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1、Pushing Through UndercurrentsSectoral and Regional Forces Influencing Technology-driven Systemic Risk,and Resulting Mitigation OpportunitiesPart of the Future of Financial Services seriesPrepared in collaboration with Deloitte2ForewordINTRODUCTIONFor feedback or questions,please contact:Drew Propson

2、,Lead Authordrew.propsonweforum.org+1(917)224-6239The World Economic Forum applies a multistakeholder approach to address issues of global importance.Consistent with this mission,the creation of this report involved extensive outreach to,and dialogue with,numerous organizations and individuals.These

3、 included the Forums financial services,innovation and technology communities,and leaders from academia and the public sector.The outreach comprised over one hundred interviews and seven global workshops,conducted virtually and in person,over the past twelve months.The aim of these dialogues was to

4、capture insights around sectoral and regional forces that influence the spread of technology-driven systemic risk across the financial system and to identify targeted mitigation opportunities available for financial services players.The holistic and global content of this report would not be as comp

5、lete without contributions from the subject matter expertswho helped to shape our thoughts on the emergence of technology-driven systemic risks and possible risk mitigation approaches.We particularly thank this projects Steering Committee and Working Group.Their expertise and generosity with their t

6、ime have been invaluable.Also critical has been the ongoing institutional support for this initiative from the World Economic Forum and the leadership of our Chairman,whose vision for a more inclusive,resilient and sustainable world,particularly in these times of increasing complexity and fragmentat

7、ion,has been integral to this work.Finally,we are grateful to Deloitte for their commitment to,and support of,this project.3Editors noteINTRODUCTIONThe deepening adoption of technology within global financial services continues to come with considerable benefits while also introducing new risks that

8、 threaten the stability of the financial system if not properly managed.In an effort to better understand these risks and identify approaches to addressing them,the World Economic Forum launched the Technology,Innovation and Systemic Risk(TISR)initiative in 2021 to explore the role of technology in

9、both increasing and mitigating systemic risk in the financial system and,by extension,the economy.The publication of Beneath the Surface in 2021 raised new questions about the sectoral and regional conditions under which technology-driven risk can originate and spread across an ecosystem and which t

10、argeted mitigation opportunities will warrant further exploration.While mitigation approaches for systemic risk in financial services have been examined in other research studies,few have looked at how technology and sources of innovation can be used to identify and mitigate specific technology-driv

11、en systemic risks,with consideration for jurisdictional circumstances and geographical nuances.This comprehensive study brings together a global community of stakeholders across industries and disciplines to better understand these research topics and provide strategic insights to the public and pri

12、vate sectors.The outcomes of this research have reinforced the urgency for financial ecosystem players to sharpen their understanding of the origination points and spread of technology-driven risk from sectors and regions to implement effective mitigation solutions.It is hoped that this document wil

13、l help you push through the undercurrents influencing technology-driven systemic risk and inspire you to initiate new conversations around mitigation opportunities.Other recent reports from the Future of Financial Services series2019Drew PropsonHead,Technology and Innovation in Financial Services,Wo

14、rld Economic ForumRob GalaskiVice-Chairman and Managing Partner,Financial Services,Deloitte2019202020214Sami AhmedSenior Vice-President,Data and Advanced Analytics,OMERSKate PlatonovaGroup Chief Data Officer,HSBCShivaji DasguptaGlobal Head,Data Products and Artificial Intelligence,Deutsche BankStefa

15、n AltnerManaging Director,Head,Risk Governance and Assessment,Julius BaerDirk StephanekHead,GCOO Risk Management,UBSKfir GodrichManaging Director,Global Head,Technology and Enterprise Services,BlackRock Peter CaiManaging Director,Global Head,Risk Data,Analytics,Reporting and Tech(DART),CitigroupAman

16、 ThindGlobal Chief Architect,State StreetGero GunkelChief Operating Officer,ZCAM,Zurich InsuranceFergal CoburnChief Technology Officer,Allied Irish BanksSusanna WoodersChief Risk Officer,Fidelity InternationalBasak KoralturkHead,Corporate Strategy,JP Morgan ChaseRobert ContriGlobal Financial Service

17、s Industry Leader,Emeritus,Deloitte Thomas ZschachChief Innovation Officer,SWIFTLena Mass-CresnikChief Data Officer,Moelis&CompanyMembers of the Steering CommitteeINTRODUCTION5Steven AspreyManaging Director,Global Diversified Program,OMERSVincent LoyAssistant Managing Director,Technology,Monetary Au

18、thority of SingaporePhilip GarnerHead,Innovation,Lloyds Banking Group(through April 2022)Tobias AmietManaging Director,Global Head,Products and Services Compliance,Julius BaerChristian MittelbergGlobal Risk Officer,S&P GlobalEva GustavssonDirector,Government Relations EMEA,PayPalShane De ZilwaVice-P

19、resident,Analytics,VeriskHarqs SinghManaging Director and Chief Operating Officer,Technology Platforms,Data&AI,Information Security and Enterprise Services,BlackRockJames HarborneHead,Group Digital Public Policy,HSBCNicola Feakin Head,Technology Risk and Management,Oversight,Fidelity International T

20、obias WildHead,Architecture and Technical Delivery,ZCAM,Zurich InsuranceValrie HoessHead,Digital and AML Policy,Political Affairs,Deutsche Bank AGDoria FerranteSenior Vice-President,Product and Payment Services Risk,VisaMichael LeibrockChief Systemic Risk Officer and Head,Counterparty Credit Risk,DT

21、CCMembers of the Working GroupINTRODUCTIONProject leadershipThe Technology,Innovation and Systemic Risk project leadership team includes the following individuals:World Economic ForumDrew Propson,Lead Author,Head of Technology and Innovation in Financial ServicesMatthew Blake,Head of Shaping the Fut

22、ure of Financial and Monetary SystemsProfessional services leadership from Deloitte CanadaRob Galaski,CoAuthor,Project Adviser,Vice-Chairman and Managing Partner,Financial ServicesHwan Kim,Project Adviser,PartnerGayatri Suresh Kumar,Project Adviser,PartnerLuca De Blasis,Project Adviser,Chief of Staf

23、f6Members of the Project TeamINTRODUCTIONAdditional thanksThe project team expresses gratitude to the following individuals for their contributions and support:Project authorsThe World Economic Forum expresses its gratitude tothe following individuals on the project team:Deloitte CanadaAyesha Madan,

24、Senior Consultant(Secondee to the Forum)John Okoronkwo,Manager(Secondee to the Forum)Emina Ajvazoska Laurent ColletVincent GouverneurMarkus SalcheggerDimitri TsopanakosTony WoodLaurent BerlinerJay DeverettSuchitra NairIan SandlerDenizhan UykurSaemoon YoonJulie BernardValeria GalloMichael Nassar Mari

25、us von SpretiJohn WangJenny ZhangJonathan BurdettRichard GodfreyMike RitchieUsha SthankiyaMichelle Watt7WIP8Context and approach93Conclusion98Endnotes95Acknowledgements12Executive summary and key findings82Regional risks and mitigationSector-specific risks and mitigation21ContentsContext and approac

26、h9Recent explorations of technology-driven systemic risk in financial services have raised new questions about which hidden forces influence risk and what targeted mitigation opportunities are availableCONTEXT AND APPROACH The Forums most recent report of the Technology,Innovation and Systemic Risk(

27、TISR)Initiative,Beneath the Surface,was launched in 2021 to explore the relationship between adopting technologies in financial services and systemic risk.This current report,Phase II of the TISR initiative,explores the underlying sectoral and regional forces that influence technology-driven systemi

28、c risk and targeted mitigation opportunities.Phase I systemic risk themes:Core research objectives:Gaps in entity-based regulationDigital interdependenciesShared model vulnerabilitiesNew drivers of financial exclusionConflicting national prioritiesEmerging sources of influenceHow do technology-drive

29、n systemic risks originate and spread within sectors in the financial services ecosystem?What types of entities in financial services have the most influence in exacerbating or mitigating technology-driven systemic risks?What sectoral and regional opportunities exist to mitigate technology-driven sy

30、stemic risks?while raising new questions for Phase II about the sectoral and regional forces that influence technology-driven systemic risk and mitigationTISR Phase I identified six systemic risk themes that have emerged from the growing adoption of technology10Over the past year,over 100 financial

31、services and technology experts have been engaged in global workshops and expert interviews.*CONTEXT AND APPROACHGlobal workshopsSeven workshops were conducted during 2022,both virtually and in person.These sessions brought together leaders across the financial ecosystem:financial institutions(e.g.b

32、anks,asset managers,exchanges,infrastructure providers),financial and non-financial technology firms,regulators and policy-makers.Non-governmental organizations and academic institutions were also engaged in a series of interactive discussions with these entities.Three workshops explored the sectora

33、l and regional forces influencing the trajectory of technology-driven systemic risk.Four workshops tested and refined insights on targeted and technology-led mitigation opportunities available for sectors,entities and regions.Expert interviewsInterviews were conducted with over 100 public and privat

34、e sector leaders from prominent entities and experts adjacent to the industry.The inclusion of company case studies or references within this report does not reflect an explicit endorsement of the company or its products and services by the World Economic Forum.*Note:Please see Acknowledgements for

35、a list of individuals who participated in the workshops and interviewsThis report introduces leaders,regulators and policy-makers to the sectoral and regional forces that influence technology-driven systemic risks in financial services and how these risks can be mitigated This report WILL NOT:This r

36、eport WILL:This report seeks to help:Identify idiosyncratic risks that an individual financial ecosystem player faces from the adoption of emerging technology Investigate sectoral forces influencing systemic risks that are not driven or amplified by technology Provide detailed implementation approac

37、hes to execute mitigation opportunities.Explore how sectoral forces influence the way technology-driven systemic risk spreadsExplore how regional forces influence the spread of cross-sector risks Determine which entities are best positioned to lead mitigation opportunities to address technology-driv

38、en systemic riskPresent targeted opportunities to strengthen efforts to address technology-driven systemic risk.Leaders focused on strategy,innovation and/or risk at financial and non-financial organizations to gain clarity into:The sectoral and regional forces that drive their unique exposure to te

39、chnology-driven systemic risk Targeted mitigation opportunities for public and private sector players.Policy-makers and regulators better understand how to design targeted policies and mitigation strategies to support private entities across different sectors and regions.11CONTEXT AND APPROACHExecut

