Bakig & Fiacial Services White Paper Cloud Solutios for Cetralized Referece Maagemet
About the Authors Sriivasa Kumar Yerchuru Sriivasa heads the Capital Markets practice at TCS ad has over 20 years of experiece workig with bakig ad fiacial services customers. He spearheads large strategic programs across capital markets ad other market iitiatives. His areas of iterest iclude ivestmet bakig, private wealth maagemet ad asset maagemet. He holds a master's degree from the Idia Istitute of Sciece, Bagalore. Gaesh Padmaabha Gaesh has seve years of experiece i IT solutios ad cosultig i the Capital Markets domai. He has worked with leadig market ifrastructure firms o iitiatives related to corporate actios ad settlemets. Gaesh holds a master's degree i busiess admiistratio from the S. P. Jai Ceter of Maagemet, Sigapore. Ramakoteswara Rao T Ramakoteswara Rao has over 15 years of experiece workig with maufacturig, retail, bakig ad capital markets customers across the US, the UK ad Europe. His areas of iterest iclude large program maagemet, wealth maagemet ad related idustry iitiatives. Rao holds a master's degree i mechaical egieerig from IIT, Madras.
Due to the repercussios of the global fiacial crisis, most bakig ad fiacial istitutios are seekig iovative ways to improve efficiecies ad cotai costs. Fiacial istitutios are examiig their busiess processes ad idetifyig ew fuctios that ca be maaged effectively by their outsourcig parter. Referece Maagemet (RDM) curretly revolves aroud data quality, itegratio betwee data elemets ad flexibility to meet regulatory demads. Over the years, cetralizatio ad stadardizatio of data maagemet ad reducig risks ad costs have bee the prime motives for trasformatio programs whe the techology has bee available at a reasoable cost. Such trasformatios have resulted i icreased automatio ad higher straight through processig (STP) with a special focus o cetralized solutios istead of siloed data processig methods. Today, maagig referece ad master data offers o differetiatio ad there is o competitive cost advatage i maitaiig systems separately ad liaisig with multiple etities such as data vedors, techology vedors, iteral IT teams ad cliet teams. Despite use of improper referece data resultig i fixes o trade data, may capital market firms cosider the cost of maitaiig referece data withi the firm as a uecessary overhead. As a result, capital market firms are adoptig a platform based approach for RDM that has resulted i icreased process efficiecies though o measures have bee iitiated to improve the data quality. Thus, it is ecessary for the firms usig data from various sources to develop their ow expertise to improve the data quality through strog goverace mechaisms ad iformatio maagemet tools.
Despite havig failed to address data quality issues, may data vedors ad techology solutio providers are offerig a flexible approach to RDM, as the demad for a cetralized utility for data maagemet grows. A cetralized utility would help to address the issues related to system deploymet ad efficiecies. The emergece of a cetralized utility model for referece data maagemet is curretly evolvig ad idustrializatio of such a model requires cosesus ad collaboratio betwee multiple market participats, data vedors, techology solutio providers ad regulators. I the iterim, firms eed to explore optios to adopt ext geeratio techology services such as RDM as a service (maaged service model) ad cloud or data virtualizatio techiques. Oe optio is to adopt a cloud-based cetralized eterprise data maagemet solutio that esures improved risk maagemet, regulatory compliace ad maximizes operatioal efficiecy across the eterprise. To couter icreased pressures, fiacial istitutios are evaluatig the optio of cloud-based hostig, maiteace, moitorig, ad support of referece data systems i a attempt to uderstad if it ca result i improved cost ad operatioal efficiecies. The objective is to explore the optios of promotig o-demad data sharig betwee tradig, sales, referece data, market data, ad fiacial cotrol systems.
