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good morning and good evening everyone and welcome to another episode of definitive perspectives live today we will be talking about connected data data a word that many of us hear 100 times a day probably but it's the rush for the highest quality and most easy accessible data which has completely changed how organizations acquire use and more importantly govern it the size of the potential revenues and efficiencies can be unlocked through access to more data and improved data management a large of these challenges is connecting market and reference data across the entire organization from the trading desk to settlement to i.t systems and solutions joining us today are two of our global heads of prefinitive now the london stock exchange group janelle bc global head of real time and also john mason group head of pricing reference services thank you both for taking the time and sharing your thoughts on this topic thank you um let's take out the first question um probably this is very very this one but i want to get our audience a little introduction to what we will be talking about and um in your opinion are financial service firms falling short of their potential because they probably do not have the market and reference data and data management tools they need maybe janelle we can start with you yeah um so thank you shahad and firstly hello everyone and thank you for joining us today um shahad said i'm janelle veazey and global head of real time in the data and analytics division of the london stock exchange i am delighted to be with you here today but to delve straight into this answer i think the the simple starting point is yes um according to our survey overall firms are falling short of their potential by almost a third because they actually don't have access to the data and or the associated tools they need to really optimally perform their job and interesting as well i think that the front office decision makers in particular feel they are falling short by as much as 38 and i think if these firms had access to the data and the tools they needed and it's interesting to note how respondents to our survey said they believed they could increase revenue by 36 on the one hand and actually increase efficiency by 34 percent and and it's interesting these numbers sound large can actually translate into hundreds and millions of dollars across our pool of survey respondents but what we found though from our client research as well are positive examples of where things like cloud enabled technologies are actually leading positive change and just to give a quick example of this our definitive tick history google cloud platform can actually help reduce the total cost of ownership of tick history data by as much as 90 percent so there are some promising statistics too um john any thoughts from you yeah i think that's what's interesting here um it's not really us thinking whether companies are making best use of their data it's as the survey showed it's actually companies thinking they're not making the best use of their data and i think that comes down to a couple of areas is do they have the data in the first place and if they have the data do they have access to the data and i think in a lot of instances they probably have the data but it's dispersed across the organization and it's the inability to get that data in a in a sort of a conformant way to then make it useful for some of the use cases and i think that 30 percent that sort of grosses a thirty percent statistic around more revenue was really interesting because the financial services firms have traditionally monetized processes transaction banking or payment services that's where they make their money and data has been a bit of an offshoot or has been a way to facilitate the process and i think increasingly banks and financial institutions are looking at data as an asset and how they can revenue generate from data and that means looking at data slightly differently and i think the survey probably demonstrates that thinking thank you i mean when we're thinking about how they're using it what we can you know what else they can do how to combine the data and everything that comes along with this workflows optimizing maybe we can do a little um deep dive towards what kinds of challenges uh are firms facing within these you know market and reference strategies as well as implementations in that next step yeah sorry did you go john we go janelle ladies first you go i was just gonna say i think it's fair to say that the challenges are many for our customers i mean it's an obvious point but and they're across the board now they're across a whole number of themes from

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operational resilience to um cloud enabling technologies um to data governance programs all of the key themes that i think that the survey really drew out very well i think probably to name one of the top stats there are three fourths of the survey respondents actually saying that market data management strategies haven't actually changed in the past decade and do an overhaul to really extract proper value from investment and so that was one interesting outcome and again data governance really a significant challenge within firms with around a quarter of respondents saying that they're finding achieving data consistency through different channels or from different suppliers to be really challenging with around a quarter also finding that connecting data across the front middle and back office is a real issue for them and again i think there's a whole host of challenges and complexities um even around you know silo data and difficulties around navigation um and so forth so again the um the issues and relating to the investment priorities i think is really important 37 of respondents saying data governance is a top investment priority for their firms over the next 12 months and that need to improve data governance within firms is definitely one of those motivating factors behind the the moving the market and reference data and storage and use to the cloud now um that is very popular theme as well so i think just one last one for me on in terms of our real-time world where we've seen a real surge in interest in cloud-based technologies is through our cloud-enabled real-time optimized solution which actually supports a wide range of use cases and that's another thing we're seeing in terms of challenges today i think