Podcast transcript: How tech innovations are solving the challenges of legal and compliance team
45 min approx | 28 February 2022
Susannah Streeter
Hello and a warm welcome to the EY and Microsoft Tech Directions Podcast. I'm Susannah Streeter and in this episode, we're focusing on technological innovation, solving the challenges of legal and compliance teams. We are in times of unprecedented change with an accelerated shift to digital technologies in so many areas of business. The age of big data has well and truly arrived, and it is expected to keep fuelling the global economy in the years to come. New emerging technological innovations are seen as very much a solution. And the benefits of cloud virtualization, big data analytics and artificial intelligence are vast, but the degree and pace of change we're confronted with can seem overwhelming. The legal and compliance function is considered to be an essential part of the advanced guard in this digital revolution. But how do we persuade more in-house teams to join the transformation charge? If new platforms are embraced, they can help alleviate pressures, and empower teams to become more efficient, generate revenue, and drive innovation. So, in this podcast, we will be discussing what changes are needed to ensure businesses can fully reap the benefits of data-driven technologies. And we'll explore how new platforms are harnessing smart processes, such as robotic automation, text and predictive and analytics in order to automate large swathes of manual repetitive tasks and just how this can liberate armies of workers, leading to increased job satisfaction, retention and recruitment. I'm pleased to say we have three eminent thought leaders who will guide us through the rapid developments taking place, discuss what's stopping businesses from adv much needed change, and offer plenty of solutions along the way. But before I introduce them, please do remember conversations during EY podcasts should not be relied upon as accounting, tax, legal investment, nor other professional advice. Listeners must consult their own advisors.
So, I'm really excited to hear the views of some of the top experts in the legal and compliance business. First up a big welcome to Meribeth Banaschik, who is joining us from Cologne in Germany, and is EY’s Europe West Innovation Leader. Hello there, Meribeth.
Meribeth Banaschik
Hi, thanks for having me, Susannah.
Streeter
So much to talk about. And I'm really pleased as well to welcome Todd Marlin, EY Global Forensic and Integrity Services Technology and Innovation Leader who is in Park City, Utah for us today. Hello there, Todd.
Todd Marlin
Hello, Susanna. Thanks for having me.
Streeter
And from Phoenix, Arizona, we have Alan Gibson, Director, Legal and Compliance Innovation at Microsoft. Hello there, Alan.
Alan Gibson
Hello. Thanks for having me and look forward to this conversation.
Streeter
We have so much to discuss right now. So, let's go straight in. And Todd, I want to ask you, the age of big data really has well and truly arrived. But with oceans of information being accumulated by the very minute, just how hard are companies finding it, do you think, to manage, preserve and handle this data correctly?
Marlin
I think companies are finding extremely difficult the type and volume of data is increasing. So, it's not just the volume. You know, you think back to the pandemic that we currently find ourselves in, employees are using personal devices. There's been the rise of collaboration and communication tools like Teams and Zoom. And of course, a panoply of external third-party solutions that parts of the organization use or employees use on their own. And that's just an extremely challenging environment for organizations to track, understand and then call upon when they need to for legal and compliance needs.
Streeter
It certainly is. So, tell me a bit more about the integrity report you've released? What does this show about the extent to which some players are prepared to go to get ahead?
Marlin
So, you know, at the end of the day, the EY 2022 Global Integrity Report reveals that while the pandemic has made it harder for businesses to act with integrity, more companies than ever value corporate integrity and its benefits, reputation employee retention. You know, at the end of the day, there's a challenge which is, what senior leadership is saying is important and what they are prepared to do. And this results in what we call a say/do gap. And often that's not lost on employees. Why it's relevant to this conversation is that that also applies to technology. What, you know, management expects and that they're saying that they're doing, there's a lot that needs to happen for it to be implemented technologically to monitor different risks to surface priorities, data insights, and then to act upon it and follow through. And so that say/do gap. Really understanding how the team and what they're implementing and whether they're implementing and how it's working, is a really challenging exercise. Certainly, given the diversity of data types, and technologies that are at play in this.
Streeter
It certainly is overwhelming. And let me bring in Meribeth. Many companies are of course embracing the big data revolution. But to what extent do you think teams are overwhelmed right now. You heard what Todd had to say. Do you think too many teams are waiting passively for technology to solve problems rather than being proactive?
