剑桥2022年监管科技报告 CAMBRIDGE SUPTECH LAB REPORT 2022 STATE OF SUPTECH

STATEOFSUPTECHREPORT2022

SUPPORTEDBY

ABOUTTHE

TheCambridgeSupTechLabattheCambridgeCentreforAlternativeFinance,theUniversityofCambridgeJudgeBusinessSchool,acceler-atesthedigitaltransformationoffinancialsupervision.

Whilefinancialservicesarebecomingincreasinglyglobal,digitalandcomplex,analogueprocessingandantiquatedtechnologiesindatagathering,validation,storageandanalysiserodetheanalyticalcapa-bilitiesofsupervisoryagencies,whoareoftentoolateinprotectingconsumersfromfraudandseeingsignsofstressinthefinancialsys-temormisstheunderlyingcauses.Thisisallhappeningwhilefinancialcrimeremainsatrillion-dollarissue,andpublicagenciesfacenewchallengessuchastheregulationandsupervisionofcryptoassets,andmonitoringenvironmental,socialandgovernance(ESG)aspectsofthefinancialindustry’sbusiness.

TheLabaimstomeetfinancialsectorsupervisors’needsbyworkingwiththemtodevelopnewmethodologiesandprocessesthatfurthermarketoversightandempowerconsumers,andtodeployhsuptechapplicationsthatgeneraterelevant,reliable,timelyinsightstoinformtheirdecisions.

Fromresearchtoexecutiveeducation,totechnicalassistance,tocraftingproduction-gradesuptechsolutions,wearecommittedtosupportingtheemergenceofthesuptechecosystemandtoem-poweringanewgenerationofinnovationleadersseekingtodigitallytransformfinancialsupervision.

Weinviteyoutofindoutmoreat

@Cambridesuptechlab

@CamSupTechLab

CAMBRIDGESUPTECHLAB

Suggestedcitation:

CambridgeSupTechLab(2022),StateofSupTechReport2022,Cambridge:CambridgeCentreforAlternativeFinance(CCAF),UniversityofCambridge.Availableat/SOS

Thementionofspecificcompanies,manufacturersorsoftwaredoesnotimplythattheyareendorsedorrecommendedbytheCambridgeSupTechLabinpreferencetoothersofasimilarnaturethatarenotmentioned.

Allgraphicsandchartscanbedownloadedat/SOS

Authors

SimonediCastri

MattGrasser

JulietOngwae

JoseMiguelMestanza

Design

MartaLopera

EmilyDuong

JessicaAli

Copyediting

AlpaSomaiya

AdebolaDaramola,Alexander

Apostolides,KyriakosChristofi,PhilipRowan,YueWuandBryanZhangoftheCambridgeCentreforAlternativeFinance(CCAF)contributedtotheanalysis.

TheCambridgeSupTechLab

issupportedby

TABLEOFCONTENTS

EXECUTIVESUMMARY 6

SAMPLE,METHODOLOGY,ANDTAXONOMY 10

1.1.Researchmethods 11

1.1.1.Sampleoffinancialauthoritiesbygeographyandincomeclassification 11

1.1.2.Questionnaireforfinancialauthoritiesonspecificsofsupervisorydata 13

1.1.3.Questionnaireforsuptechvendors 13

1.2Suptechtaxonomy 15

1.2.1.Supervisoryareasandusecases 15

1.2.2.Technologiesanddatasciencetoolsinthesupervisorystack 16

EVOLUTIONOFTHESUPTECHLANDSCAPE 18

2.1.Timelineofthedigitaltransformationoffinancialsupervision 19

987–2007:Suptechfoundations 21

008–2016:Theglobalfinancialcrisisandthemassadoptionoffintech 21

017–2019:Thedawnofsuptech 22

020–present:Covid-19acceleratessuptech 23

THESTATEOFSUPTECH 24

3.1.Demand:Financialauthorities 25

3.1.1.Adoption 25

3.1.2.Gaps 30

3.1.3.Suptechgenerations2.0 33

.Datacollection 36

.Dataprocessing 37

.Datastorage 37

.Dataanalytics 38

.Dataproducts 38

3.1.4.Supervisoryareas 39

3.1.5.Enablingfactors 40

3.1.6.Funding 40

3.1.7.Governance 42

3.1.8.Gender 46

3.1.9.Outcomes 48

3.2.Supply:Sourcingsolutions 50

3.2.1.Sourcesofsuptechapps 50

3.2.2.Thevendor’sbusinesscase 51

3.2.3.Offeringsbyfocusarea 52

3.2.4.Funding 52

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CHALLENGESTOUPTAKE.........................................................................................................................53