40、ive summary and key findings13The sectoral and regional forces that underlie technology-driven risk present both challenges and mitigation opportunities for financial services ecosystem playersEXECUTIVE SUMMARY AND KEY FINDINGS|SUMMARY there is fragmentation across product development and distributi

41、on areas in financial services.speed,accessibility and cost are unintentionally emphasized over long-term resilience and transparency highly dynamic geopolitical and regional forces outpace a financial institutions resilience measures for cybersecurity,workforce shortages and environmental threats.S

42、ectoral and regional forces reveal targeted opportunities for public and private players to enhance mitigation efforts bypromoting trust-enhancing products that help consumers make informed decisions and minimize the trade-off between bringing transparency and offering conveniencedismantling informa

43、tion siloes to identify clusters of technology-driven risk at the ecosystem level extending predictive analytics capabilities to better determine the effects of future geopolitical and regional uncertainty on a financial institutions resilience.213546Technology-driven risks can proliferate across se

44、ctors and regions to grow systemic when14Technology-driven risks can proliferate across sectors and regions to grow systemic when there is fragmentation across product development and distribution areas in financial servicesEXECUTIVE SUMMARY AND KEY FINDINGS Extension of financial infrastructureSour

45、cing of market intelligence Provisioning of creditThe fragmentation of financial infrastructure is advancing through“as-a-service”models that are being offered by regulated financial services entities.The risk of incomplete oversight will grow as the entities responsible for risk oversight(e.g.regul

46、ated financial institutions)decouple from those that manufacture and distribute financial products(e.g.non-financial players).Example:Regulated traditional financial institutions are extending their existing infrastructure to non-financial players through banking-as-a-service(BaaS)products and depen

47、ding on partnerships with platform and application programming interface(API)providers to participate in embedded financial offerings.Where is fragmentation coming from?How is this accelerating the spread of technology-driven risk?Large multinational technology platform providers are strengthening t

48、heir alliances with non-financial players to displace traditional financial credit offerings and harvest more first-party data.This pattern has increased blind spots to credit default risk and fragmented the development and distribution of credit products into multiple non-financial entities.Example

49、:Point-of-sale credit offerings from technology platforms(e.g.buy now pay later)are helping retail players grow faster,giving these technology platforms access to first-party consumer spending data,and forming credit ecosystems that operate without traditional financial players.The mainstream distri

50、bution of market intelligence has fragmented into partially regulated entities like data brokers and social news providers.This intelligence is feeding directly into artificial intelligence(AI)models that make real-time financial decisions and has the potential to amplify the impact of data deceptio

51、n tools(e.g.deepfakes)on financial markets and consumer trust.Example:Investment firms are relying on unregulated data brokers for access to non-financial data generated and sold by adjacent players(e.g.retailers)to expedite their access to rich sources of market intelligence.123456Three areas where

52、 fragmentation is most prominently occurring are the extension of financial infrastructure,provisioning of credit and sourcing of market intelligence15Some new entrants across sectors are unintentionally emphasizing near-term competitive advantages over long-term resilience and transparencyEXECUTIVE

53、 SUMMARY AND KEY FINDINGS 123456Transparency for consumers and long-term resilience for institutionsShort-term competitive advantages of speed,accessibility and low costWhat is fueling the trade-off across the ecosystem?The separation of risk management and product distribution functions Value propo

54、sitions from groups of new entrants are focused on enabling instant and affordable access to financial products for all consumers and less on the ability to manage and anticipate the associated long-term risks.This is leaving the ownership and management of risk downstream to traditional financial s

55、ervices players.Separating risk management and product distribution capabilities is beginning to reduce end-to-end visibility for consumer protection(e.g.protection against chronic overborrowing)and fuel future product liability challenges and potential consumer distrust in the industry(e.g.distrust

56、 from a lack of transparency in how personal data is managed).The rising cost of conducting due diligence and reinforcing trust with consumers The cost and complexity of conducting due diligence will continue to rise for financial institutions as the externalization of infrastructure and data servic

57、es will increase the number of third-party relationships to manage.Inefficiencies in centralized due diligence and transparency solutions(e.g.third-party audits and certifications that verify financial solvency and data protection measures for consumers)will continue to challenge financial services

58、players in bringing transparency to consumers while competing on speed,cost and convenience.Highly dynamic geopolitical and regional forces16Highly dynamic geopolitical and regional forces are outpacing a financial institutions resilience measures against cybersecurity,workforce shortages and enviro

59、nmental threatsEXECUTIVE SUMMARY AND KEY FINDINGS 123456Where regional vulnerabilities are growing2.Maintenance of critical operationsRegional competition for technology talent and growing competition from adjacent industries are leaving some regions vulnerable to shortages in the skills required to

60、 maintain critical operations(e.g.disaster recovery solutions).Localized dependencies to fulfil critical services(e.g.customer support)are also creating potential clusters of concentration risk should talent availability in these regions be disrupted.1.Risk assessments for vulnerable critical servic

61、e providers and institutional clients Cyberattacks are becoming increasingly geopolitically motivated,sophisticated and frequent against financial institutions and critical service providers.Given limitations in the speed and granularity of risk assessments currently conducted for a financial instit

62、utions client base and supplier network,the evolving nature of cyberattacks on these types of institutions may be putting financial institutions at risk.Cyberattacks on businesses providing critical services to a nation can be used as a gateway for damaging a nations economy(e.g.Hydro-Quebecs critic

63、al role in supplying energy to the US2),making these institutions more likely targets for cyberattacks.This can increase credit default risks for financial institutions that fund these institutions.3.Pricing of climate-related risk within financial services products Limitations in the availability o

64、f,and accessibility to,climate-related data,including data on the chronic effects of climate change(e.g.a long-term gradual change in agricultural productivity1),are affecting financial institutions ability to price in the financial risks of climate patterns,loan adjudication,insurance policies and

65、investment policies.Sophisticated and geopolitically-motivated cyberattacks Heightened competition for technology talent poolsChronic changes in climate patternsGovernment-sponsored enterprises,such as Fannie Mae and Freddie Mac,hold over$6 trillion in mortgage debt that does not price flood risk.4A

66、 2022 global report on talent trends revealed that 49%of C-suite and human capital leaders in the banking and financial services industry(BFSI)report talent scarcity for IT skills.3Example17Sectoral and regional nuances reveal targeted opportunities for traditional financial institutions and fintech

67、s to promote trust-enhancing products and services that help reinforce financial system stabilityEXECUTIVE SUMMARY AND KEY FINDINGS As consumer data becomes democratized through open banking platforms,connecting consumer financial activity across different products can enable automated money managem

68、ent intelligence services that financial services players can offer to guide long-term customer choice and balance decisions that protect long-term financial health.Example:Finicity and Plaid are aggregating consumer and small business account data and applying advanced analytics to offer personaliz

69、ed financial advice5Liability insurance products can protect consumers from data breaches or unauthorized activities that cannot be attributed to a single third-party provider or financial institution(e.g.a consumers bank account data is compromised in a merchants website,which is built on a platfor

70、m by a third-party provider).Alongside existing financial and media literacy efforts,financial institutions and fintechs can embed authentication and digital credential services for financial services-related content to help protect consumers from the effects of disinformation and data deception too

71、ls.Where can traditional financial institutions and fintechs offer trust-enhancing products and services?The fragmentation of financial services capabilities has led to gaps in holistic consumer protection practices,as fewer private entities offer end-to-end visibility on consumers financial health

72、or are obligated to make a customer whole.There is a growing market gap for offering consumers personal financial management across their financial dealings while maintaining a highly convenient and affordable shopping experience.Traditional financial institutions are uniquely positioned to“connect

73、the dots”and extend their role as trusted partners for consumers who have multiple financial dealings with niche and adjacent players.In partnership with fintechs,traditional financial institutions can also use insights into their customers financial activity across niche offerings to further deepen

74、 customer relationships and reinforce value propositions that are centred on trust and transparency.123456There is an emerging opportunity for incumbents and fintechs to offer trust-enhancing value propositions in a fragmented product landscapeHow can financial services entities address this opportu

75、nity?18Public and private sector players can collectively dismantle information siloes to help better identify technology-driven risk at the ecosystem levelEXECUTIVE SUMMARY AND KEY FINDINGS Third-party providers(e.g.fintechs,e-commerce players)Data aggregators Regulators for financial institutions,

76、Big Tech,and adjacent playersEnd consumersSubset of existing playersSubset of existing data flowsFuture potential playersFuture potential data flowsL E G E N DOpen finance platformFinancial institutions(across sectors)As an entitys network size grows more relevant in determining systemic importance(

77、as identified in the Phase I report),regulators and institutions can use existing open data platforms to access and aggregate real-time and verifiable insights on technology-driven riskMapping the degree of common service provider relationships across cloud infrastructure,alternative data providers

78、and API stack providers will help regulators identify common dependencies across financial institutions(regionally or by sector).Generating and aggregating these datasets can make way for intelligent monitoring solutions that predict disruptions to a third-party vendors financial health and security

79、 posture and enable proactive action by financial institutions and regulators.Regulators can aggregate existing open banking platforms and transactional data to monitor the trajectory of regional credit risk trends.Standardized data aggregation from open finance ecosystems can help regulators across

80、 jurisdictions compare regional risk trends and design data-driven approaches to regulation(e.g.by analysing the implications of active regulation on a customers financial activity).How can information siloes be dismantled and distributed?How can technology-driven risk be identified at the ecosystem

81、 level?Sector B financial playersSector A financial playersSystemically important third-party service providers for one sectorL E G E N DSystemically important third-party service providers cross-sector12345619Financial services players predictive analytics capabilities should reflect future geopoli

82、tical and regional uncertainty and be applied towards resilience effortsEXECUTIVE SUMMARY AND KEY FINDINGS 123456Consider new dimensions with which to predict and monitor a financial services players operational resiliencyEmbed real-time and forward-looking geopolitical data-gathering mechanismsTest

83、 for sectoral resilience through cross-jurisdictional exercises that use simulation techniques Scenario implications and resilience strategies must include geopolitically-motivated triggers and conditions that can compromise critical third-party service providers or critical institutions to whom fin

84、ancial institutions have sold products and services.Exposure to regional risk vectors(across regulatory,cyberattack targeting and environmental factors)should be embedded as an input variable when updating risk profiles and pricing financial products for a financial institutions client base.Financia