Banaschik
Well, it did take the legal industry quite a while to embrace technology, some of this technology was available up to 10 years ago, but I think due to COVID-19 and also the cost pressure that GCOs are under and chief compliance officer, reduced headcount, there are very high expectations for technology. And because of that, there's a lot of pressure on them. I think there are a lot of new pieces of legislation that are coming out, especially in Europe, we see artificial intelligence legislation, supply chain legislation, privacy continues to be complex. And as those new bits of legislation come out, they are a bit overwhelmed trying to figure out how to handle everything on their desk. What's most interesting to me about this, so bringing in the data aspect, is how they get their data and whether or not they really know where their data is in the organization.
Streeter
And this is crucial, isn't it? Because companies need to be prepared for scenarios when litigation hits. And when lots of firms may scramble to try and find out what happens in terms of non-compliance or fraud, knowing where that data is, is absolutely crucial, isn't it?
Banaschik
Exactly. And I mean, with litigation, we know that that involves e-discovery. And the process with which you gather electronic evidence to prove something or to try to disprove something in litigation, but as you can imagine, the volume of data means that things like AI and machine learning have to be used to get through the volume. And to meet those court deadlines. Right now, what's interesting to me about litigation, specifically, is how technology is helping with litigation operations. So, you can remember the financial crisis litigation that was happening, automotive crisis litigation, more and more GCOs are having to think about how to handle lots of litigation landing on their desk at the same time, how to intake it, how to make sure that it's sent to law firms, and how to use technology to do some of that. It's quite an interesting area.
Streeter
It really is. Alan, let me bring you in, because big data has been described as more valuable than oil, but do you think compliance teams really have recognized this?
Gibson
Well, I'm not convinced that a majority of the compliance teams have recognized this. But I do think that compliance teams are starting to recognize it, or they're at least thinking about going on this, this data or modernization or digital transformation journey. We've touched upon a couple of topics already. But when you think about this journey that a compliance team needs to go on, it's really thinking about moving from a business intelligence or developing that business intelligence to more advanced analytics and these AI approaches that have been mentioned. How do we think about going from static reports and reporting on what happened to starting to leverage this, this data to describe, you know, why did it happen? And then in the future, using it for predictions. What will happen and directing conduct? What should somebody do in response to it?
Streeter
So, what examples can you give that can really demonstrate the type of potential that this technology has if is leveraged correctly?
Gibson
The top-of-mind example for me, just because I sit so close to it, as formerly a practising anti -corruption attorney is identifying which contracts create the most risk for a company. And one way you can do it is, you know, their standard dimensions that you may use to consider to identify whether a contract is risky, the size of it, where it takes place, the amount of discount, the third party that's involved in it. And you know, that's the traditional approach that companies have taken. But let's say that you could extract more value from your data to get insights from it. What that means is, how do you identify that that contract is an outlier from others, you can do it so that, you know, looking historically, hey, we entered into this contract, it has additions that it has higher probability or higher amount of risk in it. But the advancement of using compliance analytics would be as you enter into a contract, as it works its way through the contracting process, is it already indicating an increased risk of non-compliance and allow you to change your behavior or your response before you actually enter into the contract? So, instead of just identifying non-compliance or misconduct after the fact, you're actually able to predict that the risk of non-compliance has gone up, and allowed you to proactively respond to it before the risk becomes an issue?
Streeter
So huge potential. But Todd, where do you think the starting point should be? How can these digital solutions be best applied to modernize how companies manage compliance risk?
Marlin
Well, the starting point, first and foremost is not all companies are created equal. Not all companies have the same compliance risks and things that they need to focus on. One is, you know, understanding, you know, their data landscape, and the risks that they want to prioritise and then understanding the interplay between that data and that risk. So, what systems have the data at issue? What risks do you want to focus on is an anti-bribery and corruption? Is it something else? Then as well, you know, understanding today, you know, how's that risk being monitored? How are you trying to identify where things may be an issue, so you can intercede? And then, as well, you can use that information to design a new process where you look to prioritise through the use of, you know, different analytics, perhaps different AI techniques to prioritise information. So, it can be surfaced to experts to make decisions about whether the risk that's being or the instance, if you will, is in fact, you know, a problem and then allowing those experts to make judgments and play that back into the system or the process, so that in the future risks and instances can be prioritised based on the judgments of experts. So, the whole key here is that you can't attack every risk simultaneously. It's just too overwhelming. You got to know what you have, you got to know what you want to do. And then you go through a process of trying to design a tech-enabled process with, you know, artificial intelligence, analytics, perhaps other mechanisms to get the right data in the hands of experts to make judgments so that better decisions can be made in a more timely fashion.
