate it. But put a plan of integration. So the sword cuts many different ways, the way I've always seen it. I think that you're right, though. The governance is everything, and that these types of elements especially are critical in technology to make sure that if you're going to put metrics out, either financially or require disclosure to the regulators, if you can't produce it, what's the point? You've got to have this evolution that continually works through that says we can do these things or we cannot do these things. And if the answer is no? Well, the answer is no. So let's move on for just a minute. One of the things that we have on our agenda here is AI. And this is certainly a topic that is far reaching for many of us. I myself am not an expert. I'm going to default to the panel to give me better answers. I will say this, that in my research and my view of this in the industry, you've got a little bit of a gray rhino here. This was a term that was coined by my friend Michelle Wucker, that a gray rhino is drawing attention to the obvious risks that are neglected despite and often because of their size and likelihood. So AI can be considered, I think in some regards, a little bit of a gray rhino in that it's new. And when you look at also too, I wanted to throw this out for everybody's comments. You're looking at a global survey that's just been produced in 24 hours, that everybody in the industry reports that 82% of the enterprise leaders have increased their budgets by. 82% of the people have increased their budgets in 2023. Going into this, they're looking for a two x investment and notable impact on product quality and delivering value to the customer or improving the workers productivity. Call it what you want. There's obviously an investment made and that people are talking about this as far as the budget and the trend and the forecast growing to $251,000,000,000 by 2027. So this isn't going to stop, it's going to get stronger. And so when we think about it in those terms as being something that's obvious, I would say that it may be a gray rhino, but it's not that anybody's neglected it. It's that I think some people are introducing something that's new and doing it faster. So let's start with Kaylee. Talk a little bit about AI and how's this being yours from your vantage point in making robust decisions and model decisions? Give us some color on that from your point of view.

KALEY CRANE, MANAGING DIRECTOR AT ERNST & YOUNG

Sure. Every client conversation I have these days, AI comes up in those conversations. So I agree with you. I think it's here to stay. Right. It's a matter of how do we start leveraging that and when. The important thing about AI, though, is that it's only as good as the data you're going to feed into it and the training that you give it, right? So you've got to have that base foundation to leverage the technology. So the companies that are kind of ahead of the game have already invested in getting their data right so that they can now hire those data scientists and quants and put these models on top of them to do the AI. But we are seeing a lot of interesting use cases out there, obviously within the trading organization, just pulling in as much market data as they can, performing. We were at a time where in the old days, trading decisions were made with traders sitting in a daily meeting talking about strategies. Now they're going into those meetings with these models that are already producing insights to drive those decisions on what they're going to do, and then even kind of middle back office seeing the models better from a risk management perspective, better identify risks. Like, hey, there's risks within your portfolios, you need to take this action type thing. Within logistics, obviously there's predictive analytics models for transport and vessel movements. And then even with the kind of back office and as contracts get automated confirmation, settlements get automated, you have a whole new source of data that you can apply analytics and AI on top of as well. So I think it is here to stay. I think key is getting that data right first and then figuring out how you start leveraging that technology.

GLENN LABHART, PARTNER AT LABHART RISK ADVISORS

So would you say the use of this AI is for some parts of the organization, objective versus subjective? I'm taken by the comment of a risk committee meeting and people coming with these data of let's talk about the risk in the market, what our portfolio is doing, what do we feel we should be doing? Is there the balance between objective and subjective, giving people this capability?

KALEY CRANE, MANAGING DIRECTOR AT ERNST & YOUNG

Absolutely. I think that you're just going to have to kind of balance that as we go. Right. But there is, I mean, I think we're moving more to objectivity because we have data and less away from the subjectivity that trading decisions maybe used to be made.

GLENN LABHART, PARTNER AT LABHART RISK ADVISORS

Absolutely. Avaro, I'll throw that one over to you on AI. How do you see this playing into the market? The people being able to define and assess risk and make business decisions?

ALVARO MARIANI, SENIOR RISK MANAGER AT RADARRADAR

Yeah. So let me echo what Kaylee is saying, right. And I tried to issue warning on following buzwords earlier, but that's clear, that's a trend that's just going to grow, right? And what we see is, as Kelly was saying, you have to have your house in order in terms of understanding and having the data to take advantage of this wave. And if that is today, already an advantage, right. I think what you're going to see, that advantage will just grow and with time, and as AI takes hold of trading, the gap between that, the players that are organized and understand the data and the ones that don't will grow with time.

JACQUELINE HALLMARK, MANAGER, IT CYBER AND INFORMATION SECURITY AT JUST ENERGY

Jackie comments on Aya yes, so as you know, my stance is making sure that we put guardrails in place, but I do see the need to incorporate it in certain aspects of the organization. I do see the benefits from an operational efficiency standpoint. What could have taken analysts weeks, months to identify may take the AI a day or two, if not sooner. So that will definitely speed up the process that we utilize in how we're analyzing the data. The caveat that I put in there is, to Kaylee's point, the governance around the data and making sure that the data is clean is critical. Garbage in, garbage out. What you put into it is going to feed that model and that's ultimately going to be what's driving the decisions in there. If you have the poor data quality, you're going to get poor results. If there's data bias, you're going to have that bias reflected in your outputs. So making sure that that data is clean is absolutely critical. And then also ensuring that the people that you're hiring or that are maintaining those data sets understand the foundations. You can't just take somebody off the street and be like, go interpret this, because AI could be producing whatever it feels like. There's been a common effect known as AI hallucinations. If it can't find an answer, it's not trained to say, I don't know, it'll try to produce something. So you have to make sure that the integrity and quality of it is accurate. And that's a learning process. It's just like you're teaching someone baby steps. You keep continuing to feed it the data, you're telling it what to think about it, you're teaching it. It's the same thing with the AI models. You have to continuously train it and you have to have the people available and ready and knowledgeable to be able to train it. My biggest concern as well is around the cybersecurity risks, is just making sure that you have taken those risks, identified them, and you map it out so that you have your risk management strategy ready and identified for when you do implement AI into your environments that you know how you're going to maintain this.