85、l institutions can engage automated operational resilience platforms using global market intelligence data to aggregate operational resilience risk scores and evaluate a firms risk exposure before engaging them as a third-party provider.6 Financial services players should use synthetic datasets to e

86、nrich intelligence data from regions where diagnostic data is difficult to procure.These datasets will ensure better representation of regional forces when simulating future geopolitically-triggered events and response plans.International resilience exercises should focus on simulations that disrupt

87、 a sectors shared global infrastructure(e.g.a global payments network)and test response patterns and regional exposures for geopolitically-motivated cyberattacks.International resilience exercises and outcomes should also be analysed at a regional level to determine what future public funding backst

88、ops and buffers are required to contain the systemic effects of attacks.In what ways can private and public financial ecosystem players use predictive analytics capabilities to better meet the evolving speed of geopolitical and regional forces?20This report is comprised of three core sections that e

89、xplore the origination of technology-driven systemic risk across sectors and regions,and the targeted mitigation opportunities availableEXECUTIVE SUMMARY AND KEY FINDINGSKey findingsRegional influences and mitigation opportunitiesDescriptionReview key takeaways for public and private sector players

90、within the financial services ecosystemExplore the systemic nature and underlying forces behind technology-driven risks originating in financial services sectors(“sector-specific risks”)Examine existing efforts and emerging opportunities available to identify and address sector-specific risksExplore

91、 the regional forces that influence the proliferation of technology-driven systemic risks across financial services sectors,and the targeted mitigation opportunities available for consideration Sectoral exposures to systemic risk and targeted mitigation opportunities123Sector-specific risks and miti

92、gation22A collection of sector-specific risks have been identified as originating within a sector and having the potential to become systemicSECTOR-SPECIFIC RISKSCapital markets*Investment managementPaymentsBankingInsuranceMarket manipulation from the distribution of synthetic mediaMarket volatility

93、 from speculation fuelled by social mediaVulnerabilities in parametric insurance smart contractsRisk exposure from banking-as-a-service(BaaS)offeringsAccumulation and securitization of buy now pay later(BNPL)debt Potential for contagion to spread into traditional markets if crypto-asset ecosystems c

94、ollapseInvestor manipulation from compromised sensor-generated dataGrowing protection gap for catastrophic cyberattacksInadequate stability mechanisms for stablecoin arrangementsSecurity vulnerabilities of decentralized central bank digital currency(CBDC)architecture Prioritized sector-specific risk

95、s:Two sector-specific risks have been identified for each sector(non-exhaustive)and will be explored in the following section of the report.Sector-specific criteria:In order to be classified as a sector-specific risk,the risk must meet all three criteria below.1.Originates in one sector2.Highly dyna

96、mic risk vectors3.Potential to become systemicThe technology-driven risk originates uniquely within a sectorThe underlying risk vectors are highly dynamic and increase the probability of the risk materializingThe risk has a high potential to grow and become systemic should it materialize*In this rep

97、ort,capital markets includes market infrastructure sector players23The following section shares findings on the top sector-specific risks alongside targeted mitigation opportunitiesSECTOR-SPECIFIC RISKSFindings on targeted mitigation opportunitiesSector-specific risk analysis1.Overview of sector-spe

98、cific risk Background and context on the sector-specific risk Findings on the highly dynamic risk vectors that exacerbate the sector-specific risk2.Plausible systemic scenario and amplifying forces A potential systemic scenario that illustrates the second-order impacts on other ecosystem players if

99、the sector-specific risk materializes Exploration of the entity and regionalforces that increase the probability and impact of the sector-specific risk materializing2.Deep-dive into current mitigation efforts A summary of collaborative mitigation efforts largely government-or sector-initiated that a

100、re currently gaining traction across the ecosystem(including relevant examples)Analysis of the areas of opportunity available to strengthen existing efforts3.Deep-dive into emerging mitigation opportunities An exploration of each emerging mitigation opportunity,how the solution can be executed to ad

101、dress the effects of the sector-specific risk,and the conditions necessary for success1.Desired mitigation outcomes and opportunity landscape A summary of mitigation outcomes required to address the sector-specific risk A summary of current mitigation efforts and emerging opportunities for considera

102、tion to enable desired outcomesEach sector-specific risk exploration will include the following:Capital markets2425Market manipulation from the distribution of synthetic mediaOVERVIEW OF SECTOR-SPECIFIC RISK|DISTRIBUTION OF SYNTHETIC MEDIANovel deception tools like deepfake voice phishing and synthe

103、tic social botnets that are underpinned by AI are becoming increasingly popular methods to spread disinformation that can maliciously influence financial markets.BackgroundThe rapid growth of the synthetic media market and research advances in deep-learning algorithms have quickly lowered the financ

104、ial and technological barriers for malicious actors to manipulate financial markets,specifically through the proliferation of deepfake videos and synthetic botnets.Generative AI modelling companies are seeing a rapid increase in deepfake applications,with content on the internet growing at the rate

105、of 400%year on year.7While the adoption of synthetic media by legitimate actors grows in parallel(e.g.using synthetic datasets to enrich investment simulations),the implications of non-malicious inaccuracies within synthetic datasets may not yet be systemic.Deepfake technologies are also beginning t

106、o take up a larger share of cyberthreats.Two out of three respondents in the 2022 Global Incident Response Threat report indicate that malicious deepfakes are increasingly being used for attacks.This trend reflects a 13%increase from 2021.8Ease of access to deepfake tools,open-source libraries and g

107、enerative AI applications(e.g.ChatGPT)are lowering the cost of producing synthetic mediaThe growing volume of images and videos of systemically important individuals(e.g.central bank governors,bank CEOs)increases the precision and effectiveness of malicious synthetic mediaSystemically important inst

108、itutions that use social media channels to communicate with the public can increase the degree of trust placed in these platformsRisk vectors Emerging risks Connected devices controlled by malware(“synthetic botnets”)are increasingly being used to produce synthetic social media content positioned to

109、 induce withdrawals from fake“run on the bank”scenarios(impersonations of bank customers claiming to be unable to withdraw their deposits)and flash crash events(hacking and posting messages about fictional market-moving events on behalf of trusted accounts,like the Twitter account of a central bank

110、chief).9 With the increased availability of large image and video databases accelerating the accuracy of AI models used to generate deepfake videos and images and the growing maturity of deepfake algorithms,it is becoming increasingly difficult for fraud-detection software to identify deepfakes that

111、 target multiple attack surfaces(voice and video),meaning the risks from synthetic media are primed to grow with potentially systemic implications.Communities with high dependency on alternative media for information accessCommunities with unaffordable or unstable internet connectivity are primed to

112、 consume most of their information from social media providers that have partnered with local network carriers(e.g.Metas FreeBasics Program in Philippines).1026Systemic risk scenario and amplifying forcesPOTENTIAL SYSTEMIC SCENARIO AND AMPLIFYING FORCES|DISTRIBUTION OF SYNTHETIC MEDIAForces that can

113、 amplify and accelerate the riskIf disinformation about interest rates proliferates across credible social media platforms and accounts through the use of synthetic media(e.g.the social media account of a trusted public official is compromised,and a face-swap video about a dramatic drop in interest

114、rates is posted nationwide),shifts in public sentiment about financial markets can lead to the following second-order impact:Consumer mistrust and scepticism in government institutionsIndividuals may not trust future communications made by public officials on social media platforms.As a result,long-

115、term reputational damage to government institutions and lingering scepticism around current monetary policies may contribute to prolonged market volatility.Impact on investor portfolios through bond price volatilityIn response to dramatically lower interest rates,retail and institutional investors m

116、ay begin selling their positions on bonds or money market accounts,resulting in sharp movements across financial markets.Potential systemic risk scenario(if the sector-specific risk is not mitigated)Technology companies lowering the financial barriers to generate synthetic mediaThe cost of generatin

117、g synthetic media is dropping as companies are improving video-generation methods(e.g.Microsoft,GPT-3 language models)that enable users to use off-the-shelf or open-source machine learning software to quickly generate fake content.High-frequency trading algorithms connected to real-time high-speed d

118、ata feedsHigh-frequency algorithmic trading programs that read real-time high-speed data feeds may not distinguish real news from disinformation and can amplify the systemic effects of synthetic media that are deployed on credible channels.Regional forceEntity force27Target mitigation outcomes and o

119、pportunity landscapeDESIRED MITIGATION OUTCOMES AND OPPORTUNITY LANDSCAPE|DISTRIBUTION OF SYNTHETIC MEDIAMitigation opportunities to address the risks from distributing synthetic media about financial markets must centre on more robust media moderation,equipping users to recognize disinformation and

120、 strengthening authentication efforts for both content and users.Stronger user authentication on alternative media platformsStronger content authentication and media literacy Stronger synthetic media moderation Limit the monetization opportunities available for synthetic media shared on social media

121、.Crowdsource social media fact-checking capabilities by encouraging digital citizenship and collective trust.Embed digital content credentials within the social media upload process to maximize transparency.Decentralize transparency efforts through plug-in tools powered by artificial intelligence.Ex

122、tend biometric authentication requirements for systemically influential individuals social media accounts.Target mitigation outcomesMitigation opportunity landscapeCurrent mitigation efforts growing in adoptionEmerging mitigation opportunities for considerationThe following slides will summarize cur

123、rent mitigation efforts that are growing in adoption and provide thorough analysis of emerging mitigation opportunities for consideration 28Current mitigation efforts growing in adoptionDEEP-DIVE OF CURRENT MITIGATION EFFORTS|DISTRIBUTION OF SYNTHETIC MEDIA Current efforts to identify disinformation

124、 and boost media literacy among communities are gaining traction,while unrealized opportunities remain to better protect influential social media accounts from being compromised and sharing disinformation.As a part of the European Commissions media literacy initiatives,platforms should be encouraged

125、 to publicly classify the content subject to limitations in advertising revenue due to the Code of Practice on Disinformation.Partnerships with mainstream social media platforms,advertising agencies and regulators will be crucial for digital content credentials requirements to become an industry sta

126、ndard;partnerships should also be used to increase education for consumers and producers of content.A crowd-sourced fact-checking tool on social media would need to reach mass consumption levels to gain credibility and would need to be continually monitored for diversity in the user base to gain cre