Cotets 1. Itroductio 6 The Curret Sceario 6 Challeges i Referece Maagemet 6 Referece Maagemet Solutios Available Today 7 Comparig Maagemet Models 8 2. Settig up a Flexible ad Scalable RDM solutio 9 Cetralized Maagemet A Strategic Approach 10 Beefits of Cloud Solutios for Referece Maagemet 11 Maagemet through a Cetralized Referece Utility 13 3. Coclusio 14 4. Further Readig 15
Itroductio Over the years, most research, products ad solutios have focused o distributed referece data platforms which ca be scaled at the eterprise level. Most fiacial istitutios are egaged i itegratig the eterprise data maagemet program with referece data icludig legal etity data, istrumet data, pricig, corporate actios, stadig settlemet istructios, ad cliet data. The cocept of a sigle or cetralized referece data platform was triggered by the eed to reduce maual itervetio, speed up the o-boardig process, simplify risk aalysis, expedite regulatory reportig ad improve automatio, thereby achievig higher operatioal efficiecies. The Curret Sceario Referece data is cosumed across the securities processig value chai. Despite techological advaces, the problems related to faulty referece data, misiterpreted corporate actios ad higher recociliatio efforts cotiue to exist leadig to icreased operatioal risks ad costs. Orgaizatios icur lower costs by fixig faulty trasactios at the iitial stages of the trade process as compared to later stages. Losses due to iaccurate processig of corporate actio, bad data or misiterpretatio of data accout for five to eight percet of firms operatioal costs. Today, the referece data space is teemig with products icludig Eagle PACETM, ad GoldeSource amog others. Firms ca ow choose from multiple referece data products for each busiess lie, ad are thus spedig more o sourcig data from various data vedors, leadig to high maiteace costs ad complex work flows, requirig a large umber of resources to maitai the processes ad systems. Although expediture o referece data ca be lowered through outsourcig, the implemetatio cost cotiues to rise as the solutio will eed to itegrate with legacy applicatios. Additioally, these products caot address some challeges related to data acquisitio, maiteace, ad maagig ad distributig data to the core applicatios. Firms ofte duplicate processes to perform the same tasks for a idetical outcome ad these processes lack the ability to use straight through processig (STP) for timely trade settlemet. Challeges i Referece Maagemet Some of the specific challeges that surroud RDM across the securities value chai from a operatioal perspective iclude: Time cosumig customer o-boardig process ad lack of a sigle view of cliet ad product details resultig i limited up-sell ad cross-sell opportuities for the fiacial istitutios Iaccurate statemets due to icosistet cliet ad product data leadig to poor cliet reportig ad maagemet Pricig errors ad ieffective pre-trade aalysis due to erroeous data resultig i iaccurate quotes Poor risk maagemet ad assessmets due to iaccurate couterparty ad trade book data Icreased settlemet errors, recociliatio issues, trade breaks ad icorrect paymet istructios ad higher maual itervetios due to delay i capturig market data 6
Poor real time risk reportig systems due to lesser P&L cotrol, market risk exposure, duplicate trades ad trade failures due to o-availability of data Poor cliet services as a result of iaccurate calculatio of brokerage fees, commissios ad stamp duties Maual processig of corporate actios, etitlemets ad cliet otificatios resultig i icreased recociliatio of corporate actio processes. Costatly evolvig regulatory eviromet with emergig regulatios like FATCA ad LEI sigificatly impactig referece data Existece of multiple data sources ad processig of data i silos leadig to iefficiecies To reduce the data quality issues, firms eed to itegrate: Differet types of referece data such as fiacial istrumet data, idexes, Exchage Traded Fuds (ETF)s, legal etity idetifiers ad corporate actios data with eterprise data Corporate actios ad couterparty data with the firm's data maagemet system Referece Maagemet Solutios Available Today Large firms adopt siloed data systems ad source data from differet service providers based o cosumptio by differet busiess uits leadig to duplicatio of referece data. Followig a merger or a acquisitio, firms expad ad grow geographically ad adopt siloed solutios resultig i differet RDM systems ad databases that ca lead to itegratio difficulties. I additio to the above complexities, firms ivest i complex platforms to store varied market data icludig tick size, price ad curve rates amog others. While the use of referece data products from leadig vedors like Asset Cotrol, Eagle PACETM, Iformatica - Siperia, Oracle Siebel ad GoldeSource is icreasig, may firms still cotiue to maitai referece data i legacy systems ad itegrate with web-based solutios through Service Orieted Architecture (SOA) or message bus. The