兰德-信用信息市场的未来（英）-2021.7-70正式版.ppt

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1、Future of the CreditInformation MarketFinal reportFay Dunkerley,Katerina Galai,Charlene Rohr,Emily Gloinson,Marina Favaro,William PhillipsThis research was conducted through RAND Europes Centre for Futures andForesight Studies(CFFS).The CFFS brings together deep expertise in futuresresearch methods

2、along with specialist sector knowledge to help our clients planfor the future in conditions of uncertainty.Commissioned by theFinancial Conduct Authority Copyright 2021 Financial Conduct AuthorityFor more information on this publication,visit www.rand.org/t/RRA608-1Published by the RAND Corporation,

3、Santa Monica,Calif.,and Cambridge,UKR is a registered trademark.RAND Europe is a not-for-profit research organisation that helps to improve policyand decision making through research and analysis.RANDs publications do notnecessarily reflect the opinions of its research clients and sponsors.All right

4、s reserved.No part of this book may be reproduced in any form by anyelectronic or mechanical means(including photocopying,recording,or informationstorage and retrieval)without permission in writing from the sponsor.Support RANDMake a tax-deductible charitable contribution atwww.rand.org/giving/contr

5、ibutewww.rand.orgwww.randeurope.orgPrefaceRAND Europe was commissioned by the Financial Conduct Authority(FCA)to conduct forward-lookingresearch to understand how the credit information market might evolve in the future.The research wasundertaken between July 2019 and December 2020.This report forms

6、 part of the Credit InformationMarket Study(CIMS)undertaken by the FCA.1A rigorous,rigorous,structuredstructured andand expert-led approach expert-led approach was adopted to identify several plausible scenarios of howthe credit information market might develop in five to ten years time.Using a stru

7、ctured scenario methodology and an extensive,iterative expert and stakeholder consultation,this project identified the factors influencing change,built an understanding of how the market mightevolve in the future and the implications of different scenarios.The findings published in this report formp

8、art of the overall evidence base for the Credit Information Market Study.This report contains the findings from:xxPhase 1 Identifying and prioritising key factors that could shape the future of the market;andPhase 2 Developing a number of potential coherent scenario narratives.It also contains detai

9、ls of the underpinning methodologies we used to arrive at the final scenarios.RAND Europe is an independent,not-for-profit policy-research organisation whose mission is to helpimprove policy-and decision-making through objective research and analysis.RAND Europes clientsinclude European governments,

10、institutions,NGOs and firms with a need for rigorous,independent andmultidisciplinary analysis.For more information about the project or this report,please contact:Dr Fay DunkerleySenior Analyst,Home Affairs and Social PolicyRAND EuropeWestbrook Centre,Milton RoadCambridge CB4 1YGUnited KingdomTel.+

11、44(1223)353 329,x2595fdunkerlrandeurope.org1 See FCA 2020b.iiiSummaryRAND Europe was commissioned by the Financial Conduct Authority(FCA)to conduct forward-lookingresearch to understand how the credit information market might evolve in the future.This report formspart of the Credit Information Marke

12、t Study(CIMS)undertaken by the FCA.The credit information market involves a diverse range of stakeholder groups,extending beyond the corerelationship between financial institutions and customers to include credit reference agencies(CRAs),regulators,consumer representatives and FinTech companies,amon

13、g others.In the UK,the FinancialConduct Authority(FCA)plays a key regulatory role in the market.The credit information market is closely linked to the lending markets but can also be influenced by factorsthat are external to these markets.CRAs could potentially face a wider range of competitors who

14、use newand emerging technology to process vast datasets.Consumers attitudes to sharing data may be shaped byexperiences in other sectors,which in turn may be influenced by changes in regulation,such as GDPR.Inthis study,key factors were identified across five areas that could influence the evolution

15、 of the creditinformation market.The five thematic areas and corresponding key factors are depicted in Figure S1 below.Interactions across these five areas were identified as critical in determining the future development of thecredit information and lending markets.Figure S1 Thematic areas and key

16、factors that influence the credit information marketUncertainty in these factors and how they interact could lead to different paths over the next ten years.Scenarios are long-standing tools that are used to explore this uncertainty.The scenario development was underpinned by a structured,expert-led

17、 approachIn this study a structured-scenario development methodology was used.A key feature of this approach isthat the scenarios take account of a range of interrelated factors from both within the credit informationivmarket and other influencing areas exogenous to it.They therefore provide an inte

