Trade Surveillance for MiFID

Access unique insights into trading behaviour, including a suite of market abuse and financial crime alerts, with Trade Surveillance for MiFID.

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Reinforce your trade surveillance with our multi-asset class, multi-market surveillance solution for market participants in scope for MiFID II

In Europe and the UK, national competent authorities use transaction reporting data and order record keeping data to detect market abuse within their automated surveillance systems.

The Market Abuse Regulation (MAR) expects firms to use multi-asset, multi-market surveillance to identify market abuse and financial crime​ – but existing surveillance systems have limitations. Data costs to build advanced multi-asset solutions are prohibitive, while the complexity of linking behaviour across asset classes is still a challenge for the industry.

Trade Surveillance for MiFID offers a unique solution to these challenges. It provides a complex but cost-effective European multi-market surveillance tool that delivers alerts to clients based on data already held by LSEG.

By combining multi-asset transaction chains with public market data, it assists firms in gaining an advanced view of their likely regulatory risk. 

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Trade Surveillace for MIFID

[Music Plays]MiFID II created a significant shift in the regulatory landscape and has led to changes in how firms operate across borders, particularly following Brexit. Execution venues have multiplied.Transparency requirements are tougher. In-house surveillance builds remain prohibitively expensivedue to the complexity of consuming multiple market data feeds. Inefficient solutions generate large numbers of false positives. LSEG’s Trade Surveillance for MiFIDis designed to leverage your existing data.It provides post-trade alerts and unique insights into trading behaviour.Featuringcross-product, cross-venue market abuse and financial crime alertsMarket Replay with a consolidated UK and EU order bookand behavioural anomaly detection.Trade Surveillance for MiFIDuses similar methodologies and datasets to UK and EU regulatorsto identify potential market abuse.By combining your transaction reporting datawith a consolidated UK and EU order bookin LSEG’s proprietary data lake……we will help you to analyse complex cross-market, cross-product manipulation,and better understand your regulatory risk.Contact our team to learn more about LSEG Trade Surveillance.LSEG. Make more possible.Contact us at regreportingsolutions@lseg.com

