2026香港银行业量子准备度研究报告

QuantumPreparednessofHongKong’s

BankingSector

July2026

Contents

Forewordp.3

ExecutiveSummaryp.4

01QuantumComputingp.6

02Post-QuantumCryptographyp.13

03CurrentHongKongLandscapep.22

04WayForwardp.40

05Appendixp.50

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ForewordWayForwardAppendix

Foreword

Thefinancialservicesindustryisenteringanewphaseoftechnologicaltransformation.Advancesindata,computingpowerandartificialintelligencearereshapinghowfinancialservicesaredelivered,managed,andsupervised.ForHongKongtomaintainitsstatusasaninternationalfinancialcentre,itmustnotonlyembracenewtechnologiesbutalsodevelopthecapacitytomanagetherisksthatmayaccompanytheiradoption.

Quantumcomputingrepresentsadevelopmentofstrategicsignificance.Althoughthetechnologyremainsinanevolvingstage,itslong-termimplicationsforfinancialservicesareprofound.Ononehand,quantumcomputingmayeventuallyunlocknewpossibilitiesinriskanalysis,modellingandoptimisation.Ontheotherhand,itmayalsounderminethecryptographicfoundationsthatunderpintrustandsecurityinbankingsystems,paymentnetworks,andfinancialmarketinfrastructure(FMI).

Thebankingsectormustthereforeapproachquantumdevelopmentswithbothstrategicforesightanddisciplinedexecution.Theimplicationsofthequantumeraextendbeyondfuturetechnologicalopportunities.Theyencompassoperationalresilience,cybersecurity,third-partydependencies,andlong-termtransitionplanning.Inparticular,theshifttoPost-QuantumCryptography(PQC)willrequiresustainedeffortovermanyyears,giventhedeepintegrationofcryptographicfunctionsacrosssystems,processes,andexternalinterfaces.

TheHongKongMonetaryAuthority(HKMA)hasidentifiedthisasakeyprioritywithinHongKong’sbroaderfintechagenda.Under“Fintech2030”1,oneofthestrategicobjectivesistostrengthenbusiness,technology,andquantumresilience.Thisunderscoresaclearintent:to

supportresponsibleinnovationwhilesafeguardingtheresilience,integrity,andtrustthatarefundamentaltothebankingsystem.Inpreparationforthequantumera,theHKMA’sapproachistoencouragetheindustrytobeginearly,actinanorderlyfashion,andbuildthecapabilitiesnecessarytonavigatethetransitionahead.

Quantumpreparednessisnotmerelyatechnicalchallenge.Itdemandsseniormanagementengagement,institutionalplanning,capabilitydevelopment,andcoordinatedactionacrosstheecosystem.ItalsocallsforcollaborationamongAuthorizedInstitutions(AIs),technologyproviders,academicinstitutions,andotherrelevantstakeholders.Awell-preparedbankingsectorwillbebetterequippedtomanagequantum-relatedriskswhileremainingpoisedtoharnessthebenefitsoftechnologicaladvancementovertime.

TheHKMAwillcontinuetosupporttheindustrythroughpracticalguidance,activeengagement,andcapacity-buildinginitiatives.Asthelandscapeevolves,theobjectiveremainstopromoteameasured,forward-looking,andcoordinatedapproachtoquantumpreparednessacrossthebankingsector.

Preparingforthequantumeraisasharedresponsibility.Itrequiressustainedcommitmentandclosecollaborationacrosstheentirefinancialecosystem.Byactingearlyandworkingtogether,wecanenhanceHongKong’sreadinessforthefutureandsupportthecontinuedevolutionofaresilient,trusted,andinnovativefinancialsystem.Asinnovationaccelerates,resilienceandtrustmustkeeppace.ThatishowHongKongwillremainfuture-readyinthenextphaseoffinancialtransformation.