18、rnally consistent andplausible picture of what may happen both in the credit information market,and within wider society.Structured engagement with experts was a key component of the research approach.To ensure the studywas balanced and did not over-represent one groups interests or a narrow point o

19、f view,the project teamidentified a wide range of relevant disciplines and sectors from which to draw expertise.Inputs from expertsand stakeholders have been used in a structured way throughout the project to develop the key factors thatdescribe the credit information market,understand how these int

20、eract and could develop in the future(factor projections)and select the scenario clusters.Stakeholder consultation was comprised of the followingactivities:scoping interviews,remote survey exercises,workshops,consistency analysis,cross-impact analysisand multiple feedback sessions.Four future scenar

21、ios have been developed for the credit information marketFour scenarios have been developed in the study.These scenarios represent a wide spectrum(envelope)ofpossible futures and are sufficiently differentiated from each other,in terms of credit information and widersocietal developments,to provide

22、a broad test for future policies.The scenarios are written from the vantagepoint of 2030;this timeframe was adopted to reflect both the five-to ten-year horizons of interest for thewider Credit Information Market Study,and a sufficient timespan for the scenarios to be informative froma policymaking

23、perspective.vFour future scenarios for the credit information marketviThe four scenarios provide insights into the implications for the credit information market,the lendingmarkets,consumers and wider society.Below we highlight some of the key observations and lessons.The scenarios play out against

24、a range of economic backdrops.These indicate that,whileeconomic circumstances play a role in consumer demand for credit and that this maydiffer between population segments,consumer demand is also influenced by the cost ofcredit and the willingness and ability of consumers to engage with the markets.

25、CompetitionCompetition andand innovationinnovation in both the credit information and lending markets is akey driver in enabling lenders to access a wider variety of better-quality credit informationat a lower cost.However,where competition is driven by more players in the creditinformation or lendi

26、ng markets,consumers may find the markets more confusing or moredifficult to engage with,making it harder to understand how their data is being used andby whom.While the use of a wider varietyvariety ofof datadata can improve financial inclusion for those withthin files,it could also increase the ab

27、ility of lenders to deliberately promote credit toconsumers that may be unsuitable or unaffordable,and increase the potential for errorsthat could have wide-ranging repercussions.The use of a widerwider varietyvariety ofof datadata andand moremore sophisticatedsophisticated analyticalanalytical tech

28、niquestechniques indecision making should increase the overall quality of lending decisions,as lenders are ableto better-price risk and offer consumers credit products on the most appropriate terms.Although some population segments might benefit,those who have less data availableabout them,or those

29、who are considered less creditworthy,could face more expensiveproducts or less choice.Consumers are more likely to be able to access credit on appropriate terms when they havea higher level of confidenceconfidence in CRAs,and lenders and are more willing to share additionaldata.TechnologyTechnology

30、is both a key enabler and a potential barrier to development in the creditinformation market.While innovation may lead to lower costs and more varied,better-quality data being used,a lack of transparency in decision making or low investment indata security could have a negative impact on consumer co

31、nfidence.viiTable of contentsPreface.iiiSummary.ivTable of contents.viiiFigures.xTables.xiAbbreviations.xiiAcknowledgements.xiii1.Introduction.11.1.1.2.Factors influencing the credit information market.2Report outline.52.Approach.72.1.2.2.2.3.Scenario methodology.7Systematic project implementation.8

32、Stakeholder consultation.133.Future scenarios for the credit information market.153.1.3.2.3.3.3.4.3.5.Future scenarios.15Scenario 1:Widening credit gap.17Scenario 2:Consumer-centric credit.20Scenario 3:Big-Data driven.23Scenario 4:Lenders lead.264.Broader implications.31References.33Annex A.Methodol

33、ogical approach.37Step 1:Determine influencing areas.38Step 2:Identify longlist of factors.39Step 3:Validate influencing areas and longlist of factors.41viiiStep 4:Assess mutual influence.41Step 5:Identify key factors.43Step 6:Inform development of projections for key factors.44Step 7:Conduct consis

34、tency assessment.45Step 8:Identify clusters of plausible futures.45Step 9:Select final set of scenario clusters.47Step 10:Write scenario narratives.48Annex B.Stakeholder engagement.49B.1.Stakeholder consultation methodology.49Annex C.Glossary of terms.55ixFiguresFigure S1 Thematic areas and key fact