how our customers actually support the need for a greater number and a more diverse set of use cases than we've probably ever had before and i think this is one example of where um we're finding it's reflecting our customers rapid application development needs for cloud native and cloud adopting firms so you know thinking around the complexities our customers are facing we hope that this shift of very complex market data estates to the cloud actually helps make things easier for customers hopefully with less risk and allowing firms to migrate at their pace whether that's a slower or a faster pace into the cloud do you agree john yeah i do i think this i think it's the use cases bit and janelle roll her eyes at me here because it's from me all the time where i talk about uh we're a data to process industry we've moved data to where the process is needed because as i touched on earlier that that's typically what we've monetized as an industry is the process and therefore as long as the data has been good enough for that process everyone's been happy and and data architectures and data strategies have grown up around that type of approach to data and then in the last few years we've seen people saying well data is an asset i need to get more governance over over data in the same way i would over any asset i need to get more governance i need to get more structure i need to get more conformity over that data and that means a slight shift in data architecture and data strategy because now i need to link data across process because it's the data that's important not just the process so i can understand why the survey is pulling out some of those insights into the industry that people feel the data management architecture and data management strategies haven't caught up let's say with what people's demands on the data are and i think that is a i think that is a significant challenge and how do you do that when you've got ongoing regulatory change so the regulator's always asking for a new way of recording information a new way of reporting information a new taxonomy over data itself and then who's an industry how does a company respond to that whilst at the same time dealing with the strategies it's a good old analogy of you know changing the time when you're on the motorway driving at 70 miles an hour and and how do we do that and that that's really what the industry i think is wrestling with and that sort of conveys some of these responses but i mean um i also mentioned complexity you also mentioned the whole shift what other challenges that firms are facing remarkable in reference data are is there anything that you would say is uh one of the let's say the biggest challenge legacy i'd probably say for me is is just moving to what people are trying to do with the new things the new use cases the use of artificial intelligence machine learning the use of looking to wanting to look across the organization as a whole those have always been challenges i would say we all know when we went through certain uh traumas let's say in terms of lehman brothers or bearings and someone

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said so what's our exposure to lehman and you'd go and you'd find it across 27 different databases and you had to bring all that sort of data together so those have always been challenges within the industry and i think that's sort of reflected here and you add in the new use cases that are being put into that the more historic analytical use cases not just data for the sake of the process but what can we get out of the data and i think that brings new challenges as well so um i think it's it's the combination of things you had where we're sort of adding as we go yeah i would definitely agree with that i was just going to say it really is all the moving parts that that creates the the mountable challenge and that many firms have today and i think if you think about that that balance that i mentioned at the beginning that firms have to have between productivity between efficiency and a well-governed market and reference data environment all of that within an age of increased regulation with an accelerated pace of technology a huge number to john's point about the use cases the use cases are obviously driving a whole bunch of new marketing reference data projects that are underway as well and that are taking time and money from firms to invest in and then on top of all this you have all the the cultural um changes as well in terms of how firms i think having seen over the years the firms that are doing perhaps slightly better in this space are the ones taking on a more data centric rather than system-centric approach as well and are really being collaborative in how they come together across different areas of their business so looking at whether the front middle and back office comes together with operational teams it and support teams where that works well you see a real positive change in impact in in areas such as data governance within firms too so i think that that cultural and impact is really important and then just on on a fairly broad level if you look at a lot of these challenges and perhaps what they can impact or hinder is sometimes innovation you know again coming back to those use cases there are so many now as we move forward with the need for more and more data but in terms of the impact there you know that there's so many challenges that underpin these um that it can be difficult for customers and i think again also they absolutely reflect some of those challenges you both mentioned now uh a couple of times data governance and security risk it has been well a very hot topic especially during the pandemic maybe if we look at this a little bit closer how can thinking more strategically and the examples that you also mentioned about common instruments benefit the overall process i think pandemics regulation what often happens is organizations react and they have traditionally reacted to things and they've tended to solve that problem so and i was involved in the mythic roll out across the organization for example on prior to that um other regulations that organizations look to solve as discrete regulations so we need to solve method or we need to solve frtb or we need to solve libel um i think if you look at it strategically just to flip it on its head and say well we know we're going to have to cope with change we know that we're going to have to deal with perhaps new taxonomies then you can