54

4.1.1.Implementation 54

4.1.2.Datalifecycle 57

4.1.3.Resources 57

4.1.4.Infrastructure 61

4.2.Challenges:vendors 61

CASESTUDIES 64

5.1.Datacollection:BankofEnglandtransformingdatacollectionfromtheUK

financialsector 65

5.2.Dataprocessing:CentralBankofthePhilippinesAPI-basedprudentialreporting

systemandback-officereportingandvisualisationapplication 69

5.3.Datastorage:NationalBankofRwandaElectronicDataWarehouse 73

5.4.Dataanalytics:CentralBankoftheNetherlandsoutlierdetectiontoolforAML/

CFT/PFsupervision 76

5.5.Dataproducts:ReserveBankofIndia(RBI)DAKSH 81

5.6.Fullstack:BISProjectEllipse,anintegratedregulatoryreportinganddata

analyticsplatform 82

CONCLUSIONS 86

Developasuptechstrategyand/orroadmap 87

Builddatacapabilitiesforthesupervisorsofthefuture 88

Growadata-driveninnovationculture 88

Scale 89

References 90

Appendix1:Listofrespondents 95

Appendix2:SuptechTaxonomy 102

Appendix3:Definitions 106

4.1.Challenges:financialauthorities

CAMBRIDGESUPTECHLAB

EXECUTIVESUMMARY

6|STATEOFSUPTECHREPORT2022

TheCambridgeSupTechLab

StateofSupTechReport2022presentsinsightsonthecurrentstateofthedigitaltransformationoffinancialsupervisionworldwide.

TheReportprovidesaglobalsnapshotacrossseveralfacetsofsuptech,includingunderpinningdigitalinfrastructureandtechnologies,supportedsupervisoryusecases,approachesemployedfordevelopinganddeployingsuptechapplications,andtherelatedchallengesandrisks.

TheStateofSupTechReport2022focusesathowfinancialauthoritiesaredevelopingandimplementingsupervisorytechnologies(suptech),andestablishesabaselinefromwhichtotracktheprogressandimpactofsuptechadoptionallowingfinancialauthoritiesacrosstheworldtobenchmarktheprogressoftheirsuptechinitiatives.

Tofacilitatemoregranularanalysesofthesemacrotrends,theReportintroducesanovelversionofthe“SupTechTaxonomy”adoptedbytheBankforInternationalSettlements(BIS)(

BIS2018

,

BIS2019

),classifyingsupervisoryusecases,technologies,anddatasciencetoolsinastandardizedandstructuredmanner.Inordertocomplementtheanalysesandtogroundthefindingsinapracticalcontext,theReportalsoprovidesatimelineofdisruptionsandinnovationsinsupervision,andasetofsixcasestudiesofsuptechapplications.

TheReportisbasedontheinsightsthat146financialauthoritiessharedthrough:

•Asurveyof134financialauthoritiesfrom108jurisdictions

•Aquestionnaireondatamodelswith74individualsupervisorsrepresenting46agenciesand35jurisdictions.

Theanalysisalsoadvancestheunderstandingofthesuptechmarketplacefromthesupplyside,providingcriticalinsightsfromthenascentbutrapidlygrowingindustryofsuptechvendorsthroughin-depthqualitativeresearchofkeyvendorssampledfromtheCambridgeSupTechLab’s

SupTechMarketplace

andhighlightingtheirperspectivesonthebusinesscaseforsuptech,theprimaryusecasestheyfocusonandthechallengestheyfaceincommercializingsuptechsolutions.

CAMBRIDGESUPTECHLAB|7

HighlightsFROMTHE

stateofsuptechREPORT2022

•Suptech‘ishappening’.Mostfinancialauthoritieshavealreadyengagedinsuptechinitiatives.

Whilesuptechdevelopmentisstillatanascentstagewithroomforgrowth,thesurveyresultsindicatethat71%offinancialauthoritiesarerisingtothechallengeasweseetheadoptionofsuptechsolutions,strategiesandroadmapsincreasing.

