2019 FinAccess - CBK€¦ · 3 USAGe of finAnCiAL SeRViCeS AnD PRoDUCtS 3.1 Financial services...
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Access | UsAge | QUAlity | impAct
A P R I L 2 0 1 9
2019 FinAccess HouseHold survey
Every effort has been made to provide complete and accurate information. However, CBK, KNBS, FSD Kenya make no claims, promises or guarantees about the accuracy, completeness or adequacy of the contents of this report and expressly disclaim liability for error and omission in the contents of this report.
CENTRAL BANK OF KENYA
© finacess, 2019
Access | UsAge | QUAlity | impAct
2019 FINACCess HouseHold survey
2019 FinAccess Household Survey i
TABLE OF CONTENTS
Definition of teRMS & ABBReViAtionS iifoReWoRD ivACKnoWLeDGMent vii 1 intRoDUCtion1.1 Economic context 11.2 Survey objectives 21.3 Survey methodology 21.4 Survey demographics 5
2 ACCeSS to finAnCiAL SeRViCeS AnD PRoDUCtS2.1 Accesstofinancialservices 62.2 Accesstofinancialservicesandproducts, 8
2006-20192.3 Accesstofinancialservicesacrossdifferent 9
segments of the population
3 USAGe of finAnCiAL SeRViCeS AnD PRoDUCtS 3.1 Financial services usage by institution 143.2 Frequencyinusageoffinancialservices 16
by institution 3.3 Useoffinancialserviceproviders
by demographics 17
3.4 Driversofusage 183.5 Financialservicesbywealthquintile 193.6 Digitalactivityinusage 203.7 Useofaportfoliooffinancialserviceproviders 213.8 Financialservicesusagebyproducts 21 4 finAnCiAL ReLeVAnCe4.1 Thebiggestpriority 394.2 TheNeeds-basedFramework 404.3 Selectionofsolutionsforafinancialneed 474.4 Meetingneedsforbusinessandagriculture 48
5 finAnCiAL HeALtH AnD LiVeLiHooDS 5.1 Financial health by categories 545.2 Financial status perceptions 55
6 ConSUMeR PRoteCtion AnD finAnCiAL LiteRACY 6.1 Financialliteracy 576.2 Knowledgeoncostofborrowing 596.3 Knowledgeoftransactioncosts 606.4 Perceptionsonbetting 606.5 Consumerprotection 62
7 SUMMARY AnD ConCLUSionS 65
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Abbreviation/concept Definition
AFC Agricultural Finance Corporation
ASCA Accumulating Savings and Credit Association
ATM Automated Teller Machine
Basic phone CANNOT access internet, CANNOT send and receive email, does NOT have a camera/radio/media player
CBK Central Bank of Kenya
Chama Informal group
CMA Capital Markets Authority
CRB Credit Reference Bureau
DFI Development Finance Institution
DFS Digital financial service
DT–Sacco Deposit Taking SACCO
EA Enumeration Area
Equitel A mobile app and Mobile phone–based banking services by Equity Bank Limited
Feature phone CAN access internet, CAN send and receive email, has a camera/radio/media player, CANNOT download and install applications on the phone
Financial needs based framework
The Financial Needs framework based on Insight to Impact’s (i2i) pioneering methodology, which measures the extent to which financial devices are being used to meet people’s financial needs
FSD Kenya Financial Sector Deepening Trust Kenya
HELB Higher Education Loans Board
i2i Insight to impact
ICDC Industrial and Commercial Development Corporation
In kind Refers to payment in form of a service or product but not in cash
Income earner Individual who has work and/or investments that provide a defined income stream on a regular basis
IPA Innovations for Poverty Action
IRA Insurance Regulatory Authority
JLB Joint Loans Board
Definition of teRMS AnD ABBReViAtionS
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Abbreviation/concept Definition
KDIC Kenya Deposit Insurance Corporation
KIE Kenya Industrial Estate
KISH Sampling method for randomly selecting an individual in the household
KNBS Kenya National Bureau of Statistics
KSh Kenya Shilling
KYC Know Your Customer
Merry–go–round A group in which the members contribute a fixed amount for a fixed duration, and each member is paid the entirety of the collected money on a rotating schedule
MFB Microfinance bank
MFI Microfinance Institution
MNO Mobile Network OperatorMobile Money /Digital Apps
Financial services provided through mobile phone–based software applications such as BRANCH, TALA, etc.
Mobile phone banking
Mobile phone–based banking services and products by commercial banks such as Timiza, HF Whizz, M-Coop Cash, M-Shwari, Eazzy loan, and T-Kash.
Mobile money Mobile phone financial services or simply mobile money offered by MNO
MTP Kenya Vision 2030 Medium Term Plan
NASSEP National Sample Survey and Evaluation Programme
NHIF National Hospital Insurance Fund
NSE Nairobi Securities Exchange
NSSF National Social Security Fund
POS Point of Sale Device
Poverty Probability Index (PPI)
A poverty measurement tool designed by IPA, which uses 10 questions about a household’s characteristics and asset ownership which are scored to compute the likelihood that the household is living below the poverty line.