127、dibility and minimize bias.AI-powered fact-checking capabilities for users should include abilities to fact-check video content and identify fabricated user engagement coming from synthetic botnets.Considerations to strengthen existing mitigation effortsEmbed digital content credentials within the s

128、ocial media upload process to maximize transparencyContent creator platforms are championing initiatives that increase users visibility into digital credentials(including edit history)for content shared online,thereby helping users distinguish reality from fabrication(e.g.Adobes Content Authenticity

129、 Initiative).12Decentralize transparency efforts through plug-in tools powered by artificial intelligenceFintechs like Factinsect offer plug-in fact-checking software for users to compare alternative media content against selected quality media by visually spotlighting contradictory or disproved tex

130、t within seconds.13Limit the monetization opportunities available for synthetic media shared on social mediaThe European Commissions Code of Practice on Disinformation was updated in 2022 to ensure that disinformation distributors do not benefit from advertising revenues and that signatories commit

131、to stronger measures to avoid the placement of advertising next to disinformation shared on media platforms.11Crowdsource social media fact-checking capabilities by encouraging digital citizenship and collective trustLarge social media platforms are beginning to employ users to police disinformation

132、 and publish recommendations within posts to scale their fact-checking capability,maximize transparency for users,maintain neutrality and help reinforce media literacy(e.g.Birdwatch/Community Notes,Twitters fact-checking tool).Sector-initiatedGovernment-initiatedBiometric authentication requirements

133、(e.g.face authentication with liveness assurance checks)should be extended for social media accounts that belong to systemically influential entities(e.g.bank CEOs,governors of central banks,high-profile investors)and influential individuals with high followership volumes to curb the negative second

134、-order effects that can reach financial markets.Relevant case studiesHow it could work Conditions necessary for successOpportunity overviewGovernments set shared standards on what constitutes a systemically important social media account(e.g.followership volume,government officials,relevance to mark

135、et movements).Social media platforms pull facial recognition,fingerprint or voice data for systemically influential entities and their designated social media managers as part of their onboarding process and security settings for verified accounts that meet government standards.They can also verify

136、if the post is outside of the normal pattern and tone of past posts by the systemically influential individual.Systemically influential entities or their associated social media managers perform additional biometric checks before every content upload.Capital market providers share market datasets an

137、d correlation metrics to support the development of standards.Baaz,a social media platform in the Middle East,has partnered with IDMission to enable an end-to-end encrypted identity process that authenticates its users identities through passive liveness,biometrics and industry-compliant security pr

138、actices.14Data privacy mandates in place for biometric authentication data received by social mediaInput from capital market makers,social media platforms and fourth-party software-as-service providers on government standards that define systemically influential entitiesSocial media content posts sh

139、ould be verified and confirmed as not being produced by generative AI applications29Extend biometric authentication requirements for systemically influential individuals social mediaDEEP-DIVE OF EMERGING MITIGATION OPPORTUNITIES|DISTRIBUTION OF SYNTHETIC MEDIA nePotential for contagion to spread int

140、o traditional markets if crypto-asset ecosystems collapseOVERVIEW OF SECTOR-SPECIFIC RISK|CONTAGION FROM CRYPTOCURRENCY EXCHANGESShould levels of retail and institutional investment in crypto rebound and outpace the effects of regulatory action,current lending and custody processes used in crypto-as

141、set ecosystems may spread contagion into traditional markets should cryptocurrency exchanges fail.BackgroundInstitutional cryptocurrency investments dropped by 95%in 2022 in response to the latest string of cryptocurrency exchange bankruptcies.15While the crypto market has remained largely isolated

142、from traditional markets due to relatively low institutional exposure,the structural barriers that protect traditional markets from crypto contagion remain permeable.Amid growing anticipation for regulatory action,institutional investor interest is beginning to resurface.16As established regulatory

143、regimes formalize protection measures for crypto assets,retail and institutional investors may regain new levels of confidence and acceptance in cryptocurrencies as a long-term store of value.17In response to growing demand,investment firms can reaccelerate the channels available for investors to ga

144、in direct exposure to crypto-assets(e.g.through partnerships with cryptocurrency exchange platforms,bitcoin-backed loan offerings or cryptocurrency options for pension funds).If the speed of renewed institutional and retail demand for crypto exposure outpaces the effects of enforcement and monitorin

145、g action from crypto regulators,traditional financial institutions may become vulnerable to the risk vectors from cryptocurrency exchanges lenient lending models and complex investment products available to unsophisticated clients.Democratized access to highly-leveraged trades can threaten the liqui

146、dity of exchange operationsLimited transparency on leveraged trading volume and capital reserve data can make investor deposits vulnerable to lossPseudonymous design of the underlying blockchain technology can make credit-worthiness assessments challengingEmerging risks Unchecked use of consumer fun

147、ds:Unlike conventional stock exchanges that generate revenue exclusively from trading fees,many cryptocurrency exchanges also preserve client funds,provide counterparty services,and lend and borrow money outside regulatory oversight.Their multi-faceted role can create conflicts of interest when prov

148、iding their investors with the best execution obligation(e.g.exchanges may face off one of its investors for a trade)and when borrowing funds(e.g.exchanges using their tokens as collateral for loans and incentivizing their customers to purchase their tokens to increase its value).18 Unrestricted acc

149、ess to leverage:Many crypto-asset exchanges have allowed unsophisticated retail investors unrestricted access to significant amounts of leverage(up to 125 times)to purchase crypto-assets,often without sufficient disclosure and understanding of the associated financial risks.19Permitting overleverage

150、d trades with limited restrictions heightens the insolvency risk for a cryptocurrency exchange.Custody,lending and borrowing offerings can create conflicting incentives for an exchange when facilitating tradesRisk vectors 30High fragmentation and inconsistency in crypto-asset regulation Regions with

151、 inconsistent regulations placed on cryptocurrency exchanges increase the risk of redirecting high-risk,low-transparency trades into fewer communities and increasing the concentration of trading risk into fewer economies.31Systemic risk scenario and amplifying forcesPOTENTIAL SYSTEMIC SCENARIO AND A

152、MPLIFYING FORCES|CONTAGION FROM CRYPTOCURRENCY EXCHANGESA large cryptocurrency exchange has a growing user base of traditional investors who make multiple levered bets on crypto assets.The exchange is not yet required to disclose daily capital reserve data or customer protection practices.During a p

153、eriod of intense leveraged trading activity,the cryptocurrency exchange cannot meet customer withdrawal requests and puts a freeze on future requests.In response,other investors begin withdrawing funds from other cryptocurrency exchanges in a panic,contributing to a sharp drop in cryptocurrency valu

154、es.Growing adoption of decentralized cryptocurrency exchangesDecentralized exchanges,which coordinate crypto-asset trading by using automated algorithms and operate outside regulatory perimeters,are beginning to gain market share over centralized exchanges that have recently enforced new crypto regu

155、lations and reporting requirements.20Interconnectedness of decentralized finance applicationsBecause lending collateral can be recycled and reused between different DeFi protocols,insolvencies in one token can lead to rapid second-order impacts on other liquid staking protocols(e.g.terraUSD with Lid

156、o,and MIM stablecoin).21Regional ForceEntity ForceGrowing credit risk for banksInvestors that lose a significant volume of cryptocurrency value from an insolvent exchange(e.g.life savings,frozen pension funds)may face insolvency,which can threaten their ability to repay bank loans.Balance sheet writ

157、e-offs for large asset managersAsset managers that have developed cryptocurrency products(e.g.private trusts,crypto-backed loans)and have balance sheet exposure may need to write off values in their balance sheet,which can affect their solvency ratios.Swings in institutional investor portfoliosInsti

158、tutional investors will unwind funds invested in traditional markets to repay debt and cover their cryptocurrency losses,resulting in sharp swings in traditional markets.Forces that can amplify and accelerate the riskPotential systemic risk scenario(if the sector-specific risk is not mitigated)32Tar

159、get mitigation outcomes and opportunity landscapeDESIRED MITIGATION OUTCOMES AND OPPORTUNITY LANDSCAPE|CONTAGION FROM CRYPTOCURRENCY EXCHANGESMitigation efforts to minimize the contagion from cryptocurrency exchange activities must increase the transparency of exchange solvency for investors and con

160、trol access to leveraged trading for creditworthy exchanges and investors.Transparency on indicators of exchange solvencyControlled access to leveraged trading for investorsProtection of investor deposits Impose usage restrictions on customer deposits held in exchange custody Establish shared reserv

161、e pools across the industry to address isolated liquidity challenges Design on-chain credit scores based on publicly available blockchain transaction data Enhance know your customer(KYC)measures for exchanges that verify proof of funds via Open API platforms Mandate Proof of Reserve certificates fro

162、m third-party auditors Mandate real-time Proof of Solvency disclosures using zero-knowledge-proof protocolsTarget mitigation outcomesMitigation opportunity landscapeCurrent mitigation efforts growing in adoptionEmerging mitigation opportunities for considerationThe following slides will summarize cu

163、rrent mitigation efforts that are growing in adoption and provide thorough analysis of emerging mitigation opportunities for consideration 33Current mitigation efforts growing in adoptionDEEP-DIVE OF CURRENT MITIGATION EFFORTS|CONTAGION FROM CRYPTOCURRENCY EXCHANGES With the significant collapse in

164、multiple leading cryptocurrency exchange platforms,the focus of mitigation efforts has been onprotecting investor deposits and identifying creditworthiness,while some opportunities to maximize exchange transparency remainuntapped.Since many investors trade on unregistered platforms operating in juri

165、sdictions with little to no regulation,more funding should be dedicated to educating investors and discouraging advertising on unregistered platforms.On-chain credit scoring protocols should also connect to off-chain credit history(via oracles like Chainlink)to recognize creditworthiness and offer h

166、igher yields for new crypto-asset investors with no on-chain credit score.Regulatory bodies should contribute towards defining the criteria with which cryptocurrency exchanges are deemed eligible for recovery funds during market crises.Proof of Reserve certificates should extend to showcase an excha

167、nges liabilities in real-time to identify solvency issues more efficiently.Considerations to strengthen existing mitigation effortsSector-initiatedGovernment-initiatedImpose usage restrictions on customer deposits held in exchange custodySecurities regulators in regions like Canada and New York have