start to look at things differently and i'll give a sort of a real world example form pf in the us aifmd in europe both looking at hedge fund reporting aifmd asks you to aggregate regions on pf asks you to aggregate at a country level or vice versa forgive me i'm sure someone watching will say he's got that wrong he's got it the wrong way around but one there's one one does the other one's at a reasonable level one's at a country level if i'd address just one that said i'd address the regional system first as a as a i just need to solve this problem and i had regional analysis of countries and then aifmd came along and i asked got asked for country i'd have to start disaggregating data which as anyone who manages data knows is an absolute pain to disaggregate data whereas if i looked at it strategically and said what's the most granular data element that i can have here right it's country code it might even be a county code or a speaker and then i'm going to aggregate i can always aggregate up to a country or up to a region but i can't necessarily disaggregate so easily so it's taking it's looking at that data and saying well how do i how would i model that to give me the most flexibility how do i get to the most granular elements and that means um looking at it and then being able to source that data from your vendor and make sure that you can get that data appropriately but that's that's an example that i would use between giving yourself a challenge by

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responding and then looking at it strategically and trying to avert those challenges and it's interesting isn't it john how sourcing that data in the most optimal way has can have such a positive impact in terms of the navigational aspects of data the discoverability of data how you can actually then really maximize and get best return on your investment um from a data perspective um i think that's that's really critical here um and some of that comes back to fairly fundamental kind of principles or challenges in some cases around kind of uniformity of data commonality of things around data models and and so forth and i think again you know it was interesting that the survey rated um that actually this this was a key topic and i'm really governing the data and the rules around this was really important for our customers i think um from our us respondents it was something like a third actually deemed that whilst they were market leading in their data governance around this space and for other countries it was far far lower and either just average and many even lower than that so i think more this is again forcing more customers to really think about the need for commonality and data and what that means for them and i think again some of that is is this single reference point of data that we talk about with this golden sourcing and i think that's really relevant in conjunction with with data governance as well i think thanks for that we have one question also from the audience coming in i would like to um well challenge you um for an answer someone is asking do you see a greater use and more diverse use cases of non-real-time content maybe this goes more in direction of you john yeah absolutely um do and i think there's been a couple of questions actually which i'll i'll bring together there which is the in more diverse use cases and also sort of enhanced use of machine learning ai type tools but absolutely we do and i'm just going to refer down to my notes here in terms of the survey it's something like over 30 firms felt there were challenges around those additional use cases the ones that we're seeing are a traditional non-real-time use case would have been an end-of-day security of interest list i need to price these thousand instruments please give me the end of day promise for these thousand instruments over the past 18 months or so what we've seen is i'd like to see 20 years worth of end of day prices please for the entire exchange or for the entire asset class and those types of analytical queries rather than processing queries have been increasing so we are seeing more um diverse use cases for non-real time particularly around product creation or analysis where organizations are looking for insight now the pandemic gave us a system shock um prior to that we had to go back to 2008 of course the people were going back to 2008 and beyond to get that system shock to build those into their models the pandemic gave us a more recent system shock but still doesn't mean people aren't going back over long periods of time looking at historic data and that that's that's a more uh current use case i would say of of non-real time that we've seen and that lends itself to the other question about use of machine learning ai we're seeing people wanting to apply those tools both at the beginning and at the end at the beginning around quality assurance making sure the data is high quality and then at the end what insights can and this data give us so absolutely in response to that definitely seeing more diverse use cases of non-real-time content thanks for that i believe there are a couple other questionsthat are coming up we will um get back to those i have also another question on my list for the both of you in in terms of uh looking for looking but ahead you know in the next 12 months let's say something around that how do you see firms evolving their approach to market and reference data over that period let's say 12 months okay well i think it's certainly fair to say we're going to see a lot more of the same over the next 12 months i think the certainly the survey showed that firms are going to continue to increase the amount of data that they purchase as well as spending on data management tools and for example we're expecting firms to see to increase their investment in data governance that we've touched on today and really improve data quality for use cases