QTC Questionnaire Technical Committee
RBA Retirement Benefits Authority
ROSCA Rotating and Savings Credit Associations
SACCO Savings and Credit Co–operative
SASRA Sacco Societies Regulatory Authority
Smart phone A phone that CAN download and install applications
UNYMC United Nations International Year of Microcredit
Wealth quintileEach household respondent is given an affluence score based on household assets. The population is equally divided into groups (quintiles) and each respondent is placed in their corresponding quintile based on the level of affluence/ social strata
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itgivesusgreatpleasuretopresenttoourstakeholdersthe Financial Access (FinAccess) Household Survey 2019. Since 2006, FinAccess surveys have beenestablished as the leading source of reliable data
onfinancialaccessandusage inKenya,andiswidelyrelied on by the media, Government, researchersanddevelopmentpartners.The2019Survey seeks toimproveonthistrackrecordbyprovidinginformationbeyond the conventional measures of access and usage. It provides new information on the quality and impact dimensions, examining financial health andlivelihoods, consumer protection, financial literacyin addition to probing more deeply on the frequency of usage. The survey further includes independent business and agriculture modules to better understand usageof financialproductsand serviceswithin theselivelihoods, crucial for the development of an all-inclusivefinancialecosystemforallKenyans.
Measurement of financial inclusion in Kenyacommencedin2006throughthecreationofFinAccesssurveys implemented over the years by the CentralBankKenya(CBK),KenyaNationalBureauofStatistics(KNBS) and Financial Sector Deepening (FSD) Kenya.GiventhefastpaceoffinancialsectordevelopmentinKenya, theFinAccessSurveyconstitutesan importanttool for monitoring financial inclusion trends anddynamics, thus informing policy and industry onprogress towards pro-poor and pro-growth financialsector development. Both the Central Bank of KenyaandTheNationalTreasuryandPlanninghavereliedonFinAccess data to inform the development of policies thatsupport inclusion.These includeagencybankingand national payments regulations as well as initiatives to improve transparency in the sector. Data generated from these surveys is also widely used by the private sector,developmentpartnersandresearchers.
foReWoRD
dr. Patrick Njoroge governor, cBK
Zachary Mwangi Chege Director general, KNBs
dr. david Ferrand Director, FsD Kenya
2019 FinAccess Household Survey v
The 2019 Survey was jointly conducted by KNBS, CBKand FSD Kenya. The Statistics Act, 2006 is the legalframework under which these surveys are conducted. Theimplementation of 2019 FinAccess Survey followed the setstatistical methodological standards of conducting surveys that promote best practices in the production cycle of survey planninganddesign,datacollection,analysisandreporting.The survey targeted individuals aged 16 years and above,fromscientificallyselectedhouseholds,designedtoprovideestimates at the national and regional level and by residence (rural and urban areas). The household sample selection was drawnfromthefifthNationalSampleSurveyandEvaluationProgramme (NASSEP V) household sampling frame. KNBSgives assurances that the survey results are sound and will provide useful insights in making informed decisions onfinancialdeepeningandgreaterinclusionacrossthecountry.We, therefore, encourage all to use the data to promoteevidence-baseddecisionmaking.
The2019surveyfindingsclearlyshowthatKenya’sfinancialinclusion landscape has undergone a transformation since 2006. Formal financial inclusion has risen to 82.9 percent,up from 26.7 percent in 2006, while complete exclusionhas narrowed to 11.0 percent from 41.3 percent in 2006.Furthermore, the disparities in financial access betweenrichandpoor,menandwomen,andruralandurbanareashavealsodeclinedremarkably.Keydriversofthesechangesinclude:thegrowthofmobilemoney,governmentinitiativesand support, and developments in information andcommunicationstechnology(ICT).Thesignificantreductionin the proportion of the adult population totally excluded fromfinancialservicesandproductsvindicatesthepolicies,strategies and reforms undertaken by the government aswell as the widespread adoption of digital technology and innovationsbyfinancialsectorplayers.Thesehavehelpedin
deepeningfinancialinclusionbyenablingthepopulationtoovercome infrastructural constraints to access especially in rural areas.
Despitetheprogressmadesofar,affordabilityandconsumerprotection issues such as unexpected charges remain barriers to formal service access. Even more notable is the considerable modesty of the developmental impact of formal financial access. Many Kenyans have formalaccounts in various forms, but these accounts are rarelyusedbecausetheyarenotsolvingrealday-to-dayproblemsfor many households, smaller andmicro scale businessesand farmers. Considerable reliance remains on the use ofinformal instruments – clearly demonstrated through the needs-basedframework,aninnovationinthe2019FinAccesssurvey questionnaire.
The survey results will help unravel the constraints that still impede financial inclusion and foster the design of policymeasures, products and delivery channels that match thepopulation needs. Existing literature has demonstrated that demand for financial servicesandproducts from thepoor,low-incomehouseholds,micro-andsmall-scalebusinessesand farmers grow when the financial service providersunderstand what each population segment uses and values. It is only through good understanding of the needs of stakeholders,thatservicesandproductscanbemademoreaffordable,convenient,flexible,reliable,safeandsustainableto support the development of a more inclusive financialecosystemforallKenyans.Inaddition,giventhesignificanceofthedatafromFinAccesssurveys,itisourhopethatmoreprivatesectorplayerswilljointheCBK,KNBSandFSDKenyain supporting future surveys.We thank Airtel Kenya, KenyaPostOfficeSavingsBank,DiamondTrustBank(DTB)andNICbankforfinanciallysupportingthe2019survey.