1HKMA.2025.TheHKMAUnveils“Fintech2030”attheHongKongFinTechWeek2025.(

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ExecutiveSummary

Quantumcomputingrepresentsasignificantadvancementincomputingtechnologywithtransformativepotentialforthefinancialservicessector,particularlyinareassuchasportfoliooptimisation,riskmodelling,frauddetection,productpricing,stresstestingandcomplexsimulation.Concurrently,theemergenceofCryptographicallyRelevantQuantumComputers(CRQC)posesapotentiallysignificantcyberrisktothetraditionalcryptographythatsafeguardssecurecommunications,customerdata,payments,authenticationandFMI.Althoughthetimingofthisthreatremainsuncertain,themigrationtoPQCisexpectedtobeamulti-yeareffort.Earlypreparationisthereforeessentialtoaddressboththeoperationalcomplexityofmigratinginterconnectedsystemsandthe“HarvestNow,DecryptLater”(HNDL)risktolong-livedconfidentialdata.

ToassessthecurrentstateofreadinesswithinHongKong’sbankingsector,theHKMAinvitedallAIsoperatinginHongKongtoparticipateinasurvey.Thefindingsrevealthatwhileawarenessofquantumcomputingisgrowing,practicaladoptionremainslimited.MostAIspossessatleastsomeawarenessofquantumcomputing,andasmallergrouphasbegunexploringorpilotingapplications.However,adoptionisstillinitsearlystage,withmanyAIsidentifyingthetechnology’slowimplementationreadinessgivenitsnascentnature,uncertaincommercialvalueandalackofinternalexpertiseaskeychallenges.Therefore,quantumcomputingisgenerallyperceivedasalong-termstrategicopportunity.However,quantum-relatedcyberriskandPQCreadinessdemandimmediateattention.

AssessmentofPQCreadinessacrossthedimensionsofAwareness,Planning,PilotsandPracticalPreparednessindicatesthatthesectorremainsatanearlystageoftransition.AcrossthemajorityofAIs,formalgovernance,dedicatedfunding,workforcetraining,quantum-riskassessments,cryptographicinventories,migrationplanning,testingprotocolsandprogressmonitoringare

notyetfullyestablished.AsmallbutnotablegroupofAIshasmademoreadvancedprogress,includingformalgovernanceframeworks,structuredplanning,pilotactivityandmorematureoperationalpractices.Nonetheless,theoveralllandscapereflectsunevenreadiness,withacleargapbetweenleadinginstitutionsandthebroadersector.

AIshaveidentifiedseveralcommonbarrierstoadvancingPQCreadiness.Theseincludetheabsenceofestablishedriskassessmentmethodologiesandindustry-standardframeworks,thetechnicalcomplexityandscaleinvolvedinbuildingcryptographicinventories,legacyinfrastructureandaccumulatedtechnicaldebt,uncertaintyaroundstandardsandregulatorytimelines,andashortageofinternalexpertise.Externaldependenciesfurthercomplicateprogress.AIsoftenrelyoninputfromvendors,FMIs,commonutilityprovidersandcounterpartiestoassessrisks,understandembeddedcryptography,definemigrationpathwaysandcoordinateinteroperabilitytesting.ThesedependenciesunderscorethatPQCreadinesscannotbeachievedinisolationbyindividualinstitutions.

ThispaperoutlinesapracticalactionplanforAIsadoptingthesamefour-stageapproach:fromAwareness,Planning,PilottoPracticalPreparedness.AIsmaybeginbyestablishingboardandseniormanagementengagement,assigningclearownership,buildingworkforcecapability,developingacryptographicinventory,assessingquantum-relatedexposure,prioritisingmigrationbasedondatasensitivityandsystemcriticality,engagingvendors,andestablishingadocumentedroadmap.Subsequently,controlledpilotscanbeconductedtovalidateinteroperabilityandrollbackmechanisms,whileembeddingPQCreadinessintobusiness-as-usual(BAU)processes,suchascyberriskmanagement,operationalresilience,third-partyriskmanagementandchangegovernance.

Thepaperalsoidentifiesareaswhereexternalsupportcanacceleratesector-widereadiness.AIshaveexpressed

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strongdemandforsupervisoryclarity,practicalguidance,industryknowledgesharingandfacilitatedtestingenvironments.Inresponse,theHKMAwillsupportthesectorthroughinitiativessuchasprovidingsupervisoryguidance,trainingandworkshops,developingPQCtoolkitsincollaborationwithacademicpartners,andfacilitatingindustrycollaborationandengagementthrough

platformsincludingHongKongFinTechWeek,FiNETecheventsandothertargetedforums.TheseeffortsaimtohelpAIstranslatePQCconceptsintotangibleactions,promoteconsistencyacrossthesectorandencouragecoordinatedengagementwithvendorsandotherexternalstakeholders.