referece data products customize the meta data model ad adopt either a cetralized or federated approach based o busiess eeds. Table 3 shows some of the models through which firms maage referece data. Models Solutio Approach Descriptios Maturity Shared Service I premise Federated A cetralized expert team comprisig the software vedor, operatios ad applicatio maiteace teams support operatios ad maitai the RDM platform ad delivery systems High Maaged Services I premise Federated ad Cetralized A dedicated ADM vedor offers related ed to ed service ipremise with platform implemetatio ad support Medium Hosted Solutios Out of premise Cetralized RDM assets are take out of the cliet premise ad the etire platform is hosted i the vedor's data cetre. ADM ad ifrastructure services are provided from vedor premise Low Utility Out of premise Cetralized Build ad develop idustry reowed platform maaged by a sigle vedor Extremely low Table 3: Referece Maagemet Models 7
With regard to outsourcig, may firms are movig to a shared services/maaged services model for referece data system maagemet. Adoptig idustry products ad a shared services model for maiteace offers o competitive advatage; hece firms look for a more commoditized model for referece data. Usig a combiatio of tools for data maagemet, data resource firms ad third party data service vedors are providig ormalized data through a maaged services model offerig Referece as a Service. The third party data vedor would maage commoditized referece data by providig a sigle stadardized golde copy of the referece data by ormalizig, cleasig, validatig ad aggregatig data from multiple sources ad streamig it to customers through a maaged service. Comparig Maagemet Models I geeral, firms adopt two types of data maagemet models, federated or cetralized. Though the cetralized model is cosidered to be traditioal ad easy to implemet, chages i busiess requiremets make it complex leadig to a loger developmet cycle. O the other had, federated architecture offers quick turaroud i implemetatio but leads to silo-based processig ad itegratio challeges. Table 4 compares the federated ad cetralized data maagemet models. Federated Cetralized Maitais separate data elemets usig cross refereces or idetifiers Requires a hub ad spoke framework where data is eriched locally ad retais cotrol of the ehacemets ad dissemiatio of iformatio Creates iefficiecies as data is processed i silos Provides a solutio that quickly respods to chagig markets, demads ad regulatios, ad eables quick expasio ito other asset classes Ca accommodate retail baks ad istitutios with limited products ad geographical scope Maitais a sigle source of data offerig a high degree of cotrol. Processes data cetrally leadig to improved efficiecy Creates ecoomies of scale through cetralizatio ad offers local flexibility Provides operatioal itegrity, quickly meetig highvolume ad rapid respose eeds Requires loger implemetatio time whe there is a chage i market demad Ca accommodate large baks with multiple lies of busiess ad vast geographical footprit Table 4: Compariso of Federated ad Cetralized Maagemet Models Both the models have pros ad cos ad firms eed to adopt the right model, framework ad architecture to attai a flexible ad cost-efficiet data maagemet solutio. These models primarily help i addressig deploymet ad efficiecy issues but do ot address the data quality challeges curretly faced by the firms. To improve data quality, firms eed to develop expertise by creatig ceters of excellece ad usig the best iformatio maagemet tools. By adoptig a cetralized model, firms ca geerate a customized golde copy of referece data to meet demad ad elimiate process redudacies ad fragmeted data sources. 8
Settig up a Flexible ad Scalable RDM solutio To meet the curret busiess eeds uder volatile coditios, securities firms eed to adopt the right approach, framework, data architecture ad model. The right approach should have the ability to offer cost efficiecies alog with flexibility to scale up ifrastructure capabilities. Table 5 depicts the various phases of maturity o a timescale i maagig referece data by describig the saliet features of the recommeded model, its beefits ad limitatios. Phase 1 Phase 2 Phase 3 Cetralizatio Cloud based delivery system Utility based model Short term Medium Term Log Term Cetralize data maagemet through the implemetatio of a platform techology (like GoldeSource, Eagle PACETM) ad build a cetralized team for maagig the data capture ad distributio. Alteratively, create a data goverace model ad data maagemet framework Cotiue with a data hub, maitai cross referece ad cetrally maage the sourcig ad distributio of services ad mutualize the operatios ad support for RDM for the existig federated architecture Move the commo referece data to a cetral repository ad retai the specialized referece data maaged by the respective LOBs Trasfer the RDM assets to a vedor to host the ifrastructure