dr. Patrick Njorogegovernor, central Bank of Kenya
Mr. Zachary Mwangi ChegeDirector general, Kenya National Bureau of statistics
dr. david FerrandDirector, Financial sector Deepening trust- Kenya
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communicating information and insights to support evidence based decision making that improves the value of financial services for Kenyans
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This survey was made possible through the public-private partnership collaborativeefforts of the Kenya National Bureau ofStatistics(KNBS),FinancialSectorDeepening
Trust (FSD) Kenya and the Central Bank of Kenya(CBK) with funding contribution from Airtel KenyaLimited, Kenya Post Office Savings Bank, NIC Bankand Diamond Trust Bank. We take this opportunityto thank the leadership of the three institutions,namely Dr Patrick Njoroge, Governor andMs SheilaM’Mbijjewe,DeputyGovernoroftheCBK,MrZacharyMwangi, DirectorGeneral of theKNBSandDrDavidFerrand, Director of FSD Kenya for their direction,stewardship,guidanceandunwaveringsupport.
We also thank the Financial Access Management(FAM) Team comprising Mr Raphael Otieno, ActingDirector of the Research Department at the CBKsupportedbyMrDanielK.A.Tallam,AssistantDirector,Financial Sector Analysis Division in the Department; Mr Collins Omondi, Director of MacroeconomicStatistics,KNBS;andDrAmrikHeyer,HeadofResearch(FSD Kenya) for providing invaluable support andguidance in planning and conducting the survey. Overallco-ordinationwas ledbyDr IsaacMwangiofCBKsupportedbyMr.WilliamEtwasiofKNBSandMs.GeraldineMakundaofFSDKenya. Immensesupport
wasprovidedthroughoutthesurveybystafffromthethreepartner institutions,namely:CBK (MrCappitusChirongaandMs.MariaN.Ng’ethe),KNBS(BenjaminAvusevwa, John Bore, Mutua Kakinyi, Paul Samoei,PaulWaweru,PeterKamau,SamuelKipruto,TabithaWambuiandZacharyOchola)andFSDKenya (PeterGakure).
The Team was supported by Mr Amos Odero, Mr.DavidTaylor,Mr.PaulGubbinsandMs.CarolMatikoconsultantswithFSDKenya,andtheCommunicationteam comprising of Mr Wallace Kantai and ChrisMwangi of CBK Communications Office as well asWinnieMokayaandConradKarumeofFSDKenya,andTrizerMwanyika of KNBSwhodedicatedly designedthe layout of the report and provided media support. Wetakethisopportunitytoalsorecogniseandthankallother persons who in one way or another contributed tothissurveyincludingofficersfromthethreepartnerinstitutionsinvolvedinthefieldwork,administrativeand logisticalcoordination.Lastly,special thanksgotoIpsosKenya,insighttoimpact(i2i)andInnovationsforPovertyAction(IPA)forprovidingadvisoryinputindesigning and incorporating new concepts into the questionnaire.
Asanteni Sana!
ACKnoWLeDGeMent
viii 2019 FinAccess Survey
Working towards the development of an inclusive financial ecosystem for all Kenyans
2019 FinAccess Household Survey 1
This Financial Access (dubbed FinAccess) Household Survey 2019 is the fifth in a series of surveys that measure and track developments and dynamics in the financial inclusion landscape in Kenya from the demand–side. This follows the successful rollout of the 2006 baseline survey, and the subsequent FinAccess surveys of 2009, 2013 and 2016.
The surveys constitute an important tool for providing better measurement and understanding of the financial inclusionlandscape in four dimensions – Access, Usage, Quality and Impact/ Welfare. This is in line with Kenya’s Vision 2030 financial sectordevelopment agenda outlined in the Medium –TermPlan(MTP)III.
This Survey was conducted through a public-private sector partnership comprising the CentralBankofKenya(CBK),theKenyaNationalBureauofStatistics(KNBS)andFinancialSectorDeepening Kenya (FSD Kenya) with fundingsupport from Airtel Kenya Limited, Kenya PostOffice Savings Bank (Postbank), Diamond TrustBank(DTB)andNICBank.
01
intRoDUCtion
The survey introduced new perspectives on measurement of financial inclusion by taking into consideration the improvedusage dimension, needs based approach, and emerginginnovations, while maintaining time series to track progresssince2006.
This chapter provides the survey rationale, approach andmethodology,dataprocessinganddissemination,andsurveydemographics as outlined below.
1.1 economic context
The Kenyan economy remained strong and expanded at anaverageof6percentinthefirstthreequartersof2018comparedto 4.7 percent in the first three quarters of 2017. Inflationhas remained within the CBK target range of 2.5-7.5 percentthroughout 2018, reaching a 5-year low of 3.7 percent in April2018andthenincreasingmoderatelyinthesecondhalfof2018to an average of 5 percent.
During 2018, CBK decreased its policy rate two times from10 percent in January 2018 to 9.5 percent inMarch then to 9percent inJuly2018,andwasretainedat that level for therestof the year. Following the introduction of interest rate controls
Survey objectives
� Strengthen financial inclusion measurement using demand–side data.
� provide indicators that track progress and dynamics of the financial inclusion landscape in Kenya.
� provide data to stakeholders including policy makers, private sector players and researchers.
2 2019 FinAccess Household Survey
in2016,theFinanceAct2018inSeptember2018amendedtheBankingActtoremovetheminimuminterestonsavings,whichwaspreviouslysetat70percentof theCentralBankRate(CBR).Thecaponlendingrateswashoweverretainedatamaximumof4percentagepointsaboveCBR,restrictingcommercialbanks’lendingratetoamaximumof13percent.