168、 prohibited registered cryptocurrency trading platforms from using customer deposits to fund risky proprietary trading strategies or offering high-leverage derivatives in order to disincentivize risky decision-making.22Establish shared reserve pools to address isolated liquidity challenges for good

169、actorsIndustry leaders like Binance are driving efforts to design an industry recovery fund to help financially healthy exchanges that face a liquidity squeeze during market distress and investor confidence crises.23Design on-chain credit scores based on publicly available blockchain transaction dat

170、aDeFi applications like Spectral,Polygon and Amplify use publicly available blockchain transaction data by connecting crypto wallets24and zero-knowledge identity methods to assess creditworthiness while maintaining user privacy.25Mandate Proof of Reserve certificates from third-party auditorsAfter t

171、he meltdown of the cryptocurrency exchange FTX in November 2022,many exchanges are now beginning to implement Proof of Reserve certificates that can be securely verified using cryptographic methods and attested to by third-party auditors.26DEEP-DIVE OF EMERGING MITIGATION OPPORTUNITIES|CONTAGION FRO

172、M CRYPTOCURRENCY EXCHANGESRelevant case studiesMandate real-time Proof of Solvency disclosures using zero-knowledge-proof protocolsCryptocurrency exchanges can adjust collateral requirements for lending products to sustain and stabilize solvency.Proof of LiabilitiesAn investor can privately verify t

173、hrough a zero-knowledge-proof that the exchanges commitment to their balance exists and is the right amount.Proof of AssetsThe exchange publishes its capital reserves daily on-chain to prove ownership of sufficient capital to cover all their customers balances.Proof of Solvency can be designed throu

174、gh the execution of DeFi protocols using zero-knowledge proofs,which verifies an exchanges liabilities while protecting customers balance data and privacy.27Proof of SolvencyThe exchange reconciles the difference between total assets and liabilities and confirms solvency if the difference is greater

175、 or equal to zero.THORChain is a decentralized liquidity network that prioritizes the security of locked assets,and those exchanged on the network.It uses security-enhancing mechanisms like bug bounty rewards and proactive on-chain solvency verification to build trust with users and community member

176、s in the network.28CACHE Gold,a DeFi protocol that supports tokenized gold assets,has integrated with Chainlinks Proof of Reserve protocol to enable continuous verification and transparency of the true status of the gold reserves that back their tokens.29Guidance from governments or self-governing b

177、odies on the minimum cadence and degree of solvency required to be disclosed by an exchangeStandardized interoperability design for infrastructure providers and API platforms that integrate cryptocurrency wallets to exchange data(e.g.Zabo,Plaid)Crypto wallet providers and API platforms can integrate

178、 real-time solvency disclosures into their user interface,enabling easy access for investors.Conditions necessary for success34Opportunity overviewThe accuracy and transparency of cryptocurrency exchanges solvency can be maximized through an on-chain,real-time reporting mechanism.This solution can h

179、elp ensure real-time solvency data is considered in downstream lending products offered by an exchange and can be made accessible to retail and institutional investors.Real-time Poof of Solvency disclosures are less costly than certificates that require third-party audits and can better sustain cont

180、inuous investor trust in exchange operations.How it could workDEEP-DIVE OF EMERGING MITIGATION OPPORTUNITIES|CONTAGION FROM CRYPTOCURRENCY EXCHANGESInvestors should be given the opportunity to share their proof of capital and reserves(including fiat currencies)as part of anenhanced KYC process to ga

181、in access to leveraged trades for lower interest in a cryptocurrency exchange.Access to a combination of on-chain credit scores with credit report data outside of cryptocurrency investments can help exchanges better price their interest rates according to risk and offer different tranches of interes

182、t based on their investors creditworthiness.30Enhance KYC measures for exchanges that verify Proof of Funds via open API platformsToday,KYC measures embedded in cryptocurrency exchanges are aimed at preventing illegal activities such as money laundering,terrorist financing and tax evasion.31Opportun

183、ity overviewHow it could workInvestors are given the option to share their proof of solvency and crypto credit scores with exchanges ahead of being eligible for specific types of leveraged trades.Cryptocurrency exchanges conduct enhanced KYC checks that include an exhaustive review of liquidity outs

184、ide cryptocurrency trades.Interoperability between open API layers and multiple cryptocurrency exchanges to maximize consistencyMandates from government authorities on capital thresholds required for leveraged cryptocurrency tradesPlaid offers cryptocurrency exchange support by aggregating a custome

185、rs cryptocurrency accounts through an API,giving investors a comprehensive view of their finances.It helps them share crypto account information,asset types,balances and transactions for other services.32A centralized data transfer network aggregates:via an open API that connects data from investors

186、 different digital wallets and account balances.Eligible investors are offered different“tranches”of interest depending on the output of their data-driven KYC check.On-chain credit scores for crypto investmentsTraditional credit bureau report dataFrom a blockchain oracle+35Conditions necessary for s

187、uccessRelevant case studiesInvestment management3637Market volatility from speculation fueled by social mediaOVERVIEW OF SECTOR-SPECIFIC RISK|MARKET VOLATILITY FUELED BY SOCIAL MEDIAWith retail investor activity reaching record highs and speculation on social media platforms continuing to proliferat

188、e,the market volatility introduced by strategies like meme-stock investing could grow to have systemic implications.The democratization of trading complex investment products through online trading platforms can multiply the effects of speculative trading by unsophisticated investorsSocial media pla

189、tforms being recognized as a trusted source of market data by retail investors can create echo chambers that reinforce speculation and bias Minimally available leading indicators of meme-stock episodes make it difficult for investment firms to update their risk models and for retail investors to mak

190、e informed investment decisionsBackgroundWith retail investor activity and meme-stock speculation having reached unprecedented levels in 2022,the influence of both trends on financial markets continues to widen.33While the rise of commission-free trading platforms has lowered the barriers for indivi

191、duals to participate in direct investing,this rise has also resulted in the growth of“meme stocks”,where asset prices are highly disconnected from the underlying value of a company and are often driven by speculation on social media.34This dislocation has raised concerns among regulators,leading the

192、m to actively investigate the impact of digital engagement practices on market structure conditions.35While social media-driven market effects are not limited to meme-stock activity,their influence is well observed in this space.For example,algorithmically-driven social media platforms(Reddit,Twitte

193、r)are pivotal in amplifying stock volatility and heightening individual risk appetites by creating“echo chambers”for investors to frequently communicate with others with similar interests and views,potentially reinforcing speculative investment decisions.36Emerging risks Meme-stock strategies are no

194、w being extended to short-term options positions where investors place bets on prices with unlimited downside risk.37In the third quarter of 2022,S&P 500 options expiring within one day accounted for more than 40%of the total trading volume.Meme-stock episodes may also threaten sectors that depend o

195、n consumer trust(e.g.banking)if their upward trajectory continues.In October 2022,a social media post shared with more than 300,000 followers and reshared more than 3,000 times questioned the solvency of Credit Suisse and led to widespread rumours about its bankruptcy across markets.The firestorm re

196、sulted in retail investors participating in short trades with no-cap downside,with the banks shares plunging nearly 6%,shaving about$600 million off its market capitalization.38 The increase in many retail investors risk appetites may not be sufficiently calibrated within investment firms risk model

197、s to reflect the volatility and market loss that meme-stock episodes may trigger.39 If memestock activity continues along this trajectory,well-capitalized institutional investors with well-researched positions may be forced to unwind and liquidate their positions earlier,creating a significant multi

198、plier on the overall market disorder.Risk vectors 38Systemic risk scenario and amplifying forcesPOTENTIAL SYSTEMIC SCENARIO AND AMPLIFYING FORCES|MARKET VOLATILITY FUELED BY SOCIAL MEDIAOnline trading platforms gamifying trading and encouraging risky trading behaviour Online trading platform feature

199、s are designed to maximize user enjoyment,which may be directly correlated with risky trading behaviour.40Platforms also redirect investors to high-attention stocks with little access to formal financial advice available for unsophisticated investors.41False rumours about undervalued stocks are shar

200、ed on social media and spark multiple activist online campaigns on alternative media,leading to herd buying behaviour across retail investors.The resulting meme-stock herd buying behaviour may trigger the following second-order impact:Social media penetration rates across communitiesRegions with you

201、nger populations and unrestricted access to social media channels(e.g.Brazil,South Africa,Philippines42)may be at the most risk of participating in meme-stock trades due to social media-driven speculation.Investors“reverse engineering”meme-stock campaignsInvestors with controlling interest in public

202、 companies may be incentivized to spark activist campaigns on social media platforms to boost a companys stock price as a path to satisfying shareholders instead of increasing the financial viability of a company.43Regional ForceEntity ForceLiquidation of institutional investor portfoliosLarge inves

203、tment firms that underwrite the put/call options that retail investors buy begin liquidating their holdings and cutting short their losses in response to volatile and sudden changes in portfolio value(from long or short positions),creating a second-order effect on market destabilization.Retail inves

204、tor solvency leads to credit risk for banksRetail investors that have purchased short-term options and invested on margin against meme-stocks may face a liquidity crunch as markets restabilize,threatening their ability to pay back their liabilities with other lenders in the financial ecosystem.Force

205、s that can amplify and accelerate the sector-specific riskPotential systemic risk scenario(if the sector-specific risk is not mitigated)39Target mitigation outcomes and opportunity landscapeDESIRED MITIGATION OUTCOMES AND OPPORTUNITY LANDSCAPE|MARKET VOLATILITY FUELED BY SOCIAL MEDIAMitigation effor

206、ts to protect against the market instabilities introduced by intense speculation should focus on deterrence fromparticipating in speculative trades and the ability for institutional investors to detect meme-stocks proactivelyGreater transparency for institutional investors on leading meme-stock indi

207、catorsDeterrence from participating in speculative trades Embed financial literacy programmes within online trading platforms.Increase retail shareholder engagement through social media.Launch an automated adviser model in online trading platforms for proactive investment recommendations.Set up exch

208、ange-traded funds(ETFs)and indexes that help investors track emerging meme stocks.Use machine learning algorithms to spot warning signs of a meme-stock surge.Embed real-time alternative data feeds into institutional investors risk models.Target mitigation outcomesMitigation opportunity landscapeCurr

209、ent mitigation efforts growing in adoptionEmerging mitigation opportunities for considerationThe following slides will summarize current mitigation efforts that are growing in adoption and provide thorough analysis of emerging mitigation opportunities for consideration DEEP-DIVE OF CURRENT MITIGATIO