ad applicatios usig a private or hybrid cloud solutio Adopt a vedor-specific o-demad or cloud based data maagemet solutio while retaiig data delivery o-premise Beefits Expad icome streams by supportig a sigle data platform maagemet ad mutualize operatio support i a cloud eviromet Icrease efficiecies through process ad techology automatio with lea data sourcig methods ad expad the platform/utility to service multiple cliets. Develop a scalable model by creatig ceters of excellece ad build expertise by usig iformatio maagemet tools to improve data quality Improves process efficiecies through cetralizatio Reduces costs by elimiatig redudacies i sourcig ad replicatio of data Provides more cotrol ad improves data itegrity Reduces TCO by hostig the RDM asse i a cloud eviromet Utilizes resources effectively Reduces the time for implemetatio for future busiess demads ad eeds Limitatios Achieves ecoomies of scale Provides a more flexible, cofigurable ad scalable solutio Results i faster implemetatio, iformatio updates ad time to market. Requires exceptio based processig Requires loger lead time for implemetatio Caot achieve ecoomies of scale Creates itegratio challeges for the dowstream applicatios betwee cloud ad o-cloud applicatios ad betwee various data providers for sourcig data Presets cocers over data privacy ad cloud security Requires a stadardized meta data model ad goverace mechaism Requires more effort for providig customized solutios ad complexity i segregatio of data Table 5: Recommeded approach, beefits ad limitatios for maagig referece 9
Cetralized Maagemet A Strategic Approach May ivestmet baks have implemeted multi-year eterprise data maagemet programs aimed at itegratio of referece data icludig legal etity data, istrumet data, pricig, corporate actios ad stadig settlemet istructios ad cliet data. A scalable, flexible platform based solutio capable of providig cost ad operatioal efficiecies that reduces maual itervetio, speeds up the o-boardig process, simplifies risk aalysis ad regulatory reportig ad icreases automatio is ecessary to meet firms' busiess eeds. A strategic approach would be to automate referece data maagemet across the value chai by defiig a cetralized model as show i Figure 2. source Market Feeds Third Party Feeds Corporate Actios LEI Feeds Stadig settlemet istructios Couter Party Feed Hadler & Maagemet Validatio Delivery Cetralized RDM Mappig Scrubbig Trasform Distributio & Maagmet Securities Ivestmets Value Chai Sales & Product Order Maagemet Trade Executio Positio Maagemet Risk Maagemet Paymet Clearig & Settlemet Regulatio & Compliace Source: TCS Iteral Figure 2: Cetralized Referece usage across securities settlemet value chai 10
Figure 3 is a schematic represetatio of a cetralized RDM solutio. GUI Apps XML File Formats Reports APIs (Ope Architecture) / Web services Exteral Vedor Feeds Market F E E D H A N D L E R Coectivity & Feed Processig Rules & Cofiguratio Maagemet Maagemet Moitorig Tools Aalytics Distributio Exceptios Hadlig & Maagemet Work Flow Maagemet APIs (Ope Architecture) / web services Frot Office Mid Office Back Office Reports Meta Source: TCS Iteral Logical Repository Reportig base Figure 3: Referece Architecture for Cetralized RDM Beefits of Cloud Solutios for Referece Maagemet Market data is widely cosumed by ivestmet baks, hedge fuds, wealth maagemet firms ad other proprietary tradig firms, ad is a critical iput for their tradig strategies spaig across global markets. Hece, may exchages such as NASDAQ, NYSE, ad CME have started offerig public market data as a cloud computig service to market participats. The mai challeges i maitaiig a iteral market data ifrastructure iclude latecy issues, costat chages ad modificatios to feed hadlers ad cachig systems, ad high cost ad effort to adapt to mior chages. Besides, data maagemet for corporate actios, which requires additioal effort to capture, route, scrub, recocile, store ad redistribute data withi the orgaizatio, is also a challege. Also, there are challeges withi the orgaizatio to cetralize referece data maagemet ad build the ecessary etwork ad services ifrastructure to distribute it globally to cosumig applicatios. Though cloud adoptio has gaied mometum, challeges aroud data sesitivity ad security cotiue to exist ad eed to be addressed. A cloud-based techology solutio ca deliver cost savigs i the followig areas data ceter, developmet efforts, testig cycles, operatioal efforts i maagig data - ad also help improve scalability. 11