Intheimmediateterm,AIscantakeseveralpracticalstepstoadvancetheirPQCreadiness.

Engagetheboard,framingquantumriskasanenterpriseriskandestablishingitasastandingiteminriskgovernance

Identifyanaccountableownerforquantumreadiness,withseniorsponsorshipandamandatethatcrossesfunctionallines

Commissionacryptographicinventory,acceptingthatitwillbeimperfectatfirstandimprovewithiteration

Engagecriticalvendors,requestingtheirpost-quantumroadmapsandembeddingquantumreadinessrequirementsinnewcontracts

TheseactionsdonotrequireAIstowaitforfullmaturityinquantumtechnologyorfinalisedPQCimplementationguidance,andcanlayastrongerfoundationforsubsequentplanning,pilotingandmigrationefforts.

TheQuantumPreparednessIndexshowsthatbuildingupontheinitialfoundations,thenextstageofthetransitionjourneywillrequirestrongercapabilitydevelopment,morestructuredplanning,andgreaterprogressintestingandimplementation.Thetransitiontoquantum-safebankingwillrequiresustainedcommitmentoveranumberof

years.Byactingnow,buildingfoundationalvisibility,developingcryptographicagility,conductingearlytestingandcoordinatingacrosstheecosystem,AIsinHongKongcanenhancecustomertrust,strengthenoperationalresilienceandupholdfinancialstabilityintheemergingquantumera.

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01

QuantumComputing

1.1IntroductiontoQuantumComputing

Todaywearefamiliarwiththeconceptofmachinesthatcompute.Thesemachines,calledclassicalcomputers,taketheshapeoflaptops,phones,watchesandotherdigitaldevices.Attheheartofeachofthesemachinesaresemiconductordevicesthatarecommonlybuiltonsiliconandprovidethemicroscopicswitchesandcircuitsthatenablecomputation.Overthelast60years,assiliconmanufacturingtechnologieshavedeveloped,thesecomputingdeviceshaveshrunkinsizeandincreasedincapability,deliveringmorecomputationalpowerinasmallerpackage.

Meanwhile,intheearly1980s,thefoundationaltheoriesofquantumcomputationwerebeingestablishedthroughtheindependentworksofphysicistsPaulBenioff,RichardFeynmanandDavidDeutsch,whoproposedquantummechanicalmodelsofcomputationthatcouldbeusedtosimulatequantumsystemsandprocessmultiplecomputationalstatesatthesametime.

Thefurtherdevelopmentoftheseideasandthephysicaldevelopmentofmaterials,oftenusingtheadvancedmanufacturingcapabilitiesfromthesemiconductorandphotonicsindustries,hasledtotheimplementationoftheseconceptsatanatomicscale.Hardwaresupplierscannowdesignandbuildnewcomputingarchitectureswherequantummechanicsareattheheartoftheiroperation.

Overtime,quantumcomputersareexpectedtohelpsolvecertainclassesofproblemsthataredifficultfortoday’slargestclassicalsupercomputers.Whileclassicalcomputersstoreinformationasbits,whichcanbeunderstoodasbeinginoneoftwostates,quantumcomputersencodeinformationusingqubits.Qubitscan

representacombinationofstatesuntiltheyaremeasured,apropertyknowninquantumphysicsassuperposition.

Inadditiontosuperposition,anotherquantummechanicalpropertyusedinquantumcomputationisentanglement.Thisistheabilitytoconnectdifferentqubitssuchthattheycanincreasetheprobabilityofcorrectsolutionsbeingoutput.Thisisimportantbecause,whileforclassicalcomputersthataredeterministic,whereagivencalculationtypicallyproducesthesameoutputforthesameinput,quantumcomputingisprobabilistic.Thismeansthatthesamequantumcomputationcanproducedifferentresults,andeachresultisoutputwithacertainprobability.