210、N EFFORTS|MARKET VOLATILITY FUELED BY SOCIAL MEDIA40Current mitigation efforts growing in adoptionWhile efforts to identify retail activity through social media tracking,and educate retail investors on stock fundamentals,are growing,new opportunities exist for institutions to proactively support hea

211、lthy risk-taking behaviours and develop forward-looking indicators to embed in investment risk models.Online trading platforms can consider embedding financial literacy assessments for retail investors as part of onboarding for online trading platforms to tailor their recommendations for investment

212、products.Rebalancing ETFs more frequently(e.g.hourly instead of biweekly)and reducing their market capitalization requirements can increase the likelihood for investors to track the early indicators of meme-stock behaviour.49Attendance and shareholder engagement data from company sessions on social

213、media can serve as valuable input for algorithms to detect early retail investor interest and identify leading meme-stock indicators sooner.Data inputs for model algorithms can be in real-time,sourced from third-party data providers to help proactively identify and monitor heightened risk exposure f

214、or institutional investors existing holdings.Considerations to strengthen existing mitigation effortsEmbed financial literacy programmes within online trading platformsTrading platforms like Robinhood have launched in-app educational experiences(Robinhood Learn)that make financial lessons accessible

215、 to all customers across topics like stock trading,options trading,EFTs,initial public offerings and cryptocurrencies.44Increase retail shareholder engagement through social mediaFirms like RCI Hospitality Holdings have hosted their earnings calls on social media platforms(e.g.Twitter Spaces)to make

216、 financial fundamentals more accessible to younger retail investors and to increase their shareholder engagement beyond equity research analysts and fund managers.45Set up ETFs and indexes that help investors track emerging meme stocksRoundhill Investments has launched an ETF that tracks the perform

217、ance of stocks exhibiting a combination of elevated social media activity and high short interest through data from third-party data providers.46Robinhood has also launched an index tracking the performance of stocks most traded by its users.47Use machine learning algorithms to spot warning signs of

218、 meme-stock surgePost 2021,many hedge fund managers across North America and Asia regularly use algorithms to scour forums such as r/WallStreetBets or other data sources to spot coordinated buying behaviours.Fintechs are also providing“short squeeze risk”scores to Bloomberg terminal users and sellin

219、g social media data to fund managers.48Sector-initiatedGovernment-initiatedThe articles,guides and help forums offered by commission-free trading platforms are generally insufficient at proactively managing and identifying risky retail investor activity.To encourage real-time support for retail inve

220、stors,trading platformsexisting digital engagement prompts can be rebranded to educate investors on making trading decisions that encourage healthy risk-taking behaviour.Platforms can embed investment portfolio software intelligence algorithms within commission-free trading platforms to proactively

221、monitor,identify and offer guidance to investors making trades based on their trading activity,purchasing power and portfolio make-up.Relevant case studiesHow it could work Conditions necessary for successOpportunity overviewAll retail investors gain access to an automated investor assistant service

222、 as part of their default account settingsAlerts to diversify portfolio if it is too heavily dependent on performance of one stock or asset classDetection of heavy trading activity on margin,and prompting any negative portfolio forecasts to retail investorRetail investors have autonomy on what advic

223、e to take and can opt out of the investor assistant service at any timeRecommendations to explore new investments to promote portfolio balancingTo ensure consistency across platforms and prevent risky trading activity from being redirected,regulatory mandates should be placed on the minimum set of a

224、ctivities for all licensed online trading platforms to monitor.Data sharing permissions by retail investors to share their investment data anonymously and service the models that enable the smart assistant service.Belgian bank KBCs digital robotized investment assistant“Matti”offers automatic monito

225、ring of clients investment portfolios.The smart assistant is available for KBC and Bolero clients and non-customers with a minimum of 1,000 investment.Based on the profile and preferences of an investor,Matti proposes a portfolio and continuously monitors the investors portfolio.It is up to the inve

226、stor whether or not to follow Mattis advice.5041Launch an automated adviser model in online trading platforms for proactive investment recommendationsDEEP-DIVE OF EMERGING MITIGATION OPPORTUNITIES|MARKET VOLATILITY FUELED BY SOCIAL MEDIAIn order to proactively understand the evolving risk appetite o

227、f retail investor communities and new risk variables introduced,investment firm risk models should rely more heavily on forward-looking sources of data and real-time data feeds to aid in tradedecisions and portfolio rebalancing instead of using historic time series data and batch processing methods.

228、By supplementing real-time social media mentions and short squeeze activity data with additional forward-looking indicators and rate of change statistics,institutional investors can better track the value of a company as perceived by retail investors and understand what existing sentiment data trans

229、lates to impact on financial markets.Relevant case studiesEmbed real-time data feeds about retail investor activity into institutional investors risk modelsHow it could work Opportunity overviewReal-time data pipelines that come from trusted data sources from third-party data providersThresholds in

230、place within risk models for investment managers to contextualize real-time data feeds and identify when portfolio holdings need to be rebalanced to maintain risk profileHedge funds like Anson Funds are quantifying the risk that comes from retail activity by analysing retail trading activity as a pe

231、rcentage of daily trade volume and gathering evidence of divergence on platforms like Twitter,which signal when investor comments are shifting from positive to negative or vice versa.53Batch datasets on company performance,index performance,daily social media mentionsDatasets enter model framework f

232、or“batch prediction”at specific time intervalsRecommendations on portfolio balancing to maintain risk tolerance provided in batchesReal-time data pipelines that operationalize data into model algorithms and model outputs instantaneously can help investment managers identify the rate of change in lea

233、ding indicators for meme-stock behaviour.Real-time data pipelines sourced from third-party providers:Social media ticker mentions Short-squeeze risk scores Retail investor attendance to earnings calls Investor Index data from online trading platforms(e.g.Robinhoods Investor Index showcases the top s

234、tocks owned by users,weighted by the percentage of portfolio)Percentage of trade volume for a stock that comes from retailReal-time data pipelines51Batch data pipelines5242DEEP-DIVE OF EMERGING MITIGATION OPPORTUNITIES|MARKET VOLATILITY FUELED BY SOCIAL MEDIAConditions necessary for success43Investo

235、r manipulation from compromised sensor-generated dataOVERVIEW OF SECTOR-SPECIFIC RISK|SENSOR-GENERATED DATAAs real-time sensor-generated data becomes a mainstream approach for investment firms to improve portfolio alpha,the attack surface for malicious actors to compromise and manipulate market data

236、 for financial and political gain is rapidly widening and introducing new opportunities to destabilize markets.Open-source channels help cybercriminals share malware source code quickly and accelerate the rate of new types of IoT attacksHigh-speed 5G network infrastructure helps investment managers

237、gain instant access to real-time sensor data feedsThe wide attack surface from managing multiple IoT end points makes comprehensive security oversight challenging62Interconnectedness embedded in sensor architecture makes devices vulnerable if one device is compromisedBackgroundTwo-thirds of hedge fu

238、nds currently rely on alternative data platforms(most accessible via APIs54)to a significant or moderate degree to inform their investment decisions,identify market inefficiencies and predict future market moves.55The large-scale use of real-time sensor data in commodity industries(e.g.agriculture,e

239、nergy,metals,etc.)specifically has led to greater confidence from traders in their investment decisions within commodity markets.56 With more than 50%of the global datasphere expected to be generated from sensors by 2025,57sensor-generated data from satellites,CCTV footage,smartphones,and consumer a

240、nd industrial internet of things(IoT)devices will make up a greater share of the datasets that investment firms will rely on to inform their decisions.Emerging risks Deploying IoT botnets and tampering with sensor data feeds are becoming low-cost,high-reward methods for cybercriminals to disrupt com

241、modity markets for economic and political gain.Attack variants like the Manipulation of Demand via IoT(MaDIoT)are becoming financially accessible methods for malicious actors to deploy high-energy consuming botnets to manipulate the total demand of energy to influence global prices in favour of spec

242、ific market players.58Research suggests deploying as few as 50,000 botnets(e.g.infected thermostats,air conditioners,etc.)can successfully impact a regions power grid and influence market prices,creating economic havoc in a region.59 A growing black market for fake or corrupted sensor data may incre

243、ase the likelihood and damage of False Data Injection attacks,which compromise measurements from IoT sensors by small margins such that the manipulated sensor measurements bypass the sensors basic faulty data detection mechanism.60Gartner has forecasted a black market dedicated to selling fake senso

244、r and video data for enabling criminal activity as large as$5 billion,61making IoT attacks on financial markets more lucrative and accessible.Risk vectors 44Systemic risk scenario and amplifying forcesPOTENTIAL SYSTEMIC SCENARIO AND AMPLIFYING FORCES|SENSOR-GENERATED DATARegions democratizing 5G con

245、nectivity between devicesRegions enabling service providers to use non-proprietary components from multiple vendors to connect devices to 5G networks will become more vulnerable to the interoperability risks and security gaps that may come from a more diverse and complex vendor landscape.63If multip

246、le investment firms depend on a shared set of sensor devices that is compromised for a global commodity(either through manipulated or falsified data),misinformed trading decisions can be made across investment firms and hedge funds with the following second-order impact:Consolidation and merger tren

247、ds within the sensing industryThe sensing industry has seen a wave of consolidation between device vendors in 2022,64which will reduce the number of vendors that investment firms depend on for devices and can heighten the future collective impact of compromised sensor devices on markets.Unregulated

248、data broker industryThere is limited transparency today on the permissions,usage restrictions and data sources for alternative datasets sold to investment firms by the largely unregulated data broker industry.Unregulated data brokers may play a role in contributing to the growth of a black market fo

249、r fake data sold to cybercriminals.Regional forceEntity forceA reinforcing cycle of instability within capital markets Conflicting information between industry participants and sensor datasets leads to scepticism of the general market intelligence data provider industry,seeding further instability i

250、n capital markets and resulting in a withdrawal of capital across multiple commodity businesses due to a lack of trust.Investor liquidity challengesAltered investor sentiment and liquidity challenges as a result of flash-crash events may trigger panic sell-offs from institutional investors and drain