Gibson
I think both Todd and Meribeth and I have been in this situation before, where companies or clients quickly go to “I need technology, or I need analytics, and it will help solve my problem or address my risk”. But when you sit down and have these conversations, they don't necessarily understand their risks or their processes. So, it's super beneficial to help there and then prioritise those risks, which are you going after and why. I have lots of conversations where it is, “okay, we need analytics, these are the sorts of insights that I need to have generated”, and it quickly goes to “Okay, is that a prioritised risk?” And if we're looking into it in creating insights, so what, who is going to be taking action based on those insights we've created from the data and what outcomes are we actually trying to derive?
Streeter
So, it's really interesting to outline those opportunities that you can pounce on, but Meribeth why do you think so many companies are missing a trick when it comes to using data to make these better and more accurately informed decisions.
Banaschik
So, the lawyer in me cannot help but think precisely of those words. So informed decisions. I mean, this assumes then that you have insights. And if you have insights, it assumes that you have information, which assumes that you have data points to make that right. I mean, I'm thinking about there's a lot of talk about ESG and sustainability. And at a certain point, I'm not sure that companies even have the right data points that they need to properly report on issues or to even make informed decisions yet and in addition to that, I think that there is a sort of tension that's building on the one side with teams who want to use information that they have, for a different use a different project a different task, they want to use that data for a new insight. But at least in Europe, there might be privacy counsel, a data protection officer, which would say no, you have to limit the use of that data for what it was originally approved for. So perhaps a complex topic to find a solution at the end of the day for some general counsels.
Streeter
And Alan, you're clearly excited about the opportunities. But tell me what you see some of the best emerging smart platforms that you think really will endure and survive the so-called hype curve when it comes to their use by legal and compliance teams.
Gibson
As I look at the solutions and the platforms, they are ones that break down data silos that will allow different datasets to talk to other datasets. What this means is that how you connect data across systems and then leverage intelligence and derive insights, so that data from one system can be used to optimise the outcome or process from another. And so, the sorts of platforms that I'm seeing are ones that may start out to address a single risk. But additional risks can be added on to it in a way that breaks down data silos, instead of creating additional data silos.
Streeter
There is though, so much to choose from, isn't there, Meribeth? So how should teams do you think plan and prioritise which emerging technology will add the most value?
Banaschik
It's such a frustrating position for a lot of firms I believe. So, you have, first of all a problem and you try to find technology to solve that issue. What I see constantly happening is that then the companies will buy a point solution. So, an answer to that one problem. And then the next problem comes along with a different tool and a different tool. And before you know it, all of these different point solutions really don't fit neatly inside of their technology stack. And it might be that information from one tool doesn't flow easily into the next. And so, I have to agree with Alan, the platforms that I think will be satisfactorily delivering results to legal and compliance officers will be ones that reduce silos, will be ones that allow privacy to happen, will be ones that allow clients to see transparently into issues. And let's face it, I mean, chief compliance officers GCOs, we're not IT specialists. And maybe also we don't like admitting that we're not the smartest in the room. And so, this really requires over and over, you saw this with the GDPR. You see this also with ESG. I think we'll also see it with topics like metaverse and blockchain, it really requires a multidisciplinary team on the client side, with communications with HR, with IT to figure out what works best for the company, also, so that the team actually uses it. How sad is it when a company invest so much money, even into a point solution, only to learn a year later that the team doesn't even use it?
Streeter
Do you think Alan, that is the key, these multidisciplinary teams, do you think that will help break down information silos, which are emerging?