•Suptecheffortsremainintheexperimentationstage,primarilyfocusedonimprovingdatacollectionandbasicanalysis.

Basedontheclassificationprovidedby

theBankforInternationalSettlements

(

BIS2019

)andrevisedbytheLabinthis

report(seechapter3),thetechnologies

deployedbyfinancialsupervisorsmostly

fallintothefirstorsecondgenerationof

dataarchitecture,andmainlysupport

datacollectionaswellasdescriptiveand

diagnosticanalytics.

•Mostsuptechusecasescentrearoundconsumerprotectionandprudentialsupervision.

59%offinancialauthoritiesreporttheirsuptechapplicationsbeingdeployedinsupportofconsumerprotectionsupervision,while58%reporttheirsuptechapplicationssupportprudentialsupervision

usecases.

•Significantchallengestosuptechadoptionremaintobeaddressed.

Limitationsinbudget,dataqualityandtechnicalskillsremainthemostsignificantbarrierstoimplementingsuptech.Thereisaremarkablemismatchbetweentheexperienceoffinancialauthoritiesandvendorswhenitcomestoprocurement,withtechnologiesprovidersurgingthepublicagenciestoaddresslegacyprocurement

processes.

Financialauthoritiesalsoexpressanunmetneedfordatateams,datasharinganddata

synthesisasafoundationalpartoftheirmodernization.

•Therearesignificantdistinctionsinthestateofsuptechinemergingmarketsanddevelopingeconomies(EMDEs)ascomparedtoadvancedeconomies(AEs).

FinancialauthoritiesinAEsareearlyadoptersofsuptech,moreoftenhavesufficientdigitalinfrastructure,moreoftenassigndedicatedsuptechrolesanddepartments,haveseenmoresubstantialinternaloutcomesthanthoseinEMDEs,andseekfundingprimarilytogrowtheirteams.EMDEsageciestendtorunsuptechinitiativeswithinthesupervisiondepartmentitself,aremoreinterestedintrainings,technicalassistance,digitaltools,andseekfundingprimarilyfordesignanddevelopmentofsuptech.

•FinancialauthoritiesinEMDEsandinAEsfaceverysimilarchallengesinthedigitaltransformationoftheirsupervisoryprocessandcapabilities.

AgenciesinEMDEsandAEsreportlackofbudgetbeingthemainconstrainttothedevelopmentanddeploymentofsuptech.

•Centraliseddataofficemodelstoacceleratesuptechdevelopmentandimplementationareemerging.

35%ofthesurveyedfinancialauthoritieshaveadedicatedcentralisedofficereportingtoaChiefDataOfficerwhoiseithersolelyresponsibleforthesuptechinitiativesorworkswithotherfunctionstodevelopanddeploysuptech.

•Fundingtoacceleratethesuptechmarketisakeyareaoffocus.

Althoughsuptechvendorsreportsomesecondarysupportfromgrants,fundingforfinancialauthorities’suptechinitiativescomesprimarilyfromthefinancialauthoritiesthemselves.Mostsuptechsolutionsareprovidedbyexternalsources

8|STATEOFSUPTECHREPORT2022

CAMBRIDGESUPTECHLAB|9

likecontractedvendorsandpurchasedoff-the-shelfsoftware,yetthesevendorsalsoreportchallengesinfundingandanabilitytodeeplyunderstandfinancialauthorities’prioritizedneeds.

•Thetopsuptechchallengesdifferbetweenagencytypes.

Forcentralbanks,thechallengesareprimarilyrelatedtointernalcultureandstrategicbuy-in.Forcapitalmarkets,securities,andinvestmentinstrumentssupervisors,challengestendtoberelatedtoupgradingtheirexistingsystemsandprocesses.Forothersupervisors,theuniquelyprominentchallengesarewithITsystems.

•Mostauthoritiesstilldonothaveagenderdatastrategy.

Only21%haveacurrentlyoperatingstrategy,9%haveoneindevelopment,while70%reportnostrategyatall.

•Suptechisenablingnewsupervisoryusecasesthatwouldnototherwisebepossible.