35、ors that influence the credit information market.ivFigure 1-1 Areas influencing the future development of the credit information market.3Figure 2-1 Plausible future scenarios should reflect a wide range of possible future states.8Figure 2-2 Overview of project implementation steps,by project phase.9

36、Figure 2-3 Longlist of factors influencing the credit information market.10Figure 2-4 Influence matrix used to conduct cross-impact analysis.11Figure 2-5 Consistency assessment matrix.13Figure 2-6 Stakeholder consultation methodology overview.14Figure 3-1 Factor projections for the scenarios.16Figur

37、e A.1 Overview of project implementation steps by project phase.37Figure A.2 System-level themes and relating factors entered in Scenario Manager.40Figure A.3 System-level themes and longlist of factors.41Figure A.4 Influence matrix used to conduct cross-impact analysis.42Figure A.5 Visualisation of

38、 key factor selection.42Figure A.6 Development of projections in Scenario Manager.44Figure A.7 Consistency assessment in Scenario Manager.45Figure A.8 Cluster analysis in Scenario Manager.46Figure A.9 Cluster analysis and selection in Scenario Manager.47Figure A.10 Scenario clusters assessment and s

39、election in Scenario Manager.47Figure B.1 Stakeholder consultation methodology overview.49xTablesTable A-1 Overview of project steps and deployed methodologies.38Table A.2 Shortlist of 25 important and uncertain factors.44Table B.1 Stakeholder mapping and activity allocation matrix.51Table B.2 Stake

40、holder mapping for the scoping interviews.51Table B-3 Stakeholder mapping for the first survey,workshop and projections.51Table B.4 Stakeholder mapping for the second workshop.52Table B.5 Experts engaged as part of this study.53xiAbbreviationsAIArtificial IntelligenceAPRAnnual Percentage RateCIMSCMA

41、CRADPAFCACredit Information Market StudyCompetition and Markets AuthorityCredit Reference AgencyData Protection Act 2018Financial Conduct AuthorityFinancial TechnologyFinTechGDPRHMGICOGeneral Data Protection RegulationHer Majestys GovernmentInformation Commissioners OfficeMachine LearningMLNGOOFTPoR

42、Non-Governmental OrganisationOffice of Fair TradingPrinciples of ReciprocityPSD2SCOR(Revised)Payment Services DirectiveThe Steering Committee on ReciprocityxiiAcknowledgementsWe have been able to deliver this study because of the input and support of a number of people.Firstly,wewould like to thank

43、the Financial Conduct Authority for sponsoring the study and,in particular,AnishThakrar,Toby Watkinson and David Mendes da Costa for their support and collaboration throughout.We also acknowledge the contribution of James Black and Dr Julia Muravska for their independent reviewof the report.Most imp

44、ortantly,however,we are indebted to the host of external experts who gave their time,enthusiasmand expertise to help us identify the key factors that influence the provision of credit information and itsuse in retail lending markets,and to explore how these might develop in the future.A list of expe

45、rts can befound in Annex B.We emphasise that the views reflected in the report are those of the project team,who remain responsiblefor any errors or omissions herein.xiii1.IntroductionCredit information typically refers to information relevant to the financial standing of an individual.It ismost com

46、monly used by lenders when assessing whether to offer credit to an individual and on what terms.Credit information impacts a significant number of consumers;a third of the UK adult population have amortgage while the majority(approximately 78 per cent)hold at least one credit or loan product.2The cr

47、edit information market involves a diverse range of stakeholder groups,extending beyond the corerelationship between financial institutions and customers to include credit reference agencies(CRAs),regulators,3 credit information service providers,consumer representatives and FinTech companies,4 amon

48、gothers.In the UK,the Financial Conduct Authority(FCA)plays a central role in the market.From 1 April2014,the FCA took over the regulation of the consumer credit industry from the Office of Fair Trading(OFT).The Information Commissioners Office(ICO),set up to uphold information rights in the publici

49、nterest,is another important authority in the realm of data privacy for individuals.5This study sets out to understand how the credit information market might develop in the future andexplore potential benefits and risks to consumers.The purpose of this report is to:xxxIdentify and analyse key facto

50、rs influencing change;Design a small number of coherent,plausible and internally consistent scenarios;andExplore key,policy-relevant implications of these scenarios.The study team carried out these objectives in a structured and expert-led way,using a future scenariosmethodology that incorporates bo