Gibson
The interaction between the teams or the collaboration amongst the teams is critically important for these effective compliance programmes. And so, when I'm looking at them, the most successful ones have been a combination of a partnership between legal and compliance, IT finance, internal audit, and other domains because really what you're trying to do, and we've talked about data silos. To make it real, when I think about data silos, I think about how do we allow the data from a revenue reporting system to talk to a customer relationship management system, to your enterprise resource planning, travel gift in hospitality. All of those systems are owned by different functions within the company. But how do you establish that platform so that it allows information to be exchanged amongst those systems? That's really where you're going to get a wealth of insights from a compliance perspective.
Streeter
Let's now talk about the risks of this rapid proliferation of new tech platforms. Do you think Meribeth by increasing IT complexity and raising potential security and privacy issues, these are risks that perhaps companies haven't really got the forefront of strategy right now?
Banaschik
I mean, you see how many hacks and cyber breaches we've had in the last 12 to 18 months. I hope that companies are not learning the hard way how to handle some of those risks and are taking advantage of some of the solutions where you can, let's say, practice, and what would happen if some of those risks arise. But I mean, you mentioned the privacy aspect, I I'm not sure that we figured out all the privacy aspects of things like metaverse, or blockchain, like I was just mentioning. I see that in the privacy space right now one of the most requested services on my desk, it relates to supplier assessments. So, companies want to know if their suppliers are complying with the privacy statutes and right, and this might also mean, you know which country. All the different countries are now coming out with new privacy legislation. So, they're also having to balance which provisions to look at we all remember the borders closing, we remember the Ever Given stuck out in the strait, we've seen pictures of the California coastline. And so also maybe some technology around vendor selection. If you have to replace a supplier, I see companies really looking in detail into this area.
Streeter
Absolutely. And I want to as well move on of course and talk about AI and bring in Todd. Todd, let's talk about artificial intelligence. How can these strategies do you think be pursued and be built in such a way that there is flexibility and employees are empowered rather than limited?
Marlin
I think it starts with, you know, involving them in the process. Instead of having a push down on high in terms of identifying what the use cases are or the opportunities from a business perspective to introduce AI or other technologies to drive efficiency. My suggestion is you involve the employees dealing with those issues in the process, try to understand where there might be inefficiency, where there might be repeat processes, and the opportunity to cut costs, and have them not only suggest where there might be good business problems to work on in terms of introducing different types of AI models. But then as well offer them the opportunity to learn about how to do it. There's lots of resources out there in terms of educating on these topics, as well as many of the tools to actually do it are free. So, you know, I think it's, one involved in the process and, two educate them so they understand how they can assist, and how they can also extend their skill set to be part of creating the solution.
Streeter
Yeah, it's interesting, extending this skill set. And inevitably, Alan, automation and AI will free up time and resources to help teams, so how do you see that the human role could evolve and what new capabilities might be created for teams, as long as they have an integral part, I suppose, in making sure they're happy with the way the system is progressing?
Gibson
Yeah. And whenever we have these conversations in the background, there's always the fear that the robot army is coming in, and that humans are going to be replaced. But I like to think about it as where AI is going to help. It's really going to help people and companies make better business and compliance decisions, allow them to make more informed decisions make more effective decisions. And where I see AI really playing a role is allowing us to identify what's risky, or where the opportunity is, why it's risky, or why it's an opportunity. And then using a quantitative-based approach – what you should be doing. And the big benefit that I see to the teams is, it's really going to allow them to prioritise their time on the biggest risks and the biggest opportunities. And with the data, it's really going to equip them to do their job better.
Streeter
So, do you think we'll see a productivity bonus?
Gibson
I think so. I already see it in the sort of examples I can give, just from my work. There has been, let's say you have millions of sales contracts, and you're trying to identify which ones create the most risk. AI machine learning allows us to take a more laser-focused approach to which ones are actually creating the risk and allocating our resources. And so, it's not that it identifies the needle in the haystack where you should be focusing your time, but it does give you the handful of hay, that identifies where you should be spending your time. And I really think that's how it is helped me increase our productivity.
Marlin
You know, just to add on to what Alan said here, you know, I think there's another opportunity as well, which is, you know, at the end of the day, if you take a piles of hay analogy, and an expert looks at that, and then ultimately gets to the needles, the needles can be fed back into the model to do a better job of getting smaller piles of hay in the future that are more on target.
Streeter
Mm hmm. Yeah, it's a really interesting analogy. What do you make of that Alan?