Multiple platform providers offer cloud-based or o-demad data scrubbig solutios ad deliver the clea data i the required format or load it to the eterprise data warehouse. Cloud-based solutios ca be game chagers oly if they are scaled to a cetralized utility o a multi teated platform. For istace, if security master data ca be maaged i the cloud, data ca be delivered directly to the dowstream systems thereby elimiatig storage requiremets, o-premise maiteace of the securities master data ad related ifrastructure. A alterative meas of accessig data is through a web browser. Cloud-based MDM or RDM solutios will completely reshape the data service vedor, techology parter ad outsourcig service provider ladscapes with serious busiess implicatios. Usig a cloud-based model, firms ca address some of the key cocers ad issues i the referece data maagemet domai: Weak/legacy ifrastructure ad custom built RDM system Cotiuously chagig regulatory ladscape Costat chages to dowstream systems Modificatios to feed hadlers ad cachig systems Firms ca shift to a cloud-based solutio i two ways: Optio 1 Move from a stadaloe MDM or RDM software to a vedor specific o-demad or cloud-based solutio where data maagemet is performed o the cloud Optio 2 - Host the etire RDM ifrastructure o a cloud data ceter, perform data maagemet activities ad trasfer the ormalized data to a operatioal data store, which resides o cliet premises, ad the trasfer the data to dowstream applicatios A cloud-based RDM solutio should be able to deliver data via sophisticated web Applicatio Programmig Iterfaces (APIs) that ca easily itegrate ito o-premise operatioal data stores. This mechaism also helps address the data privacy ad security cocers. The solutio should have the capability to itegrate may data sources such as data vedor ad exchage, ad cetral securities depositories. The data maagemet solutio should esure data itegrity by adoptig logical ad rule-based data cleasig processes. The solutio should be able to aggregate data from differet sources, erich, scrub ad perform recociliatio at a record level, ad the deliver ormalized data i differet formats files or feeds for cosumptio or to a operatioal data store residig i the cliet premise. This data ca be further distributed for cosumptio to various applicatios. The data sychroizatio ad replicatios to the operatio data stores should be tued with defied frequecies so that data is refreshed i real time or itraday depedig o the applicatios cosumig mode ad itegratio techiques. Orgaizatios ca derive multiple busiess beefits from cloud-based RDM solutios icludig improved operatioal efficiecy owig to a higher degree of automatio ad reduced total cost of owership (TCO). Cloudbased RDM solutios also help lower busiess risk by reducig trade exceptios ad breaks ad elimiate errors associated with maual processes. Additioally, by usig flexible web APIs, real-time ad referetial market data is itegrated ito a spreadsheet eablig advisors to cosider cuttig the cord o termials altogether. The iheret flexibility of cloud-based RDM solutios help improve time-to-market by allowig modificatios to the applicatio to quickly respod to chages i compliace requiremets. 12
Maagemet through a Cetralized Referece Utility The cocept of a cetralized utility for referece data maagemet is evolvig as most firms recogize that maagig referece data i-house or through a outsourcig vedor is either competitive or a core activity. Referece data such as istrumet data, corporate actios data ad couter party data are the same for all firms ad ca be applied uiversally i the market place. I the curret sceario, may firms icur costs ad exped effort whe they receive faulty data or files from the existig vedor. This effort is duplicated across the market place ad resolves commo issues facig all firms. By adoptig a cetralized utility, firms ca maage their resources ad capital effectively ad focus o core activities. Furthermore, may regulators are aligig their regulatios ad policies to ecourage the establishmet of cetralized data repositories to miimize systemic risks. A few of these are listed below. Securities ad Exchage Commissio s (SEC) EDGAR corporate filig, a repository of corporate fiacial iformatio Europea Cetral Bak (ECB) is proposig a referece data utility The Committee of Europea Securities Regulators (CESR) developmet of its ow cetral referece data repository The effort of buildig data repositories is overlappig across geographies ad addig complexities by itroducig additioal stadards ad silo based processig of data, trasactios ad positio iformatio. O the other had, the idustry is aimig ad lookig at a sigle global solutio, stadard ad mechaism for referece data maagemet. I lieu of a sigle RDM solutio, some market ifrastructure firms are collaboratig with techology providers to provide ormalized ad clea data through a cetralized utility based o the maaged services model. These utilities validate, correct, erich ad maitai busiess etity referece data from various sources ad provide a sigle feed or file to the ivestmet firms which i tur take care of distributig the data to dowstream applicatios. Firms such as Deutsche Borse s/dtcc Avox subsidiary are supportig a collaboratio of over 25 fiacial istitutios, icludig ivestmet baks ad asset maagemet compaies, which share their idepedetly sourced busiess etity data to esure accuracy ad