251、 the market from significant volumes of funds.Forces that can amplify and accelerate the riskPotential systemic risk scenario(if the sector-specific risk is not mitigated)45Target mitigation outcomes and opportunity landscapeDESIRED MITIGATION OUTCOMES AND OPPORTUNITY LANDSCAPE|SENSOR-GENERATED DATA

252、Mitigation efforts against compromised sensor-generated data should focus on increasing data quality sourced from sensors,slowing the spread of malware across a network,and proactively identifying false data injection attacks.Detecting and monitoring false data injection attacksContaining malware co

253、ntagion across a sensor networkIncreasing data quality sourced from sensors Establish global certification and labelling programmes for connected devices.Mandate due diligence processes for alternative data vendors.Protect sensor data through Entropy-as-a-Service.Employ extended detection and respon

254、se techniques that integrate data across devices.Decentralize data due-diligence processes through continuous identification of authenticated devices.Target mitigation outcomesMitigation opportunity landscapeCurrent mitigation efforts growing in adoptionEmerging mitigation opportunities for consider

255、ationThe following slides will summarize current mitigation efforts that are growing in adoption and provide thorough analysis of emerging mitigation opportunities for consideration 46Current mitigation efforts that are growing in adoptionWhile mitigation efforts to boost consumer confidence in conn

256、ected devices are gaining traction,unrealized opportunities remain for investors to trust the devices and the resulting data they receive to make trading decisions.Certifications should be mandated within asset managers data vendor due diligence processes and can be made dynamic in response to indus

257、try security updates.Data providers and companies generating data from sensors should publish their partnerships with entropy providers to establish trust with investment firms and third-party alternative data platforms.Investment firms can use RegTech solutions for vendor management compliance to s

258、trengthen their due-diligence processes for alternative data vendors,stay compliant with government guidance and minimize overhead costs from due diligence efforts.Investment firms should consider the breadth of security capabilities and technologies sensor data providers have(e.g.XDR)when sourcing

259、data for trading decisions.Considerations to strengthen existing mitigation effortsDEEP-DIVE OF CURRENT MITIGATION EFFORTS|SENSOR-GENERATED DATAEstablish global certification and labelling programmes for connected devicesGovernments in Singapore,Germany and the US have championed government-backed l

260、abels that help customers easily recognize,which devices meet the highest security and privacy practices(e.g.default passwords,security updates,functionality when offline).65Mandate due diligence processes for alternative data vendorsAfter recent violations have been placed for analytics firms misus

261、ing alternative datasets that are sold to investment firms(e.g.App Annie),the US government is beginning to scrutinize an investment firms use of alternative data in the investment decision-making process.66Protect sensor data through Entropy-as-a-ServiceThe National Institute of Standards and Techn

262、ology(NIST)in the US has recommended creating new sources of“entropy”to better secure the data that is held and transferred from sensor devices(e.g.random number generation used for encryption and decryption).Fintechs like Quantropi use quantum computing power to supply businesses with additional en

263、cryption keys to protect against IoT attacks.67Employ extended detection and response(XDR)techniques that integrate data across devicesLarge technology companies like VMware are helping companies enhance their visibility into companies networks through technology that provides 360-degree visibility

264、on suspicious activity and contextualizes seemingly unrelated attacks identified across different connected devices(XDR).68Sector-initiatedGovernment-initiatedDEEP-DIVE OF EMERGING MITIGATION OPPORTUNITIES|SENSOR-GENERATED DATADecentralizing data due-diligence through continuous identification of au

265、thenticated devicesCompanies that generate data from sensors can use device identification frameworks(that use a combination of sensor profiling variables and machine learning algorithms)to proactively protect against false data or counterfeit devices deployed in a network to manipulate sensor data

266、feeds.Continuous device identification can verify all IoT devices in a network,their data sources and variance in network traffic to ultimately prevent false data from being sent through maliciously deployed devices.69By embedding these requirements as part of the vendor procurement process for alte

267、rnative data sourcing,investment firms andalternative data platforms can decentralize due-diligence efforts for IoT devices and minimize the systemic impact of malicious sensor data tampering.Relevant case studiesOpportunity overviewConditions necessary for successHow it could workRegulatory mandate

268、s for players across the value chain(sensor manufacturers,network controllers in enterprises)to declare security measures in place for device identification.Interoperability of identification framework and data collection techniques across a majority of sensor vendor providers.Portnox is a security

269、startup that has launched the first cloud-native IoT fingerprinting and profiling solution,which is helping enterprise and mid-market businesses detect and authenticate all their IoT devices with 95%accuracy.7147Filter data from only authenticated connected devices through API gateways accessed by e

270、xternal clients(e.g.investment firms,alternative data providers)API gateway for investors or platforms Service A(e.g.alternative data platform)Service n.Illustrative data flow of company producing data(e.g.construction company)70Data collectionAnalysis engineSecurity managementCollect data using rea

271、l-time network traffic sensorsStore sensor dataClassification engine to match and authenticate IoT devices and related data sourcesSecurity layer identifies device as“legitimate”or“malicious”SensorsReal-time sensor dataHow this can be extendedPayments 48Accumulation and securitization of buy now pay

272、 later(BNPL)debt OVERVIEW OF SECTOR SPECIFIC RISK|BUY NOW PAY LATER Weak credit controls create opportunities for impulse buying and easy accumulation of debt Limited reporting requirements for BNPL debt limit the visibility of consumers total debtsSecuritization of BNPL debts could create contagion

273、 to the wider financial systemConflicting incentives exist,between protecting customer interests and increasing sales which may accelerate debt accumulation levelsBackgroundDemand for BNPL products,a short-term credit option for consumers looking to pay for purchases in instalments,is on the rise.Wh

274、ile BNPL is not a new concept,it has grown in popularity due to lenient credit approval processes and ease of access in e-commerce channels through partnerships between fintechs and retailers.In 2021 alone,BNPL payments hit over$120 billion and are projected to grow by 24%over the next three years.7

275、2By 2025,12%of global e-commerce spend is estimated to come from BNPL transactions.73BNPL provides easy credit with the convenience of interest-free instalment payments for consumers who may not qualify for a bank loan or who have overdrawn their savings or credit cards.For merchants,BNPL has been i

276、nstrumental in boosting sales and acquiring new customers.Emerging risks The nature of BNPL credit creates opportunity for overborrowing and the piling up of shadow debts.BNPL loans appeal to consumers who may not be eligible for loans from traditional channels,have maxed out their credit limits or

277、exhausted savings.Research shows that consumers are inclined to spend spontaneously and are three times more likely to complete their online purchases instead of abandoning them in the cart when presented with a BNPL financing option.74Millennials are notably high users of BNPL credits,with the volu

278、me of transactions by this age demographic increasing by more than 400%in the last couple of years.75 According to Barclays,a quarter of BNPL users already feel unsure about their ability to settle their BNPL debt.Additionally,the Federal Reserve Bank report indicates that 18%of young consumers have

279、 already fallen behind on their repayments.76 BNPL default risk may also spill over to the broader financial system through securitization.As a capital-raising strategy,BNPL providers package outstanding BNPL debt and sell it to investors as securitized assets.In a weak economic cycle,the ability of

280、 consumers to repay their loans may be impacted,potentially leading to large delinquencies.Similar to the mortgage-backed security crisis in 2008,if the scale of BNPL securities grows significantly,large-scale defaults may have a spiralling effect on the financial system.Research by S&P has indicate

281、d that the volume of securitized BNPL assets is on the rise in Europe,77with Fitch sounding the alarm on the credit risks associated with this product.7849Risk vectors Easy access to BNPL credit coupled with weak underwriting rules may lead to overborrowing and potentially spill over to the financia

282、l system through debt securitization.50Systemic risk scenario and amplifying forcesPOTENTIAL SYSTEMIC SCENARIO AND AMPLIFYING FORCES|BUY NOW PAY LATER Entrance of Big Techs into BNPL credit space The new BNPL products that Big Tech players are embedding within their existing product ecosystems(e.g.A

283、pple Pay Later,Amazon Pay Later)are rapidly widening the userbase that is exposed to short-term instalment credit.If the volume of BNPL debt were to grow to significant levels and a large percentage were securitized as subprime borrower debt,a protracted economic recession event may impact consumers

284、 ability to repay their loans synchronously,resulting in large delinquencies with the following second-order impacts:Jurisdictions with regulatory guidelines not covering BNPL loans The absence of regulatory guidelines in jurisdictions where BNPL finance is offered has created opportunities for arbi

285、trage(exploiting regulatory loopholes across jurisdictions),resulting in lending practices that may be detrimental to consumers financial well-being.Low financial literacy ratesConsumers in jurisdictions with lower financial literacy rates and inadequate access to money management resources are more

286、 susceptible to impulse buying and likely to overborrow.79Regional ForceEntity ForceDecline of consumers well-beingConsumers that have accumulated large and unsustainable levels of debt may struggle and experience financial distress.Bank credit delinquenciesBank loans given to customers who have acc

287、umulated BNPL debts may experience large delinquencies as their ability to repay existing debts diminishes.Banks could also tighten the requirements and willingness to lend credit to customers.Investor lossesFirms that have invested in BNPL-backed assets may absorb large losses when securitized asse

288、ts decline in value.Forces that can amplify and accelerate the sector-specific riskPotential systemic risk scenario(if the sector-specific risk is not mitigated)51Target mitigation outcomes and opportunity landscapeDESIRED MITIGATION OUTCOMES AND OPPORTUNITY LANDSCAPE|BUY NOW PAY LATERMitigation opp

289、ortunities to address the risks from short-term instalment credit products like buy-now-pay-later must protect customers from overborrowing,improve transparency on customers ability to pay and inform investors on the quality of securitized debt.The following slides will summarize current mitigation

290、efforts that are growing in adoption and provide thorough analysis of emerging mitigation opportunities for consideration Transparency on quality of securitized debt to protect investorsTransparency on customers ability to payCustomer protection from overborrowing Design safeguards to protect agains

291、t overborrowing and misleading advertising.Develop a code of conduct for BNPL providers to support appropriate loan labelling.Enhance data sharing between BNPL providers.Include BNPL data in credit bureau reporting.Use open banking platforms to enhance affordability checks on customers.Design a rati

292、ng framework to evaluate and rate securitized BNPL debt portfolios.Target mitigation outcomesMitigation opportunity landscapeCurrent mitigation efforts growing in adoptionEmerging mitigation opportunities for consideration52Current mitigation efforts growing in adoptionDevelopment of regulatory fram