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and such as artificial intelligence and machine learning and speaking with our customers i think there's again these cultural changes that i touched on earlier are really starting to be recognized and and they're implementing these data governance programs i think will have really positive side effects and again we've touched on on the collaboration but i think there's broader impacts as well across data management approaches um within firms and then there was another area i think within the survey where we showed considerable activity over the next 12 months in that space of operational resilience and that we've also touched on as well and quite a staggering statistic i think it was around 84 percent of respondents are actually working on implementing an operational resilience framework over the next year so again a really hot topic for our customers in the coming months um and i think again what we will see from the regulatory perspective is their increase in in focus on operational resilience as well and i think we're seeing that coming through and definitely in the plans that our customers have but ultimately just before handing over to john i think i'd say the continuation of moving to that that more data centric model is going to really help here i think firms continuing to focus on that cultural change and that's important and not just implementing data governance programs but really investing and enhancing what firms have today many firms already have programs in place today it really is the continued investment in that space and i have to say i think certainly from a real-time perspective we will see that pace that accelerated pace and within digitalization absolutely continuing in the next 12 months we're seeing no signs of that slowing down for our customers and again i do hope that what that brings with it is a degree of simplification flexibility scalability and agility for our customers in terms of how they can consume use and distribute data within their organizations so these are exciting times but i think certainly what we're hearing from the survey is consumer firms are really struggling with many pressures their face today um across all these areas and i think the the increased focus will be to balance those out and to really unlock the true value of data and make sure they can really get that strong return on their investment and i think as well as firms evolving it's us evolving as a vendor i mean i think it's what do we see the demands from our clients being and i touched on this data process process to data sort of paradigm shift that to me is is me in the mid 80s records tapes and cds onto a tape for the car versus today i sit in the car and i just log into my spotify account and i call up a playlist it's it's moving to that type of it's not no longer moving physical data in physical file formats because of a latency spectrum to an organization it's that company coming to us and saying i'd like to see this data on this latency paradigm please please i just access it and and that's the shift that we'll be making in response to our clients are asking for and i think that's where our clients want to go is more to that that process to data type paradigm so i'm hopeful that's what we will see over the next 12 months or so certainly what we're driving for um because i think it enables a lot of what um we've spoken about in this session as well as addressing some of the challenges that organizations have once you once you've got the data inside your firewall you've got data issues challenges lineage all those things to address if you can come up the data let us do it that's that's our day job probably this is really the the biggest uh challenge also we we see a shift we see many surveys have also mentioned that um there has been an increase uh people are pushing much much you know much much more than before to get different departments get connected better to be more efficient to become better at what they do to be more flexible because it hasn't been a priority before the pandemic it seems now it's becoming you know more and more important because more companies are seeing also a shift in how fast they become can become better because of the combination of exactly what you also mentioned at janelle before you know optimizing the processes do you as a last question also from my side do you both think that this really is the biggest um challenge now for the companies to really combine those different departments get you know change the processes maybe not integrate more processes and make it more efficient by you know um getting getting those departments connected in order to for everyone to see what we have and where and and you know having this more accessible probably i think it's definitely one of the top priorities and i think again like you

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say firms have had to work really hard in a virtual environment to connect people to connect processes tools um and to keep moving forward as a business so i think if you look at areas such as mobile data and how data has to now be used in very different ways on the go in different environments and different speed connections and it really has quite revolutionized the way we've had to think about that for our customers and we understand that many firms going forward are going to be working in these hybrid environments so as far as we hear that's not going to go away anytime soon so i think it's a great opportunity for us to really be open in the way that we deliver and we connect our customers to data and i think it's a great chance for our customers as well to really think about how how they work openly both in terms of operationally with each other but also in terms of connecting the data yeah agreed and i think i think the challenge the real challenge is doing it in flight is is you still have to run a business you still have to meet regulated requirements you still have to support those processes whilst at the same time trying to get to an architecture that enables all of this great analysis and insight that people are striving for and i think that's that's the real challenge and that there i would say look look people like us look to know your vendor and say what what can you do for me in terms of um what are you doing around your data and i know that's something janelle and i spend most of our days talking to our internal teams about how we're going to facilitate that to help our clients so yeah that i think is the biggest challenge is is moving but moving in flight thank you so much i'd like to close down this conversation it has been a really nice uh ending and a very nice message so thank you both for your input and hoping to well have you soon back in the show thank you pleasure thank thank you if you enjoyed today's episode in the conversation you can download the full report by using the link in the comments or by scanning the qr code that you see right here in the screen thanks for attending and hoping to see you soon