WhilesuptechsolutionsusechatbotsandAPIstooptimizeexistingprocessesandaugmentlegacytools,othersareopeningcompletelynewopportunitiesforsupervisors.Theabilitytoingestmassiveonlinedatasetslikesocialmediastreamstoconductsentimentanalysis,toparseonlinereviewstoassessrisksoridentifyfraudulentfintechapps,andtoconductreal-time,on-chainanalysesfordigitalassetssupervisionarejustafewofmanyexamples.

Takenonthewhole,theseinsightsframeasuptechspacethatisrelativelynascent,butrapidlyandnecessarilyacceleratingtoaddresstheneedsofsupervisorsinthefaceofnovelandnewly-magnifiedrisksintroducedbyafinancialsectorthatisdigitalizingandgeneratingsupervisorydataatanexponentialrate.Addressingtheneedsoftheecosysteminaneffectiveandequitablemannerwillrequireclosecollaborationbetweenfinancialauthorities,vendors,funders,educators,researchers,technologists,datascientists,andtherestofthesuptechecosystem.

ThisinauguralannualStateofSupTechReportaimstofeedthatconversationandsupportcollaboration,buildingabaselineagainstwhichtoconductagencyandregionalbenchmarking,methodicallytrackingyear-on-yeartrends,andagrowthofamarketplacetoservetheneedsofsupervisors,whointurnservetheinterestsofthebillionsoffinancialcitizensofthejurisdictionstheyoversee.

1.

SAMPLE,METHODOLOGY,ANDTAXONOMY

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1.1.Researchmethods

Threeprimarydatasourceswereusedtocompilethisreport:

•Asurveyof134financialauthoritiesfrom

108jurisdictions

•Aquestionnairefor74individualsupervisors(representing46agenciesand35jurisdictions)onthespecificsofsupervisorydata

•Aquestionnaireforsixselectedsuptechvendors.

Inaddition,theLabcomplementedtheseresourceswithqualitativeinterviewsandcasestudiestofurtherdevelopandtesthypothesesarisingfromthequantitativedataandmoredeeplyunderstandthechallengesandopportunitiesinadoptingsuptechapplications.

1.1.1.Sampleoffinancialauthor-itiesbygeographyandincomeclassification

MostofthedatapresentedinthisReportwerecollectedbetweenMayandOctober2022throughaglobalsurveyconductedbyCambridgeSupTechLab.Therespondentsincludefinancialauthoritiessuchascentralbanks,securitiesandcapitalmarketauthorities,financialconductauthorities,andinsuranceregulators.Ofthe134responses,81arefromcentralbanks,representing60%ofthetotalsample.92responseswerereceivedfromagenciesinemergingmarketsanddevelopingeconomies(EMDEs),representing67%oftheresponses,whiletheremainderwerefromadvancedeconomies(AEs).

Figure1.

Geographicaldistributionofsurveyrespondents

Numberof

Agencies

PERCOUTRY

1

2

3

CAMBRIDGESUPTECHLAB|11

ThefinalrespondentsampleisgeographicallydiverseandrepresentativeofWorldBankCountryincomegroups.

Table1mapsthe108geographicjurisdictionsofthe134financialauthoritieswhorespondedtothesurvey.ThecompletelistisavailableinAppendix1.

Figure2illustratestheresponse

distributionaccordingtotheWorldBank’sclassificationbyincomelevel.Thesamplecontainsresponsesfromjurisdictionsacrossallfourincomeclassifications,with55responsesfromeitherloworlower-middle-incomejurisdictions.Insomeareasoftheanalysis,wegroupthesecategoriesintoEMDEs(low,lower-middleandupper-middleincome)andAEs(highincome).

TABLE1.

GeographicaldistributionofrespondentsByregion

Region

EastAsiaandthePacificEuropeandCentralAsiaLatinAmericaandthe

Caribbean

TheMiddleEastand

NorthAfrica

NorthAmerica

SouthAsia

Sub-SaharanAfrica

Total

Percentageofsamplebyregion

16%

22%

20%

10%

2%

5%

25%

Percentageof

jurisdictions

coveredwithin

region

46%

41%

44%

46%

100%

63%

48%

Numberofrespondents

22

29

27

14

3

6

33

134

*IncomeandregionarebasedontheWorldBankCountryClassification.Ifajurisdictionwasnotlistedgeo-graphically,itsclassificationwasbasedonneighboringjurisdictions.