Gibson
Well, if we're building on analogies, we can go back to data being the new oil. And with that analogy is the one way you can do it is unlike oil data is a renewable resource. But what's very interesting about it is data can be reused and combined with other data, which actually makes it work better. And so, as you talk about, you're feeding the learnings back in. That's the beauty of the data that over time as you train your models, it should get quote unquote, smarter and smarter and continue to drive more productivity and efficiency into those processes or practice areas.
Streeter
Interesting. You talk about feeding the learnings back in. What about stripping out those really menial tasks? And let me bring in Meribeth, because we've had a lot of talk about the great resignation, with people just walking out of their jobs thinking I've got to find something that will be much more satisfying. How do you think AI could alter that? Do you think it has benefits in terms of creating better job satisfaction?
Banaschik
You know, Todd and I are a part of the Forensics and Integrity Services Group at EY. And focusing a little bit in on that integrity part. I think from our perspective, it's important to keep an eye on the biases that are inherent in AI, and not to assume every single one of those algorithms is working properly. But yes, I do think that it brings benefits, you know, to our clients and law firms that we're working with to meet certain deadlines. But you're right, I mean, from a team perspective, I personally don't want my team doing manual tasks, working late hours, getting frustrated that the job is not challenging or complex enough, I'm not sure that that's necessarily always AI. It could also be sometimes machine learning or even simple automation. But certainly, focusing on what can be automated. And if it comes to AI, this certainly, I think will help members of the team.
Streeter
So, people shouldn't be concerned about robots taking over then?
Gibson
The one thing that's interesting about that, it goes back to the digital transformation journey that I mentioned earlier, is you go through the what happened, why did it happen? What will happen? What should I do? And then it becomes is it repeatable? And that's where the automation comes in. So are there certain actions that we can take out of the workflows that become automated, that one may make the process more efficient and productive. But it also will, I think, improve the job satisfaction of a lot of people that are working in these areas.
Banaschik
I'm not sure that we're there yet with robots taking over and, but I think some people do worry about this. And if you think about, you know, maybe some travel agencies have been replaced, or I've even heard of kiosks that you can go to, to prepare your will coming from Germany. Of course, fancy nice cars that are able to drive for you stay in the lane. And this is, of course, very attractive. What does this do to some of the taxi drivers, right, we have to keep all of the balance of society in mind. But I don't think that there's a place where robots will take over as we hear in some of the sci fi movies. Although I have to admit, when I was younger, I used to watch the Jetsons. I don't know if I'm probably dating myself, but I loved watching the Jetsons to see this futuristic world and seeing the metaverse and these new, innovative topics, really, really excites me.
Gibson
Yeah, with some of the automation and robots where I see it that where I think job satisfaction has gone up in compliance groups is there's certain tasks that they would have to complete to, for example, a deal review or reviewing a third party. And they would have to go to multiple systems to search manually search or run their searches to get the information. But automation can replace some of that work. And so, if a contractor or a third party is identified as high risk, the automation will collect the information that they need to make their decisions automatically for them. And that's where I think that some of the job satisfaction and productivity comes in.
Streeter
But what is the other side of the coin? I mean, what should companies be looking at to ensure they don't introduce new risks when adopting AI, Todd, because that is a potential problem, isn't it?
Marlin
It is, and, you know, it can happen throughout the process. And Meribeth referred to this before you mentioned the word bias, you know, I see, you know, sort of three categories of, you know, really top of mind issues that the company should really consider, you know, as part of their process when they're creating this. First is in the ethics and bias area. You know, essentially, when we create machine learning artificial intelligence, it's not being programmed by the computer itself. At the end of the day, you have a human and a keyboard, making decisions about what data what fields, what limitations, and choices throughout the entire process. A good example is in the world of electronic discovery, you know, there's a process called the electronic discovery reference model, when you're creating artificial intelligence. Well, there's a process that's not that dissimilar, that has a number of different steps. And at each step, you could be introducing either known or unknown biases into those models, starting from the point of even selecting the data set that is being used for this, what you've removed from it, how you look at it, there's, there's a whole slew of different choices. And sometimes these choices have impacts, they're not even, you know, obvious to the people that are that are doing them. So, you really need to have, you know, a process where you have cross-functional team of experts looking over the process throughout this to be testing for ethical and bias type issues, and other big categories around data privacy, can you use the data that you're using, should you use the data. And then lastly, depending on what you're talking about, and maybe perhaps, you know, it's less of a concern in the compliance area. But, you know, these models that are being created, can also be you know, used as a weapon by bad actors internally or externally to inflict harm on an organization. So, it's very much something that organizations should be paying attention to obviously, in the pandemic, there was a huge rush, because of the possible efficiency gains, improving employees’ experiences by removing road tests, things of this nature. However, in that rush, you have to set up the right process with the right people at the table.