TRADE SURVEILLANCE FOR MIFID: EXPERT DISCUSSION

Hello and welcome to this conversationin which we're talking about LSEG Trade Surveillanceand how it can help companies comply with theirregulatory reporting obligations set out in MiFID II.I'm Bruce Kellaway, CEO of Regulatory Reporting Solutions at LSEG.And today I'm joined by Liam Smiththe COO of the London Stock Exchange.Before we begin, this is being recorded.So if you have any questionsor you want to get in touch with usdo please send them through to our emailregreportingsales@lseg.comLiam, thanks very much for joining us.Thanks very much, Bruce, nice to be here.Before we dive into the detail.Perhaps you could set the sceneand explain why trade surveillancehas become such an important topicfor firms operating under MiFID II today.So trade surveillance has developed fromtrading moving from principally open outcry exchangeson the trading floors into electronic trading clearly.and the surveillance industry has followed that.So over the last 10 to 20 yearstrade surveillance has become quite a substantial industryand probably the most data heavy industryin the compliance sidewith heavy data requirements forinvestment to manage and detect market abuse.Aligned to thatMiFID IIand the Market Abuse Regulation in Europereally raised the levelof the regulatory requirements that investment firmshad to meet for market abuse detection.MAR very precisely set out systems and controls and procedures and typologieswithin European and UK law and how to conduct market abuse surveillanceand MiFID II really raised the bar in terms of the regulatory data sets,how technical they are and how they’re utilised by regulators.So these factors and in terms of the amount of datathat goes through trading platforms, that's what's led to againthe increasing scrutiny around trade surveillance practices.With regulators starting to look at all that dataI presume they're beginning to takea much more holistic view across the trading data set.Maybe you could explain what you would see as a practitionerwhat you see as the hardest things for firms to cope with today.From an investment firm perspectivethe amount of data that you have to deal with is a real issue.All of us now are using cloud based systems,ingesting huge amounts of data.Complex, costly andit's all very well taken in the data you've got to get outputs from the data.So in terms of an actual issue with trade surveillance,it's what reference data do you have to align to thishow fragmented is the market construct.How do I actually understand cross product market manipulation?How am I able to get that into a time series and get a sensible output to it?So these are the sort of practical challengesthat trade surveillance firms provideand particularly its how the MiFID II transaction reporting data set,the RCS22 data set that regulators use,that goes through Regulatory Reporting Solutions,that data is really deliberately been evolved and progressedto allow competent authorities in Europe to detect market abuse.So that's very deliberate.There's a lot of advantages about how they put those data sets together.But it's a complex task for all participants to have to handle that.You keep you keep touching on the word data.I guess maybe you could talk to us about why data quality is important.and how complex that is to stitch together.Data without context doesn't mean anythingand in a real sensein the trade surveillance industry obviouslywe broadly run alert algorithms that detect patterns of behavior.There can be quite a siloed approach on an asset class.You mentioned at the outsetabout trade surveillance, how it's evolved or how it looks.Trade surveillance broadly began with exchange traded products.You know, cash equities central limit order book detection.So time series data very clearbut now certainly with the market abuse regulationI have a requirement to conduct cross product manipulation or cross market.So if a trader is conducting the hedge of an equities options tradeand they're hedging in the cash equities market,I've got to put those two pieces of data together.If I don't put those two pieces of data together,then I might have an alert on one sideand a false negative alert on the other side.But if I look at the overall positionand this data set,this regulatory data set and type of productputs this all together, then I get a good output, I avoid noise.The other point on context is about again the utilisation of reference data.If I don't have context for what is normalfor a trader or a client and so forth.Then again,I'm going to be over alertingI won't have context about what’s genuinely abnormal.So again, that's the you know, at coreit's that that causes false positive alertingnoise in the systems and you just don't get a good output.I think that false positives, and noise as you describe it,I hear lots of customers talk to me about that,how to manage that volume.Maybe that's a segway into explainingwhy you brought LSEG’s trade surveillance product to marketand what you're aiming to achieve.From an LSEG perspective,in terms of the day job or the old day job,we would cover market oversightof the entire London Stock Exchange tradingand the markets that we cover.Actually, our requirements are not too differentfrom an investment firm,an asset manager or an investment bank in that sense,apart from the fact that we're a recognised investment exchange.So we have a requirement to do that live and prevent market abuse,along with the detection of it.Additional to that capabilitywe knew that as a group, we had that capability,but we knew also, obviously, the Regulatory Reporting Solutionsthe ARM,the Approved Reporting Mechanism, that is the principal data setthat is used to detect market abuse by the regulators.65 fields, very deliberately crafted.In a previous lifeI've looked at that data from a regulatory perspectiveat the Financial Conduct Authority.So in terms of being able to detect how it's utilised,how it's put together,we have a lot of that data and we felt that our customerscould benefit from a logical wayof putting surveillance algorithms on that datato give you an advance steer about the riskswithin your entity that you might be exposed to.And as a final point, Bruce, again, as part of the LSEG group,of course, we have a huge amount of global market datafor and we're talking about contextand reference and, you know, correct referencing of data sets.So what we did in LSEG Trade Surveillance, we go,we can probably provide a very sensible,very practical solution that's highly complex,but at a very logical price pointand a very, very easy way to deploy for customers.So that was the background towardsthinking, well,trade surveillance can be