Figure2.

Breakdownofrespondentsbyincomegroups(N=134)

12|STATEOFSUPTECHREPORT2022

1.1.2.Questionnaireforfinancialauthoritiesonspecificsofsupervisorydata

InNovember2022,weaskedindividualsupervisorsfourquestionsonthespecificsofsupervisorydatatofurtherassessthestateofdatacollectionforfinancialsupervision:

1.Thematicareas:thesupervisoryareasforwhichdataiscollected

2.Channels:themechanismsandchannelsthroughwhichitiscollected

3.Formats:thedigitalformatandstructureofdatathatiscollected

4.Challenges:thespecificchallengesfacedateachlayerofthesupervisorydatalifecyclestack

Wereceivedinformationfrom74supervisorsrepresenting46agenciesand35jurisdictions.Thissampleincludedsomesupervisorswhoseagenciesdidnotparticipateintheprimarysurvey,whoseagenciesarelistedinAppendix1.

1.1.3.Questionnaireforsuptechvendors

Tocomplementtheinsightssharedbythedemandsideofthesuptechmarketanddevelopadeeperunderstandingofthebroadersuptechecosystem,wealsoengageddirectlywithsixsuptechvendorstodiscusstenquestionsthat

characterisetheopportunities,challengesandotherqualitativecharacteristicsofthemarket.ThevendorswereselectedfromtheCambridgeSupTechLab’s

SupTech

Marketplace

VendorDatabasebasedonthefollowingcriteria:

•Centricityofsuptechinstrategicfocus:Whilesomevendorsprovidesuptechsolutionsasasmallpartofabroaderportfolioofproductsandservices,othersfocusprimarilyonsuptechsolutions.Forthissetofinterviews,weprioritisedthelatter.

•Maturityofoffering:

Thesampleprioritisedvendorswithamatureproductorservicetoensureactualexperiencesinforminterviewsofoperatinginthemarket,nothypotheticalorearly-stageideasbasedonlyonpilotsorexperiments.

•Diversityofmarketposition:Thesampleaimedtoincorporatearangeofmarketperspectives,includingrelativelynewentrants(thosewhohaveonlyrecentlyadaptedtheirmatureofferingtoaddresssupervisoryusecases)andthosewhohavebeenworkingwithsupervisorssincebeforetheinceptionoftheword‘suptech’.

•Diversityofgeographieswheresolutionsaredeployed:

Thesampleaimedtocaptureexperiencesacrossarangeofjurisdictionstoavoidsamplebiastowardanyonesetofculturalnormsorlocalisedmarketrestrictions.

CAMBRIDGESUPTECHLAB|13

Figure3:

Suptechtaxonomy

14|STATEOFSUPTECHREPORT2022

CAMBRIDGESUPTECHLAB|15

1.2Suptechtaxonomy

TheCambridgeSupTechLabhasdevelopedacomprehensiveclassificationsystemtoconsistentlyorganisevariousentities–namely,suptechvendors,suptechsolutionsandsuptechdiagnostics–bysupervisoryusecase(the‘sup’insuptech)andbythetechnologiesanddatasciencetoolsused(the‘tech’).

Thistaxonomyisbasedonpasteffortstomapthespace(

BIS2018

,

BIS2019

)andexplicitlydifferentiatesbetweenthe‘sup’andthe‘tech’.Thisdisaggregationaffordsanovelopportunitytosystematicallymaptheneedsofsupervisors,classifythetoolsservingthoseneedsandultimatelyserveasanontologyforconnectingthesolutionstoneedsstrategicallyandintentionally.Itwasrefinedandvalidatedthroughdeskresearch,reviewofdeployedsuptechapplications(seetheLab’s

SupTech

Marketplace

),andinputfromover130financialsupervisorsandleadingsuptechexperts.Thetaxonomywillbeperiodicallyrevised,basedoninternalresearchandexternalfeedback,toreflectthesuptechspace’sdynamicnature.

1.2.1.Supervisoryareasanduse

cases

Thisfirstiterationofthetaxonomycovers13broadsupervisorycategoriessubdividedinto87usecases.Thestructureoftheclassificationsystemishierarchicalandbuiltonaconceptualframeworkthatgroupsusecasesaccordingtotheactivitiesconductedbysupervisoryfunctionswithinauthorities.