Thesepropertiesofsuperpositionandentanglementallowquantumcomputerstorepresentandmanipulateinformationinwaysthatdifferfundamentallyfromclassicalcomputing.Forcertaincomputationaltasks,manyresearchersbelievethatsufficientlylarge-scalequantumcomputersmayeventuallyoutperformclassical

computers.2

Forfinancialservices,quantumcomputersareexpectedtoofferpotentialbenefitsovertime,includingmoreaccuratesimulationsofmarkets,betteroptimisationofassetuseandenhancedanalyticalcapabilitiesinareassuchasfrauddetection.However,asignificantriskassociatedwithquantumcomputersistheirtheoreticalcapabilitytobreakcommonencryptionmethods.Section2providesmoredetailsonquantumcyberriskandPQC.

1.2QuantumUseCasesforFinancialServices

Thefinancialservicesindustryisahighlydata-drivenindustrywherespeed,accuracyandmanagementofrisk

2NielsenandChuang.2010.QuantumComputationandQuantumInformation.p.5.(

/10.1017/CBO9780511976667

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arekeytosuccess.Tosupportdecisionmaking,complexmathematicalmodelsareused.Thesemodelsarelimitedbycurrentclassicalapproaches.Evenwiththeverybesthigh-performancecomputinghardwareavailable,thesemodelsarecomputationallydemandingandcantakeverylongprocessingtimes.

However,quantumcomputersprovideafundamentallydifferentwayofsolvingtheseproblems,whichisnotconstrainedbythesameclassicallimitations.Quantumapproaches,usingsuperpositionandentanglement,willsupportnewapproachestocomplexmathematicalmodelsandmayenablesolutionstobefoundfasteratpotentiallyhigherquality.Itisprojectedthatsolvinghigh-value

financialproblemswithquantumcomputersmaygeneratesignificanteconomicvalueforfinancialservices.3

Globalfinancialinstitutionsarealreadyexploringquantumcomputingusecases,oftenincollaborationwithtechnologyconsultingfirmsandresearchpartners.Theseexperimentsarefocusedonexploringhowquantumapproachesmayeventuallyofferabenefittothequalityofthesolutions,thespeedinwhichtheyarefoundandtheskillsrequiredtousethistechnology.Theimplementationmaturityofquantumalgorithmsinfinancialinstitutionsvaries,withmostapplicationsattheexploratoryorpilotstage.

3McKinsey&Company.2026.McKinseyQuantumTechnologyMonitor2026:Acommercialtippingpoint.p.24.

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PortfolioandAssetOptimisation

Portfolioandassetoptimisationisacommonprobleminfinance,whichinvolvesmakingthebestuseofassetstomaximisereturns.Optimisationtechniquesmustconsiderexpectedreturnsofassets,financialrisks,marketconditions,physicalconsiderationsandmanyotherfactors.

QuantumAlgorithmAreas

Optimisationandmachinelearning

Implementation

Assetoptimisationusingquantumcomputingcanusequbitstorepresentspecificasset-allocationdecisions,suchaswhetheranassetshouldbeincludedinaportfolio.OptimisationtechniquessuchastheQuantumApproximateOptimisationAlgorithm(QAOA)canthenconsiderfactorsincludingassetvalue,expectedreturn,marketconditionsandrisklevels.Basedontheseinputs,QAOAcangenerateasetofpotentiallyfavourableasset-allocationoptions.

Quantummachinelearning(QML)methods,suchasquantumneuralnetworks(QNNs),mayalsoimproveestimatesofassetvalueandrisk,therebyprovidingbetterinputstooptimisationmodels.

CaseStudies

CitiInnovationLabs(Citi)conductedastudywithClassiqin2024totestquantumcomputingforportfoliooptimisation.Usinghistoricaldataforsixstocks,theyencodedarisk-returnoptimisationforQAOAandenforcedthebudgetconstraintviaatuneable“penaltyfactor”,thenvariedthatpenaltyacrosssimulatorruns.Resultsprovedhighlysensitivetopenaltycalibration,andsmallerpenaltiesyieldedthebest-qualitysolutions.Thestudyclaimsnoquantumadvantageoverclassicalmethods,butestablishesthetuningdisciplineneededtorealiseoneashardwarematures.4