Streeter
And because of this rush, are you expecting a whole raft of new regulatory changes on the horizon, to try and deal with all of this huge, accelerated shift towards big data and its use?
Marlin
Absolutely. And, you know, was referenced earlier, you know, the EU is in the process of creating a law to regulate artificial intelligence much in the way that they regulate privacy. However, that's not all. I mean, we're seeing this pop up all around the globe. I mean, even New York City now has a law related to AI and hiring and has certain obligations. France has an algorithm law. So, you know, there's many countries around the globe that are starting to legislate around this because of the risks associated with it. And not only the risks, but how it might impact people at the end of day in the organization's building these things and outside
Streeter
Meribeth, let me bring you in at this point, because I'd like to find out what you make about the new AI legislation coming into Europe. How do you think companies should be preparing for this?
Banaschik
This is not intended to be a sarcastic answer. But I think it really starts with understanding what AI is and being able to identify processes within the company that use AI. And I think this gets very complicated when you try to distinguish between workflows, automated processes, machine learning and artificial intelligence to really figure out what is true AI because according to the to the legislation, you will then have to cluster the AI into low, medium high risk, and take certain actions on the ones that are high risk. But if you don't know where AI is being used in your company, you won't be able to cluster it. And that makes it even harder to figure out what is exactly high risk versus medium risk. So, education, I think.
Streeter
Alan, do you think that this means that companies perhaps should start from scratch?
Gibson
Well, when I talk about starting from the beginning, I always encouraged people to, we're always thinking about people process and technology to go after these sorts of challenges and opportunities. But within that, it's like, start with the problem or the risk that you're trying to address. Too quickly, people go, 'Hey, I need a platform, or I need a data lake', and you run the risk of one, either what you're trying to accomplish collapsing under its own weight, or you don't have a clear understanding of what outcomes you're trying to drive. So, your project fails. And so really trying to understand the process you're trying to impact or improve, and then the landing accountability or ownership with somebody that is going to do something with the insights. The other thing just to get started, and Meribeth alluded to this is leverage the experts, both internally and externally. And so, like you're talking to people that are experts in legal and compliance risks, I personally am not necessarily an expert in I'm not a data scientist but get access to data scientists that can help you understand how to apply data science, how to apply the technology to actually achieve or manage the risks that as domain experts we've identified. And that's where I always like to start.
Marlin
You know, one thing, you know, in terms of where companies are, should get started. And maybe I'd reframe the question, I think something companies should be mindful of that, you know, earlier, when we're talking about, you know, how companies are grappling with understanding their data landscape, you know, whether it's gotten more difficult, well, I've got news for you, understanding their data landscape, what's coming next is understanding your AI landscape. And so rather than letting you know sort of whatever will be will be and it will happen, and they'll just be this huge landscape that you have to try to understand. I think companies should proactively start to document track and understand where this is happening in their organization. So, it's not only tracking the data that you have, but where AI exists, and what it's being used for, essentially, it's an inevitability that most of the world is going to want to have this information, because it's going to have such an already is a big role in shaping how business is done.
Streeter
And I want to ask you, Todd, picking up on what Alan said, how do you attract talent, given there is such a fight for the best talent right now?
Marlin
So that's a very good question. And then there is a huge fight for the talent, and you don't win that talent just by monetary solution. You know, being a data scientist myself and trying to recruit these folks. They want to have passion and enjoyment in what they're doing. So, what I find excites folks, in considering folks as employees is talking to them about the problems that we work on, the problems that we tried to solve, and the scope and the scale, and the impact. You know, it's really about the work and the intellectual stimulation, and the ability to make a difference. Of course, the economic portion always comes into play. But I find if you focus it on what I've just said, that becomes a secondary element.