1.2 survey objectives
The survey objectives were to:
� Strengthenfinancialinclusionmeasurementusingdemand–side data;
� ProvideindicatorsthattrackprogressanddynamicsofthefinancialinclusionlandscapeinKenya;and
� Providedatatostakeholdersincludingpolicymakers,private sector players and researchers.
Sincethe2006baselinesurvey,Kenyahasmadesignificantprogressinfosteringfinancialinclusion.Thereportpresentsthe survey methodology and key findings to the public.The stakeholders will find the report useful in providinginformation on – Access, Usage, Quality and Impact – to support evidence–based decision making and financialservices sector development that improves the value of financial services and products for all Kenyans. Additionalanalysis will be made available through issue–based reports as we encourage various researchers to write topical research papers. The data will also be disseminated through the KNBS, CBK and FSD Kenya websites and consultativeforawithallstakeholders.
1.3 survey methodology
This2019Surveywashouseholdpopulation–based,targetinghouseholdindividualsaged16yearsandaboveanddesignedtoprovidenational,regionalandresidence(ruralandurbanareas) level estimates. The survey used the fifth NationalSample Survey and Evaluation Programme (NASSEP V)household sampling frame. The frame consists of 5,360clustersandisstratifiedintourbanandruralareaswithineachofthe47countiesresultingin92samplingstratawithNairobiandMombasaCountiesbeingwhollyurban.NASSEPVframewasdesignedinamulti-tieredstructurewithfoursub-samples
(C1,C2,C3andC4)eachconsistingof1,340EnumerationAreas(EAs) that can serve as independent sampling frames. The frameusedCountiesasthefirstlevelstratificationwhichwerefurtherstratifiedintoruralandurbanstrataapartfromNairobiandMombasaCountieswhichareclassifiedasurbanareasonly,resultingin92strata.ThesamplingofEAsintotheframewas done independently within each stratum. Each sampled EA was developed into a cluster through listing and mapping process that standardized them into one measure of size having an average of 100 households (between 50 households and149households). In situationswherea stratumdidnothavesufficientclusters fromthetwosub-samples,theothersub-sampleswereincluded.
1.3.1 survey instrument design
Thesurvey instrument (questionnaire)wasfinalizedby theQuestionnaire Technical Committee (QTC), which drawsmembership from the three partner institutions with co-optedexperts, scripted successfully and signedoffby FAMto pave way for the piloting and commencement of the surveyonOctober1,2018.Thisfollowedseveralconsultativefora with CBK internal departments, FSD Kenya, IpsosSynovate Kenya, KNBS, Capital Markets Authority (CMA),SACCO Societies Regulatory Authority (SASRA), InsuranceRegulatoryAuthority(IRA),andRetirementBenefitsAuthority(RBA). The 2019 survey introduced new perspectives onfinancialinclusionmeasurementincludingimprovedusagedimensions factoring in digital innovations, consumerprotection, financial literacy, and over-indebtedness,etc.; aligned to global financial inclusion indicators; andincorporatingtheneedsbasedapproach,whilemaintainingtimeseriestotrackprogresssince2006.
1.3.2 sampling
Samplingforthe2019Surveyutilizedatwo-stagestratifiedcluster sampling design. This was geared towards providing valid and reliable estimates at national level, regionallevelsandruralandurbanareasseparately.Thefirststageentailedselecting1000clustersfromNASSEPV.Thesecondstage involved random selection of a uniform sample of 11 households (434 in urban and 566 in rural areas) in eachcluster from a roster of households in the cluster using systematic random sampling method.
2019 FinAccess Household Survey 3
KSH
KSH
KS H
The third stage involved selection of the individual at the household level using an inbuilt Computer AidedPersonal Interview (CAPI) KISH grid to select one eligibleindividual(16+years)fromarosterofalleligibleindividualsin the household. All the selections were done without replacement. The data has been weighted back to thepopulation to be representative at both the national level as well as at the regional levels. The distribution of the sample is shown in Table 1.1.
1.3.3 Piloting and scripting of the survey instrument
Pilotingofthesurveyinstrumentwasconductedinselectedcounties covering both rural and urban areas prior to the rollout of the survey across the country. Findings from the pilotexerciseguidedthefinalscriptthatwasusedinthefield.This was done to ensure that there was strict conformity to international standards of surveys and also in ensuring the flow,consistencyandskiproutineswereobserved.
1.3.4 Recruitmentandtrainingoffieldworkpersonnel
AllsurveypersonnelwerecentrallycontractedbytheKNBSon behalf of the three collaborating partner institutions – KNBS,CBKandFSDKenya.Thesurveypersonnelcomprisedof coordinators and supervisors drawn from the three institutions,15ResearchAssistants(RAs)forthepilotexerciseand45RAsforthemainfieldworkdatacollectionexercise.
The recruitment and eventual posting of the research assistants factored in their education and knowledge oflocal language in their areas of posting. This was aimed at increasing the efficiency of delivery of the questionnairethroughverbaltranslations.Intotal,therewere45researchassistants and 15 supervisors. There were two trainings,one for the pilot survey and a subsequent one for the main survey exercise.