GLENN LABHART, PARTNER AT LABHART RISK ADVISORS

Okay, interesting question we've got coming in. I'm going to throw to the panel. And Kaylee, I'll start with you first. The question coming in is, what's the experience been in regard to staff reaction to AI projects and other automation? Are people in a corporation embracing it or fighting it? So you've got this new technology coming in with new people. People are using the model. Are people fighting it? Is it working? Do you see people embracing it? How do you feel about that? Can you give me your comments on that one, please?

KALEY CRANE, MANAGING DIRECTOR AT ERNST & YOUNG

Yeah, I think it depends. And it's the same with a new ETM or CTM system, right. If you properly educate, train people, do the knowledge transition to people to be able to use these models, they work really well, right? I think people naturally have a resistance to change. So getting that process in place, making sure they're trained on it, they understand the value of it, can go a long way as far as adoption of these new technologies.

GLENN LABHART, PARTNER AT LABHART RISK ADVISORS

Alvaro, what about yourself people's reaction in the market to AI that you see?

ALVARO MARIANI, SENIOR RISK MANAGER AT RADARRADAR

So I would know. We are in the process that we still get, in some instance, a bit of fear and some instance a bit naivety, perhaps overexcitement, thinking that magically all the issues, discussions we're having, oh, I don't need to organize my data anymore, because now AI we're going to do for me, which is actually the auto a round, right? So you get that reaction. We find that natural. We're running some internal projects for a while right now to make sure that we are really understanding how to use that in the best way. And you can see, obviously, there are some low hanging fruits there. There are some immediate applications that you can find. But we do see people in the market going through this process of perhaps being a bit afraid, being, oh, I have to have an AI project because what if I don't? And also being perhaps a bit naive on how much work and the process of getting there. But we see that as natural part know introduction of a technology that will be disrupted as this one.

GLENN LABHART, PARTNER AT LABHART RISK ADVISORS

Okay, we're getting down to the end of our session here. So our final question, I'm going to just submit, and I'm going to start with Kaylee first. What's the trading shop of the future going to look like? We've got AI. We've talked about governance organizations. What are we going to look like in the future?

KALEY CRANE, MANAGING DIRECTOR AT ERNST & YOUNG

Yeah, I think everything we've talked about, add in extreme weather events, the volatility, energy transition, and then all the emerging technologies that are out there, I think we're going to see a lot more just automation, a lot less spreadsheets, a lot better data, a lot of better automated decision making throughout the trade lifecycle from front to back. So I think it's an exciting time and I think it's causing people to kind of reevaluate their overall operating models, people, process and technology to prepare for that.

GLENN LABHART, PARTNER AT LABHART RISK ADVISORS

Absolutely. Jackie, what's it going to look like in the future?

JACQUELINE HALLMARK, MANAGER, IT CYBER AND INFORMATION SECURITY AT JUST ENERGY

Yeah, I agree with Kaylee. Definitely seeing a lot more automation, definitely seeing AI. It's going to become part of the base platforms, especially as people go to more cloud adoption. It's going to be included, if you're not already, majority of the systems are already starting to implement some form of AI. And I think organizations as a whole will be better equipped, provided that the integrity of the data is there to drive those decisions and be able to quickly react and make those real time decisions, especially when it comes to these extreme weather events. We are already seeing some trends and grids coming through. So to Kaylee's point, less spreadsheets. I think that that is going to be a big one. It is going to take a lot of work with the digital transformation process, but I think that organizations will definitely get there. If we were to have this conversation five years from now, we would be talking an entirely different story, looking at how things were automated and how much efficiency has been driven in the organizations and how companies are utilizing AI in their business decisions.

GLENN LABHART, PARTNER AT LABHART RISK ADVISORS

Okay, Alvara, what's it going to look like in the future?

ALVARO MARIANI, SENIOR RISK MANAGER AT RADARRADAR

Yeah, perhaps I will try to emphasize one trend that I see less talking about that perhaps should. So I think a lot of people still hold the image of the commodities trader holding the phone, talking to a broker and talking to the market to find out the lineup and typing a spreadsheet. We have seen that changing. And just to give an example, for example, we have a new product that allows any user, but including traders, to bypass what we call the power bi layer and connect straight to the data and use Python or whatever order to do their own modeling. And I think why in the past the game was, hey, let's have a good trader and build, let's say, technology assistance around him. I think you're going to see more and more the trading driving the technology. And we already have traders that know how to code, for example, in the commodity industry, and I would pay attention to that trend.

GLENN LABHART, PARTNER AT LABHART RISK ADVISORS

Okay. Well, I want to thank all the members of the panel and all the sponsors today for supporting the commodities risk portion of this for advanced is in risk technology. There's another session that's going to go on behind this on trade finance. I'd encourage all those people that haven't registered to register for that as well. But thank you to each one of the panel members for their insight and for all participations on this. And we wish you a pleasant 2024 and a pleasant day. Thank you very much.

ALVARO MARIANI, SENIOR RISK MANAGER AT RADARRADAR

Thank you, guys. Bye.

Written by: Commodities People


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