Streeter
So, let me bring in Meribeth, listening to what Alan and Todd are saying, do you think that there needs to be a culture change within organizations to make the most of the talent that already exists within companies, and to ensure that everybody is on board with this transformation?
Banaschik
You know, I believe that success really is decided like, within the people on the team, who you have on your team winning that war on talent. And I mean, evolution is maybe the right word. I mean, there's so many things that are changing right now with the way that teams communicate with each other with the processes. And we talked about all the different technology coming in with mindsets. And I know at EY we have a specific training on purpose, like what is your purpose, what motivates you, and being able to articulate that to your direct supervisor or boss, and I think to be able to stay agile with where the market will go and all of these different topics, things that we don't even know that's coming up with. For me, it goes towards education, and at EY we're offering all of our employees the chance to get a free MBA through our whole program. And I think we also really force our growing leaders to think about what it is that they want to build, because the entrepreneurial spirit really exists, I think in order to be successful legal and compliance team should, should look at that challenge what really motivates their team members.
Streeter
So, a real culture change, perhaps a revolution in culture and needed across organizations? Well, I know that Alan's already been peering into his crystal ball during this podcast, but I'm going to ask you to do it once more, because I'd like to look ahead to five years’ time and ask you how convinced you are that legal and compliance teams will have fully embraced the big data revolution and AI?
Gibson
Fully embraced. I'm cautiously optimistic that more companies will be further along on their journey. And when I look out the five years, I think there'll be a number of companies that have implemented what I'll call a digital compliance office, which allows a chief compliance officer, a GCO to really manage the different risk domains. What we're seeing today is pockets of that. And so, they may have a feel for how they're managing their corruption risk in third parties. To go back to what Meribeth mentioned earlier around ESG. I think that that's a place that we're going to see some inroads, some significant inroads over the next five years. Are we going to be all the way there? Probably not. But I'm cautiously optimistic that we'll be making some progress, and that we're gaining momentum because of internal forces, but also regulatory effects.
Streeter
Alan, thank you. So, Meribeth, what's your take? If you peer on to your crystal ball?
Banaschik
Oh, my crystal ball is wondering about access to justice and some of the online hearings that we've see taking place during COVID. And how some of this remote work will play out. And I hope there will be some good lessons learned there.
Streeter
Meribeth. Thank you. So, the final word to Todd, what challenges do you think will remain though, because certainly, there are an awful lot of opportunities, but plenty of challenges as well ahead?
Marlin
Well, you know, first I think things are going to fundamentally change and be more in the direction that Alan is saying about having digital compliance and the role of the lawyer will change to be to involve more technology, I think compliance and legal are often the last to embrace and adopt. The challenges are with all of this change around technology, in the companies, compliance and legal need to be riding shotgun out as this is all being created, to help mitigate risk and document understand what's going on. That is not happening. So, you see this rising tide of implementing AI, ML, RPA as fast as you can, because we got to bring down costs because we're in the pandemic, you have a shortage of workers that have this expertise. You have this unprecedented demand to change things rapidly, things are gonna go awry. And I guess the challenge remains is that over a five-year period, you know, if companies are not being proactive in the way that I've mentioned, while they may have transformed themselves in these departments and beyond, they will have created a whole new slew of issues they're not even aware of that are going to bite them and cause them whether it's reputational financial or other harm.
Streeter
Okay, Todd, Alan and Meribeth, thank you so much for being with me on the podcast. I'm afraid that is all we have time for. So, I'd really like to thank you once more Meribeth Banaschik, Europe West Innovation Leader, Todd Marlin, EY Global Forensic and Integrity Services Technology and Innovation Leader and Alan Gibson, Director of Legal and Compliance Innovation at Microsoft. It's been wonderful having you here discussing this fascinating topic.
Banaschik
Thanks for the invitation. It was great chatting with you.
Gibson
Thank you and have a great day.
Marlin
Thank you and goodbye.
Streeter
For more information do visit ey.com/Microsoft. And a quick note from the attorneys. The views of third parties set out in this podcast are not necessarily the views of the global EY organization nor its member firms. Moreover, they should be seen in the context of the time in which they were made. I am Susannah Streeter I hope you'll join me again for the next edition of the EY Microsoft Tech Directions podcast.