Allocation of Clusters Allocation of households
Region (Group of Counties) Rural Urban Total Rural Urban Total
Nairobi na 74 74 na 814 814
North Rift 36 14 50 396 154 550
Central Rift 70 46 116 770 506 1276
South Rift 52 31 83 572 341 913
Nyanza 71 41 112 781 451 1232
Western 64 31 95 704 341 1045
central 70 47 117 770 517 1287
lower eastern 52 32 84 572 352 924
Upper eastern 18 13 31 198 143 341
mid-eastern 51 22 73 561 242 803
coastal Region 45 25 70 495 275 770
North eastern 37 19 56 407 209 616
mombasa na 39 39 na 429 429
Kenya 566 434 1,000 6,226 4,774 11,000
Note: Nairobi and Mombasa counties have only urban areas. na = Not applicable
Table1.1:Sampleallocationforthe2019finaccesshouseholdsurvey
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1.3.5 Fieldwork data collection
DatacollectionemployedthenewtechnologyofCAPIsystemwhichwasdevelopedbyKNBS,asopposedtothetraditionalmethod of Paper Assisted Personal Interview (PAPI). Pilotexercise data collection started on September 9, in selectCounties for a period of 6 days, while the main exercisecommencedonOctober1,2018andendedonDecember15,2018 foraperiodof75continuousworkingdays includingweekendsandpublicholidaysforallfieldteams.
1.3.6 data processing – cleaning and weighting
Weights for the 2019 Survey were computed and appliedto the primary datasets during analysis. This is because data from the survey was not self-weighting since thesample allocation was not proportional to the size of the strata. Additionally, some of the sampled householdsdid not respond to the interviews, while others couldnot be accessed due to various reasons. Accordingly, thesample required weighting adjustments to cater for non-proportional distribution of clusters and non-response, inorder to provide estimates that are representative of target populationatnationalandsub-regionallevels.
The design weights incorporated the probabilities of selection of the clusters from the census EAs database into theNASSEPVsampleframe:theprobabilitiesofselectionofthesurveyclustersfromNASSEPVframe;theprobabilitiesofselection of the households from each of the sampled survey clusters; and the probabilities of selection of an individual among other eligible individuals at the household level. These design weights were then adjusted for individual,household and cluster non-response. Non-response wasadjusted at stratum level. In doing this, the followingmathematical relation was employed:
Whi=Dhi x x x Shi
1hi
Ihij
1Ch
ch
where;
Whi Overallclusterweightforthei-thclusterintheh-thstratum
Dhi Sample cluster design weight obtained from cluster selectionprobabilitiesforthei-thclusterintheh-thstratum
Shi Number of listed households in the i-th cluster intheh-thstratum
lhi Numberofrespondinghouseholdsini-thclusterintheh-thstratum
Ch Numberofclustersinh-thstratum
ch Numberofselectedclustersintheh-thstratum
Ihij Numberoflistedeligibleindividualswithinthej-thhouseholdinthei-thclusterintheh-thstratum
Eventually,theweightswereadjustedtoensureconsistencywith the projected population figures. The weights wereapplied to each individual item to obtain estimates on any givenvariableinaspecifieddomainorcategory.
Table 1.2: survey response rates (%)
ResultResidence
Urban Rural Total
Household interviews
Households Selected 4,774 6,226 11,000
Eligible households 4,148 5,561 9,709
Households interviewed 3,611 5,058 8,669
Household response rate 87.1 91.0 89.3
Thesurveyachievedaresponserateof89percentasshownin Table 1.2. In total, 11,000householdswere selected forthe survey out of which 9,709 were occupied at the timeof the survey. Out of these occupied households, 8,669households responded to the questionnaire representing a responserateof89percentatthenationallevel.Therewasa slight variation in response rates between urban and rural householdsof87percentand91percent,respectively.
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1.4 survey demographics
The survey sample was designed to achieve a statistically valid and reliable nationally representative sample of individuals aged 16 years and above. Unless otherwisestated,thereportfocusesonadultsaged18yearsandabove,whichisthelegalageforobtaininganationalidentification
documentthatformsthemainbasisforKnowYourCustomer(KYC) identificationdocumentusedby all financial serviceproviders comply with KYC. The adult population (18 andabove)comprisedof92.4percent (25,104,967people).The16to17yearolds total7.5percent (2,040,042people).Thesurvey demographics are broken down as indicated inFigure 1.1 and Table 1.3.
Figure 1.1: demographics
Therestofthereportisorganizedasfollows:ChapterTwopresentsAccesstoFinancialServicesandProducts;ChapterThree–UsageofFinancialservicesandProducts;ChapterFour–FinancialRelevance;ChapterFive–FinancialHealthandLivelihoods;ChapterSix–ConsumerProtectionandFinancialLiteracy;andlastlyChapterSeven–providesaSummaryandConclusion.