293、eworks for BNPL products should include input from BNPL providers and other market participants to ensure buy-in and balancing of consumer and product owner interests.Codes of conduct that are developed regionally should be assessed and compared with other regional associations to acknowledge any ga

294、ps or contradictions that may encourage arbitrage.To protect consumers interests,data privacy should be prioritized so that data is shared between BNPL providers safely and securely.Due diligence on alternative data sources should also be done to ensure synthetic data from generative AI applications

295、 is not used to pass creditworthiness assessments.Credit bureau reporting models should consider increasing the frequency of BNPL reporting given the short-term instalment nature of BNPL loans.Considerations to strengthen existing mitigation effortsDEEP-DIVE OF CURRENT MITIGATION EFFORTS|BUY NOW PAY

296、 LATER Sector-initiatedGovernment-initiatedDesign safeguards to protect against overborrowing and misleading advertisingRegulatory authorities across Europe and Oceania are designing safeguards(affordability checks,borrowing limits,fair promotional practices etc.)to protect consumers from overborrow

297、ing.Jurisdictions across Asia are also exploring rules prohibiting consumers with unsettled balances from further borrowing(e.g.Singapore).80The Financial Conduct Authority(FCA)will now sanction firms breaching financial promotion rules.81Enhance data sharing between BNPL providers Regulatory author

298、ities like the Monetary Authority of Singapore(MAS)are beginning to encourage BNPL providers to exchange data of consumers,including those with past-due obligations,to check against loan stacking and enhance affordability checks.82BNPL providers are also using accessible alternative data to adjudica

299、te credit applicants more thoroughly.83Develop a code of conduct for BNPL providers In Australia,BNPL providers are self-organizing to standardize lending practices and ensure minimum operating standards are adopted.The Australian Finance Industry Association(AFIA)published a set of commitments in M

300、arch 2021 that members are required to comply with to protect consumer interests and ensure transparency.84Include BNPL data into credit bureau reportingTo enhance affordability checks,some BNPL providers like Zilch and PayPal are running soft credit checks before loans are approved.Credit bureaus l

301、ike Equifax,Transunion and Experian have also launched the inclusion of BNPL payment information as part of their credit reporting data requirements.85While current mitigation efforts are focused on minimizing debt accumulation levels,unrealized opportunities remain to protect investors from securit

302、ized BNPL investments and enhance transparency for credit providers.Aggregating data from banks and other players within the open banking ecosystem can provide BNPL providers access to a comprehensive view of the customers spending habits,which can subsequently feed into their lending decisions.Cons

303、umers already overextended with other lenders and at risk of overborrowing can be identified and precluded from new credits until outstanding balances are settled.Relevant case studiesHow it could work Using APIs,BNPL providers could connect with already existing open banking ecosystems to gain secu

304、re access to customer dataheld by other banks.Consumers who consent to their data being accessed and used in the underwriting process may be rewarded with rebates on service costs such as late fees and interest charges.Admission of BNPL entities into the open banking ecosystem.Strong data privacy an

305、d security requirements for BNPL providers.Zilch,a BNPL provider headquartered in London,uses open banking in addition to soft credit checks to connect with consumers bank accounts to get a real-time view of consumers spending habits and to gauge affordability before approving BNPL loans.86Consumer

306、opts for BNPL finance option on retailers online shopping e-commerce siteCustomer transaction data is aggregated and used for KYC and lending decisionsBNPL providers get approval to access consumers data from other financial institutions via open banking platform53DEEP-DIVE OF EMERGING MITIGATION OP

307、PORTUNITIES|BUY NOW PAY LATER Make use of open banking platforms to enhance affordability checks on customersConditions necessary for successOpportunity overviewAlthough rating agencies have not yet commenced rating BNPL credits,some are signallinginterest in this space.S&P Global,for instance,has i

308、ndicated that in addition to evaluating BNPL credits on a case-by-case basis,they would likely examine the extent to which BNPL providers rely on third-party services such as a trust account or back-up servicer(a firm that manages portfolio of assets or receivables when the primary servicer is unabl

309、e to perform).8754Design a rating framework to evaluate and rate securitized BNPL debt portfolios DEEP-DIVE OF EMERGING MITIGATION OPPORTUNITIES|BUY NOW PAY LATER To better assess the quality of underlying debts for BNPL assets issued to investors,rating organizations like Fitch Ratings,Moodys Inves

310、tors Service,and S&P could incorporate an assessment of BNPL securities as part of their ratings services.Similarto how banks are rated based on the quality of their credit portfolio,BNPL providers with sound credit underwriting processes and risk management in place can be assigned ratings to guide

311、 investors in pricing their credits.BNPL firms with positive ratings will be less likely to default and,therefore,more trusted by investors.How it could work Relevant case studiesCredit rating agencies design framework and criteria for assessing BNPL creditsRating grades are assigned based on the qu

312、ality of the loan book and risk management processes in placePeriodically,BNPL firms open their credit portfolio for scrutiny and assessment The rating criteria should be clear and transparent,so that investors can understand the basis for the ratingsCredit ratings should be objective and independen

313、t without external influenceCredit ratings should be consistent and comparable across different BNPL providers Opportunity overviewConditions necessary for success55Security vulnerabilities of decentralized CBDC architecture OVERVIEW OF SECTOR-SPECIFIC RISK|CENTRAL BANK DIGITAL CURRENCIES(CBDCs)Due

314、to their complexity and the involvement of multiple entities,CBDCs running on decentralized ledger technology widen the attack surface for malicious actors.Participation of multiple entities in the DLT network broadens the attack surface that hackers could exploitBugs or malfunction of the DLT platf

315、orm that supports a CBDC could cripple the system Side-channel attacks could be used to break into user wallets and steal consumer funds92BackgroundCentral bank digital currency(CBDC)is a digital representation of fiat currencies issued and backed by a central bank authority.Central banks are explor

316、ing the use of CBDCs for wholesale(e.g.interbank settlement)and retail(e.g.cross-border payments)applications to improve payment efficiency,expand access to the financial system,and facilitate the execution of monetary policy.88 There is a growing interest in CBDCs,with several central banks in diff

317、erent stages of exploration.As of January 2023,119 countries are exploring CBDCs,with 11 countries at launch stage.89Several design variants are being considered for CBDC implementation,including centralized,permissioned distributed ledger technology(DLT)and hybrid models.In a centralized model,a ce

318、ntral authority,typically the central bank,maintains and controls a centralized ledger that records the transactions.In the DLT model,cryptographic methods are used to record data across a network with the participation of multiple entities(such as banks).The hybrid model combines elements of both t

319、he centralized and DLT models.Several central banks are considering DLT for CBDC deployment as it offers cryptographic security,transparency,decentralization and lower intermediation cost.90The number of central banks that have conducted CBDC pilots using DLT network is growing,including the Monetar

320、y Authority of Singapore(MAS),the Bank of Thailand and the Bank of Japan(BOJ).While the security profile of the centralized model is known and comparable to existing payment systems,stakeholders should pay attention to the new risks that the DLT model might introduce due to its relative novelty and

321、the evolving understanding of its security profile when deployed in large,global use cases.Emerging risks Expanded attack surface:The involvement of multiple parties within the CBDC network introduces additional endpoints that could be vulnerable to attacks.Even though the number of participants in

322、a permissioned DLT network is restricted,a malicious actor could target participating institutions within the CBDC network to gain unauthorized access to the CBDC system by stealing or forging their credentials.91 Security risks from flaws in programming:Programming flaws in the DLT network or the u

323、nderlying smart contracts that support the programmability features of CBDCs might be exploited by malicious actors to perform unauthorized transactions or steal user data.Risk vectors 56Systemic risk scenario and amplifying forcesPOTENTIAL SYSTEMIC SCENARIO AND AMPLIFYING FORCES|CENTRAL BANK DIGITA

324、L CURRENCIES(CBDCs)Complexity of the DLT architecture The more complex the architecture design of the CBDC network,the harder it is to trace and resolve issues.For example,if the CBDC network uses multiple types of smart contracts with different programming languages,it may be difficult for develope

325、rs to identify and fix vulnerabilities in a timely manner.A foreign nation-state launches a distributed denial-of-service(DDoS)cyberattack on the CBDC payment network of another country by targeting a security vulnerability of one of the participating institutions,causing outages of critical service

326、s.As a result,the payment system of the country is disrupted,making it difficult for individuals and businesses to conduct transactions and causing the following second-order impacts:Interoperability with other networksAs the CBDC network becomes more interoperable with other networks(such as paymen

327、t rails or the CBDC of another country),the more vulnerable it is to attacks from those networks.For example,if a CBDC network is connected to a less secure network,attackers can exploit the flaws to compromise the CBDC network.Large number of participating institutionsAs more institutions are conne

328、cted to the CBDC network,the level of cyber vulnerabilities rises due to the increased number of entry points that might be exploited by malicious actors,necessitating the need for robust security protocols.Regional forceEntity forceFinancial lossesIndividual users might suffer financial losses whil

329、e participating financial institutions might be liable to cover customer losses.Additionally,the reputation of the central bank and other participating banks could be negatively impacted.Disruption of global tradeProlonged outage of the CBDC network may impede the settlement of payments for internat

330、ional trade transactions,making it difficult for businesses to meet their obligations.Loss of confidence The confidence of users in the safety and reliability of the CBDC system might be diminished leading to a decline in its usage and a shift towards privately issued digital currencies for internat

331、ional trade settlement.Forces that can amplify and accelerate the riskPotential systemic risk scenario(if the sector-specific risk is not mitigated)57Target mitigation outcomes and opportunity landscapeDESIRED MITIGATION OUTCOMES AND OPPORTUNITY LANDSCAPE|CENTRAL BANK DIGITAL CURRENCIES(CBDCs)Centra

332、l banks exploring the implementation of CBDCs using DLT as the underlying technology should prioritize protecting the security and privacy of end users and their data,implementing strong access controls and network security measures and collaborating with other countries to ensure that security prot

333、ocols are standardized globally.Cross-border security standardizationStrong access control and network securityUser protection and data privacy Strengthen end-user digital wallet protection.Establish a tiered ledger system for the CBDC database.Design quantum-resistant algorithms for futureproofing CBDC systems.Manage the risks of DLT through blockchain sharding.Standardize CBDC security protocols