Whilethematicfocusareasrefertopolicyorsupervisoryareas/activities,usecasesrefertomorespecifictaskssupportedbyidentifiedsuptechtools.

The13thematicfocusareasare:

Anti-MoneyLaundering/CounteringtheFinancingofTerrorism/FinancingtheProliferationofWeaponsofMassDestruction(AML/CFT/PF)supervision:

Suptechallowsfinancialauthoritiestoidentifypotentiallysuspiciouscustomersoractivities(forexample,throughcustomerduediligenceandsuspicioustransactionsdetection)andenhancesdataanalyticstomonitorinstitutions’complianceandAML/CFT/PFriskmanagement(forexample,assisted/automatedexamination,metadataanalytics,andtextanalytics).

Capitalmarkets,securitiesandinvestmentssupervision:Suptechequipsfinancialauthoritiestodetectpotentialmisconduct(forexample,insidertrading,marketmanipulationandpoordisclosure)andenhancesdataanalyticstomonitorthecapitalmarkets(forexample,automatedexamination,peer-group/riskclassificationandtextanalytics).Securitiesandinvestmentsusecasesfocusonempoweringsecuritiescommissionsandotherfinancialauthoritieswithasecuritiesmandatetoaugmenttheircapabilitiesbygeneratingimproveddata-driveninsightsanddetectinginsidertradingandmarketmanipulation.

Climate/ESGrisksupervision:Suptechenablesfinancialauthoritiestoenhancedatacollectionandanalyticstoassessinstitutions’climateandenvironment,socialandgovernance(ESG)riskmanagement(forexample,greenmarketmonitoring,peer-group/riskclassificationandstresstesting).

Competitionmonitoring:Suptechfocusesonmonitoringmarketcompetitiondynamicsandratesandfees.

Complianceassistance:Suptechmakesavailableautomatingcomplianceauditingandautomatedguidanceforcompliancequeries.

Licensing:Suptechsupportsfinancialauthoritiesprovidingvirtualassistancetofirmsrequestingalicenseorauthorisationtooperatewithintheregulatoryperimeter(forexample,automatedguidanceandautomatedprocessingofrequests).

Paymentsoversight:Suptechassistsfinancialauthoritiesinmonitoringandtestingtheperformanceofpaymentsinfrastructures,networksandsystems(forexample,advanced/real-timemonitoringandstresstesting).

Prudentialsupervisionofbanksandnon-bankdeposit-takinginstitutions:(nowreferredtoasprudentialsupervision):allowsfinancialauthoritiestoenhancedatacollection(forexample,automatedreporting,automatedvalidationanddataconsolidation)anddataanalyticsforbothmacroprudentialandmicroprudentialsupervision(forexample,assisted/automatedexamination,peer-group/riskclassificationandstresstesting).

ThecompletelistofsuptechusecasesgroupedbythematicfocusareaisavailableinAppendix2.

1.2.2.Technologiesanddatasciencetoolsinthesupervisorystack

OntheothersideofthetaxonomyinFigure3arethetechnologiesanddatascience

Consumerprotectionandmarketconduct

supervision(nowreferredtoasconsumer

protection):Suptechempowersfinancial

authoritiestoenhancedatacollection(for

example,advanced/real-timemonitoring

anddataconsolidation)andimprovedata

analyticstomonitorconsumerrisksand

supervisemarketconduct(forexample,

assisted/automatedexamination,

misconductdetection,peer-group/risk

classificationandtextanalytics).Inaddition,

theseusecasesalsosupportauthoritiesin

providingconsumerswithvirtualassistance

(forexample,complaintshandlingand

creditbureaurectification).

Cyberrisksupervision:Suptechimproves

dataanalyticstomonitorinstitutions’

complianceandcyberriskmanagement

(forexample,automatedexamination,

assessmentofvulnerabilitiesand

compliancemonitoring).

Digitalassetssupervision:Suptechis

deployedtosupervisecryptoassetsorDLT-

basedprotocols,platformsorsystems(for

example,cross-jurisdictionalintelligence

checksandinformation-sharingcapacity,

embeddedsupervisionandon-chain

analysis).

toolsdeployedtoaddressauthorities’challengesandrealisetheaspirationswithintheaforementioneds