Table 1.3: education by age (%)
Education level of Respondent
16-17yrs (%)
18-25yrs (%)
26-35yrs (%)
36-45yrs (%)
46-55yrs (%)
>55yrs (%)
Total (%) N
None 0.8 4.5 6.7 9.7 10.4 33.6 11.6 3,141,306
Primary 32.9 33.2 44.1 49.2 47 45.7 42.8 11,607,789
Secondary 65.4 43.2 30.9 29.2 28.8 14.5 32.4 8,785,766
Tertiary 0.8 19 18.1 11.8 12.8 5.6 13 3,529,092
Other 0 0.1 0.2 0.1 0.9 0.6 0.3 81,056
Total 100 100 100 100 100 100 100 27,145,009
rural vs urban
40%60%
Age distribution (%)
120
80
40
100
60
20
016-17yrs
18-25yrs26-35yrs
36-45yrs46-55yrs
>55yrs
17.7
11.318.3
26.2
18.9
7.5
sex
51%Female Male
49%
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02ACCeSS to finAnCiAL SeRViCeS AnD PRoDUCtS
2.1 Accesstofinancialservices
Access to financeclassifiesconsumers/usersonthebasis of registration and regulation (Formality and Informality) as well as the excluded as indicated in the Table 2.1.Inparticular,consumerisclassifiedintheformalcategoryifhe/shehasaccesstoanyformalfinancial service or product. However, the sameconsumermayalsobeaccessinginformalfinancial
services or products. Where a consumer accesses onlyinformalfinancialservicesorproducts,he/sheisclassifiedasinformallyincluded.Aconsumerwhodoesnotaccessanyfinancial servicesorproductsfrom any formal or informal categories, he/she isclassifiedasexcluded.
This chapter tracks financial inclusion using the access dimension according to different measures. This is cross tabulated along the demographic characteristics of the population such as age, sex, education and the socio economic characteristics including livelihoods, income and expenditures.
KSH
Expanding Access to Financial Services and Products
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Table 2.1: Classification of the Access to Finance
Classification Definition Institution typeFinAccess survey cycles
2006 2009 2013 2016 2019
Formal (prudential)
Financial services and products used through prudentially regulated and supervised financial service providers by an independent statutory Government Agency including CBK, CMA, IRA, RBA and SASRA
Commercial banks including mobile phone bank products offered by banks in partnership with MNOs such as KCB M-PESA, MCo-op Cash, M-Shwari, Eazzy loan, Timiza and HF Whizz
ü ü ü ü ü
Microfinance banks including mobile banking products offered by microfinance banks ü ü ü
Insurance service providers ü ü ü ü ü
Deposit Taking SACCOs ü ü ü
Capital markets intermediaries ü ü ü
Formal (non-pru-dential)
Financial services and products offered through service providers that are subject to non-prudential regulation and supervision (oversight) by Government Ministries/ Departments with focused legislations
Mobile Money ü ü ü ü
Postbank ü ü ü ü ü
NSSF ü ü ü ü ü
NHIF ü ü ü ü
Formal (registered)
Financial services and products offered through providers that are legally registered legal persons and/ or operate through direct Government interventions
Credit only microfinance institutions (MFIs) ü ü ü ü ü
Non-deposit taking SACCOs ü ü ü ü ü
Hire purchase companies ü ü ü ü ü
Development financial institutions (DFIs) e.g. AFC, HELB, ICDC & JLB ü ü ü ü ü
Mobile Money Apps/ Digital Apps ü ü
InformalFinancial services offered through different forms not subject to regulation, but have a relatively well–defined organizational structure
Groups e.g. ASCAs, chamas & ROSCAs ü ü ü ü ü
Shopkeepers/supply chain credit ü ü ü ü ü
Employers ü ü ü ü ü
Moneylenders/shylocks ü ü ü ü ü
Excluded
Individuals who reported using financial services and products only through family, friends, neighbours or keep money in secret places or not using any form of financial service
Social networks and individual arrangements (e.g. secret hiding place) ü ü ü ü ü
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2.2 Accesstofinancialservicesandproducts,2006-2019
Overall access to formal financial services and productsimprovedto82.9percentin2019from75.3percentin2016(Figure 2.1 and 2.2). 89 percent can access any form offinancialservices.ThisshowsthatKenyahasmadeprogress
in expanding financial access from 26.7 percent in 2006,resultinginasignificantdipinthefinanciallyexcludedadultpopulationto11percentin2019comparedto17.4percentin2016.
Figure 2.1: Access trends (%)
90
807060504030201000
2006 2009 2013 2016 2019
41.3 40.4
66.775.3
82.9
32.126.7
26.825.4
17.411
7.8 7.26.1
Figure 2.2: Access by categories (%)
42.3
43.9
17.4
11.0
7.2
6.1
32.6
38.6
0.4
0.4
32.4 25.37.833.7
0.8
21.0 32.726.815.4 4.1
15.0 41.332.14.0 7.7
2016
2019
2009
2013
2006
` Formal prudential Formalnon-prudential Formal registered Informal Excluded
The survey findings show that formal financial inclusionhas increased over the period 2006 – 2019. The informaland excluded categories declined from 32.1 percent and 41.3percent in2006to6.1percentand11percent in2019.These developments could be attributed to the introduction ofmobilefinancial services in2007, followedby increased
partnerships and innovations such as mobile banking,agency banking, digital finance and mobile apps. Mobilemoney has acted as an ‘on-ramp’ for formal financialinclusionespeciallyviadigitalfinance.Despiteadvances informalfinancialinclusion,theinformalstillpersistsalthoughit’sonadecreasingtrajectory.
Formal Informal Excluded
2019 FinAccess Household Survey 9
2.3 Accesstofinancialservicesacrossdifferentsegmentsofthepopulation
Despite the significant improvement in access to financeovertheperiod2006–2019,financialinclusiongapspersistas measured by sex, age, education, residence, income,livelihood and wealth quintiles. However, these financialinclusion gaps are narrowing.
2.3.1 Access by sex
Whilethefinancialaccessgapbetweenmaleandfemaleisclosing,disparitiesstillremain(Figure 2.3).Accesstofinanceby males is higher than that for females in the population.