very costly.Large implementation problems for customers,not necessarily too effectiveif you don't manage the data well.We felt that we could take away a lot of those problemsand give participants in financial services industrya really good, sensible product to manage your real riskand generate the types of alerts that you really need to see.So that was the backdrop really for the product.Ok, thank you.So with a high quality data and reference setand then aligning the trade data exactlyto what the regulator is looking at.That brings a solution to market, I follow, I follow.So, let's make this tangible.From a firm's perspectivewhat does this actually change day to day?LSEG Trade Surveillance, there's basically threekey areas why this is different from other other platforms.Firstly is the cross asset, cross product capabilitythat LSEG Trade Surveillance has.That is fundamental to the platform.As I've said a few times,it links those data sets together because of the data format.So very deliberately, LSEG Trade Surveillanceis identifying a contextual positionat a trader or an algorithm or a client level,across all asset classes.So inherently, all of our patterns are looking every timeacross product market abuse detection.So that classic problem is probably the most difficult problem for participantsto try and identify cross product because they're running an alerton equities, an alert on futures options, etc.LSEG Trade Surveillance puts that all togetherand that's the great benefit that the regulators haveand it's why obviously I would say this,but everybody really needsto be utilising a product of this sort because this is identifying to youthe same data set and the same risk that the regulators are able to see.That's, I think, the first thing that we really believe in,the second point actually is about methodology.As I've mentioned, we are, as practitioners,there's a deep understanding of how to develop surveillance algorithmsand our statistical methodology is very much aboutlooking for anomaly detection, contextual alertingrelative to an individual or a client or an entity.That methodology is the same.So if you know, for example, if an asset class,if I compare, I don't know, a FTSE 100 UK security to bitcoin.Very different volatility profiles, very different movement profile.We're using the same statistical methodology however to saywell that's an unusual movement for that security in that period.And we've got all of the wealth of reference data to identify thatwe're not just using blunt thresholds.You will know in LSEG Trade Surveillancethat something is unusual,that trading position is unusual for that entity in that instrumentand that instruments movement is genuinely unusual for that.It's not, it's above 5% move trigger an alert type thingand I know that's a very blunt example,but I see a lot of that in the industry still to this day.So again, those two factorsin terms of the data set and thethe methodology,they reduce down the false positives.That's the key driver.The final pointLSEG Trade Surveillance is completely unique.The operational simplicity of taking on the platform.As a customer you don't need to do anything.We already have your datain the Regulatory Reporting Solutions ARM.Nothing to do if you want to use the service,we can switch you on almost overnightand you can utilise the alerting capabilitiesand the UX and the market replay functionalitiesthat you have within the platformcompletely uniquely, no data integration projects.You get that capability immediately.So again, that's what's really driving a lot of the customer interest.Whether I wish to take this as a standalone solution or I wish to take itas something that sense checks the systems and controls that I already have,and we're seeing a lot of that at the higher end of customer.It's a very, very neat tool in which to use.I've certainly heard that from customers already.So I like the points.The cross product, yes, fantastic.Methodology, great.But really ease of adoption.That's what customers are loving that I've spoken to so far.So listen, final thoughts Liamand bit of a leading question and maybe I'll throw to you.So looking aheaddo you think that trade surveillance is becomingever more strategic within firms?Yes, inevitably it is.The data footprint for trade surveillanceis now becoming, arguably, one of the larger data consumerswithin an investment firm.You have to you've got time series data that needs to be consolidated.You have asset classes that need to be linked.You have behavioural profiles that you need to code for,identify for, sense check and iterate around.So trade surveillance and the databases, the data lakesthat are created to support thatare really, really key to both.Obviously the detection for the primary reasonbut the analytical capabilities that that gives to entities as well.So more and more firms are looking to go, well, what do I get out of this.First of all, so there's the understanding of trading behaviours,patterns within the dataand the overall value that that gives you is becoming absolutely strategic.I don't see that trend going anywhere soon,because it's one of the only areasthat you're really pooling together,all of that trading data that you have within an entityin order to get outputs from.So again, we're seeing again utilisation of those capabilities a lot.I think that will continue to grow.Brilliant, very clear, thank you very much.Thank you LiamTo wrap uptrade surveillance under MiFID II isn't getting simpler.Regulatory expectations remain high.Markets remain fragmentedand firms need surveillance approaches that are robust,scalable and aligned with how regulators view risk.For those watching, if you'd like to learn more about how LSEG Trade Surveillance for MiFID works in practice,including how it integrates with Regulatory Reporting Solutions,you can find further details or request a conversation with our team.Remember the emailregreportingsales@lseg.comLiam, once again,thank you very much for joining us.Thank you.

Key Benefits

Gain a holistic view of market activity across fragmented markets
View aggregated trader level exposures across products
Benefit from a statistical methodology that is transparent to customers and regulators
Leverage holistic asset-exposure blueprinted into the system architecture
Save time and resource as a result of fewer false positives
Better understand and analyse complex cross-market, cross-product manipulation
Receive unique insights into unusual trading behaviour
Capitalise on your existing transaction reporting data
Access detailed outputs from large volumes of market data, with no additional implementation costs

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