compatibility. Some of the utilities that could emerge i the idustry are: Securities master utility to maage equity ad fixed icome istrumets, issuers, bechmarks ad idices Market data ad prices utility to maage prices, yields, ratigs, duratios, iterest rates, foreig exchage rates, historical prices, closig prices, time series, volatilities, correlatios, ad factors Couter party data maagemet utility to maage couter parties, fuds, tradig etities, agets, guarators, trasfer agets, registrars, payig agets ad custodia idetities Corporate actios data utility to maage corporate evets like stock splits, proxy otificatios, mergers, teders, divided ad iterest declaratios, ad capital distributios Cliet delivery/settlemet istructio data bases to maage the stadig settlemet istructios 13
To build ad provide data maagemet solutios ad services through a cetralized utility, the followig aspects should be cosidered: Collaborative approach ad cooperatio of idustry participats to develop a multi-teated model with miimal switchig costs. Cosesus o further stadardizatio ad frameworks A uiversally acceptable meta data model ad architectural stadards Idetificatio of critical data sources, ratioalizatio as per idustry demad ad addressig jurisdictioal factors A mechaism to itegrate cliet systems ad data stores privacy/security requiremets i maagig the data repository A solutio to quickly respod to chagig markets, demads ad regulatios ad sped less time expadig ito other geographies ad asset classes Issues related to owership, liability ad sharig of legal risks To realize success, a utility model requires critical mass ad ecoomies of scale. To achieve this, market ifrastructure firms would eed to take the driver s seat to address idustry problems i partership with techology providers. Such a approach would be easier ad quicker, ad result i a viable solutio to successfully maage ad meet service levels. As market ifrastructure firms such as Cetral Securities Depositories (CSDs) i Europe are losig reveue to market iitiatives like Target 2-Securities (T2S), buildig a cetralized RDM utility o a maaged services model ad offerig data as a service to market participats ca potetially become a ew reveue stream for CSDs. Coclusio With the icrease i the diversity of data ad volume of trasactios, firms are strugglig to idetify ad resolve the uderlyig cause of referece data mismatches that result i costs to fix them. Most ivestmet firms are i favor of outsourcig both the techology ad operatios i the referece data maagemet domai. There has bee icrease i the maturatio of referece data maagemet with icreased focus o improvig efficiecies. Cost savigs coupled with the eed for a reliable ad scalable distributio mechaism across applicatios have bee importat drivers for data cosumptio. We uderstad that the cost of fixig broke trades or trasactios is icreasig expoetially ad the mai reaso for such a icrease is iefficiecies i the data maagemet process. Outsourcig software implemetatio ad mutualizatio of operatios has resulted i poor ecoomies of scale ad iferior data quality. Hece there is scope for commoditizatio of cetralized referece data maagemet usig a cloud computig solutio. 14
service providers such as Iteractive Corporatio ad XSP have moved to the cloud ad adopted a SaaS applicatio to provide fiacial istitutios with access to Global Corporate Actios. With the market shapig up to embrace cetralized referece data maagemet, cloud-based solutios will eable firms to reduce operatig costs ad complexity. Such a solutio would focus o servicig iteral ad exteral customers ad help them become result drive, agile ad extesible i distributig the referece data to dowstream applicatios with miimal impact o applicatios that are affected due to referece data chage. I geeral, RDM is trasformig from complex, federated, o-premise systems to a combiatio of complex, federated, o-premise ad cloud-based systems. With applicatios cosumig data from referece or master data maagemet databases movig to cloud-based ad as a Service platforms, it is imperative that RDM follows suit. As a result, the data maagemet fuctio will soo be commoditized ad evolve ito the as a Service (DaaS) model. Further readig 1. Waterstechology - Referece Techology: Special Report, Iside Referece, Jue 2012 2. EuroClear - Jo Va de Velde, Philippe Chambadal : A New Cetral Utility To Maage Challeges 3. Fiacialitergroup - Ifrastructure issues i the securities idustry: The case for a cetral couterparty for data maagemet 4. EDM Coucil, Quality Compariso ad Aalysis of Securities Referece, 6th Jauary, 2009 5. Alla D.Grody, Fotios C. Harmatzis, Gregory J. Kaple - Operatioal Risk ad Referece : Explorig Costs, Capital Requiremets ad Risk Mitigatio, November, 2005 6. Europea Cetral Bak - Securities Referece Utility: A outlie of the cocept, 11th May, 2009 7. Euroclear - Cetral utility for securities referece data, 2013 15
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