Figure 2.3: Access by sex (%)
90
807060504030201000
2006
male male male male maleFemale Female Female Female Female
2009 2013 2016 2019
7163
8071
8680
39
48
21 20
39
511
4
41 42
32 3924 27
16 1911 11
33
104 8
38
26
Formal Informal Excluded
2.3.2 Access by age
Accesstofinanceishighestforthe26–35year–oldsegmentofthepopulation(Figure 2.4).Majorityofrespondentsaged18–25yearsandthoseover55yearsaremorefinanciallyexcluded.
Figure 2.4: Access by age
Formal Informal Excluded
73.9
87.5
87.8
89.0
75.5
8.4
6.5
5.2
4.9
6.3
17.7
6.1
7.1
6.2
18.2
>55yrs
46-55yrs
36-45yrs
18-25yrs
26-35yrs
0% 10% 20% 30% 40% 50% 60% 70% 90%80% 100%
10 2019 FinAccess Household Survey
2.3.3 Access by education
Accesstoformalfinancialservicesincreasewitheducation.Thisisevidencedbythe98.6percentaccesstoformalfinancialservicesbyhouseholdswhohaveattainedtertiarylevelofeducationcomparedto60.7percentwithouteducation(Figure 2.5).
Figure 2.5: Access by education (%)
60.7
80
88.9
98.6
16.4
7.4
2.6
0.3
22.9
12.5
8.5
1.0
None
Primary
Secondary
Tertiary
Formal Informal Excluded
2.3.4 Access by residence
Therural-urbangapinaccesstofinancialaccesshasdeclinedduetofasteruptakebyruralresidents(Figure 2.6).
Figure 2.6: Access by residence
90
100
80
70
60
50
40
30
20
10
00
2006
Rural Rural Rural Rural RuralUrban Urban Urban Urban Urban
2009 2013 2016 2019
35.5
23.8
40.7
21.6
35.5
42.8
29.5
34.6
35.9
16.5
62.4
21.1
9.8
59.6
30.6
80.0
15.8
9.0
69.0
22.0
86.3
9.5
8.3
77.3
14.4
91.2
6.1
4.3 4.1 2.8
Formal Informal Excluded
2019 FinAccess Household Survey 11
2.3.5 Access by region
AccesstofinancebyregionshowswidedisparitieswiththeNorthRiftregioncomprisingofTurkana,SamburuandWestPokotcountiesrecordingthehighestexclusions(29%)in2019
(Figure 2.7).NairobiCounty is ranked thehighest in termsofaccesstoformalfinancialservicesfollowedbyMombasaandCentralRift region, respectively. Significantdrop in theexcludedpopulationswasrecordedinNorthEastern,UpperEasternandCoastalregions.
Figure 2.7: Regional maps of inclusion and exclusion (%)
(a) Formal inclusion (b): Financial exclusion
52.2% North Eastern
23.6% Coastal region
10.5% Mombasa
4.2% Nairobi
17.4% South Rift Valley
14.1% Lower Eastern
33.6% Upper Eastern
42.5% North Rift Valley
16.7% Central Rift Valley
20.6% Western
18.7% Nyanza
9.0% Central region
18.9% Mid Eastern
24.6% North Eastern
64.6% Coastal region
86.8% Mombasa
93.4% Nairobi
77.6% South Rift Valley
76.5% Lower Eastern
62.7% Upper Eastern
46.8% North Rift Valley
77.5% Central Rift Valley
69.8% Western
71.1% Nyanza
87.4% Central region
76.9% Mid Eastern
2016 2016
2019 2019
12 2019 FinAccess Household Survey
2.3.6 Access by livelihood
The term livelihood refers to the economic activities/occupation that the household earns an income to support life. It’s broadly categorized into; employed, running ownbusiness,workingasacasuallabourer,practisingagricultureor are part of the dependent population which relies on pension,money from family/friends/spouseoraidagency.Access to formal financial services andproducts increaseswith thedegreeof formalization in the labourmarket.Thesurvey results show that households who own business andemployedhave93.3percentand98.7percentaccesstoformalfinancialservices(Figure 2.8). Exclusion from access toformalfinancialservicesishighest(23%)forthedependentpopulation. Despite agriculture being the mainstay of the Kenyaneconomy, formalaccesstohouseholdsengagedinagricultureremainslowwithanexclusionof12.6percent.
2.3.7 Access by wealth quintiles
Accesstofinancialserviceswasalsoanalysedbasedonthewealth categorization. Five wealth quintiles (1 being lowest and5highest)werederivedfromtheProbabilityofPovertyIndex (PPI). The PPI was generated from select variablescomparable with the Kenya Integrated Household BudgetSurvey(KIHBS)2015/16fromtheKNBS.Thevariablesinclude;countyofresidence,educationlevel,assetbaseandhousingconditions. The quintiles therefore reflect the economicstatus of the population. In this regard, the survey resultsindicate that access to formal financial services increasedwiththewealthquintiles,thelowesthavinganexclusionrateof22.1percent,whilethehighesthada3.3percentexclusionrate (Figure 2.9).
Figure 2.8: Access by livelihood (%)
Formal Informal Excluded
Figure 2.9: Access by wealth quintile (%)
Formal Informal Excluded
2019 FinAccess Household Survey 13
2.3.8 Country comparison of access
Kenyaisrankedhighlyinfinancialinclusion,secondonlytoSeychellesandSouthAfrica(Figure 2.10).