HuaxiaBank,jointlywithSpinQ,developedaQNNfortheoptimisationofATMplacementandwithdrawalofunderusedmachinesacrossChina.Theteamextractedkeydatapointsincludingfailurerates,usagetrendsandreplenishmenttimingsfrom2,243ATMs.Thedatawasthenconvertedusingatechniquecalledvariationalquantumembedding,whichencodesdataintoaformatsuitablefortheQNN.TheQNNwasexecutedonSpinQ'sproprietarynuclearmagneticquantumcomputertoprovideexperimentalresults.Theapproachshowedimprovedaccuracy,higherprecisionandshortercomputingtimecomparedtothecurrentclassicalalgorithm.5

4AWSQuantumTechnologiesBlog.2024.CitiandClassiqadvancequantumsolutionsforportfoliooptimizationusingAmazonBraket.

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5SpinQ.2025.HuaxiaBankPartnerswithSpinQtoDevelopQuantumAIModelsforSmarterCommercialBankingDecisions.(

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FraudDetection

Frauddetectionseekstoidentifypotentiallyillegitimatetransactionsbyrecognisingpatternsindata.Oncesuchtransactionsareidentified,financialinstitutionscantakestepstoreverse,preventormitigatetheirimpact.

CaseStudies

QuantumAlgorithmAreas

Machinelearning

Implementation

QMLmethodsmayallowforalargernumberoffeaturesandmorecomplexrelationshipswithinfinancialtransactiondatatobeevaluatedtodetectpatternsoffraud.

PingAnInsurancecollaboratedwithOriginQuantumtodevelopQMLalgorithmsthatcouldbeusedtoidentifyfinancialfraud.TheteamdevelopedaQNNtodetectcomplexpatternsoftransactionsindicativeofmoneylaundering.ThesequantumalgorithmsareintendedtosupportimprovementsintheresponsespeedoffinancialservicesinPingAn.6

SalesOptimisation

Accuratelypricingassetsincomplexmarketsisachallengingtask.Fasterormorepreciseinsightsintoanasset’sfuturepricecansupportfinancialdecision-makingacrossareassuchastradingstrategyoptimisation,arbitrageandhedging.

QuantumAlgorithmAreas

HSBCworkedalongsideIBMtodeliverexperimentalresultsshowinga34%improvementinpredictingtheprobabilityofwinningcustomerinquiriesintheEuropeancorporatebondmarket.HSBCusedquantumdataembeddingtotrainaclassicalmachinelearningmodel.Thisclassicalmachinelearningmodelthencalculatedthelikelihoodofwinningeachcustomerinquiry,informingalargerclassicaltradingalgorithm.7

Machinelearningandsimulation

Implementation

QMLcanbeemployedtohelpmakepredictionsaboutthefuturestateofthemarket.Quantumsimulationtechniquescanalsobeusedtoreplicatethemarket’scomplexinteractionsusingaquantumstatetoprojectanexpectedassetprice.

CaseStudies

6HongKongInstituteofBankers.2025.TheQuantumTectonicShift:DigitallyRewiringtheBankingModel.BankingToday.p.5–6.

(

/storage/files/243/BT145%20Cover%20Story.pdf

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7HSBC.2025.HSBCDemonstratesWorld’sFirst-knownQuantum-enabledAlgorithmicTradingwithIBM.(

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RiskManagement

Riskmanagementiscriticaltotheeffectiveoperationoffinancialservices.Intransactionclearing,riskmayarisewhentradersareabletousefundsbeforetheirtransactionshavebeenfullycleared.Financialservicesorganisationsmustalsomatchandprocesstensofthousandsoftrades,oftenthroughqueue-likesystems.Toreducethisrisk,itisimportantthattradesareverifiedandclearedwithinashorttimeframe.

CaseStudies

QuantumAlgorithmAreas

Optimisation,simulationandmachinelearning

Implementation

Toreducetheriskintradescheduling,avariationalquantumoptimisationtechniquesuchasQAOA,canbeusedtoquicklyfindthebestpairsoftrades.Simulationmethodscanbeusedtoidentifyriskinacomplexmarket,whilemachinelearningtechniquescanbeusedtopredicttradesettlementfailures.

Barclaysdemonstratedaproof-of-concept(PoC)foraquantumclearingalgorithmdesignedtoensuretheintegrityoftrades