Figure 2.10: Country comparison of access in the region (%)
Source: Finscope surveys
14 2019 FinAccess Household Survey
03
USAGe of finAnCiAL SeRViCeS AnD PRoDUCtS
Innovation driving usage of Financial services and products
Usage” dimension of financial inclusion refers to the depth or extent to which financial services and products are used as measured
by regularity, frequency and duration of their use over time.
Usage provides information not only on the value that financial services and productscontribute to the economic lives of users, butalso whether business models that provide such services are commercially viable or not. While the previous FinAccess surveys focussed more onaccessdimension,theFinAccessHouseholdSurvey 2019 report has significantly focussedonUsagedimension,with additionalworkonimpact and welfare dimensions. Of particularprominence is the role of digital transformation in influencing the uptake of financial servicesand products.
In this chapter, we analyse how the usage of;financialservicesproviders,financialproducts,anddigitalplatformshaveevolved since2006whenthefirstbaselinesurveywasconducted.The chapter discusses drivers and barriers of usage of financial institutions and products.Thechapterconcludeswithkeyobservations.
3.1 Financial service usage by institution
This Survey sought to establish how adult population Kenya use different institutionsprovidingfinancialservices.At79.4percentand8.3 percent, mobile money services providersand digital loans apps recorded the highest increaseinusagebyKenyans(Figure 3.1).
2019 FinAccess Household Survey 15
tHe nUMBeRS At A GLAnCe
79% mobile money accounts
25% mobile bank accounts
30% traditional bank accounts
26% National Hospital insurance Fund
8% Digital App loans
Figure 3.1: Changing landscape of financial service providers in 2006 - 2019 (%)
Note: Pension category includes NSSF; Bank includes traditional banks, mobile banking (e.g. Mshwari, KCB Mpesa, Equitel Money), Post bank and Microfinance Banks; Saccos include deposit and non-deposit taking Saccos; and mobile money includes Mpesa, Mobile Pay, Airtel Money, and T-Kash.
* not exclusive users hence not additive to 40.8 percent. ** this figure does not include group of friends.
Bank SACCOs MFIs Insurance (Incl. NHIF)
Pension Mobile Money
Informal Group
Digital Loans Apps
2006 2009 2013 2016 2019
14.0
29.2
20.5
34.4 40
.8
13.1
11.0
9.0 12
.911
.3
1.7 3.5
3.4
3.6
1.7 4.
9
17.8
3.3
23.2 27
.9
3.2
1.9
3.7
12.5
12.2
0.0
61.6
27.9
71.4 79
.4
32.4
27.7
36.0 41
.130
.1**
0.6
8.3
Mobile banking: 2016 = 17.5 % 2019 = 25.3%* Traditional banking: 2016 = 31.7% 2019 = 29.6%*
16 2019 FinAccess Household Survey
The significant decline in the MFIs usage to its 2006 level1.7 percent could be attributed to increased uptake ofmobilebankingproducts,emerging rapiduptakeofdigitalloans apps and increasing role of mobile money. We also notethevolatilityintheuseofinformalsources,butusageremainssignificantlyhighat30.1percent in2019, implyinginformalgroupsarestillakeysourceoffinancinginKenyanhouseholds. We however, with advent of mobile money,this channel is becoming more formalized as noted in 11.3 percentagepointsdeclineinusagebetween2016and2019.
Stronggrowthinuptakeofdigitalappsloansfrom0.6percentin2016to8.3percentin2019indicatestheroleunregulatedserviceprovidersareplayinginfinancialservicesspace.
Intermsofthenumberofusersbyinstitution,mobilemoneyservice providers served close to 20 million adults out of the 25.1 million analysed. This was about 5 million increase in users in just years, highlighting the significant role thisinnovation continues to play in the economy (Figure 3.2). Mostoftheshiftinusagecamefrominformalgroups’usersandnewentrantsinthefinancialservicesspace.
Figure 3.2: Adults using financial services providers (millions)
Notes:* Includes commercial banks, mobile banking (e.g. Mshwari, KCB Mpesa), Post bank and Microfinance Banks;** Includes deposit and non-deposit taking Saccos; *** Includes NSSF# Comprises Mpesa, Mobile Pay, Airtel Money, Equitel Money and T-Kash.
The Government policy initiatives on universal healthcaretogether with other policy measures led to increased usage of NHIFuptakeleadingalmostdoublingoftheusageofinsuranceservices.InitiativesbyRetirementBenefitsAuthorityandNSSFhasgraduallyraiseduptakeofpensionservicestoabout3.01millionadultusersin2019.Whiletheuseofinformalgroupsdeclined marginally to 7.6 million adults in 2019 from 8.8millionin2016,theseserviceprovidersremainacriticalsourceoffinancingtotheKenya’shouseholds.
3.2 Frequencyinusageoffinancialservicesbyinstitution
AsanindicatorofmeasuringUsage,frequencyofuseofaninstitution or a product is very important. The survey results indicate that a majority of Kenyans use financial serviceproviders on monthly basis. This may imply that most of the users are salaried employees, remittances to Saccos andloan repayments to service providers (Figure 3.3).
2019 FinAccess Household Survey 17
Figure 3.3: Frequency of usage (%)
Asthecountrybecomesmoredigitalized,thesurveyresultsshow that the frequency of transactions through mobile money increaseswhile thatofbankaccount reduces.Highfrequencyintheuseofmobilemoney,mobilebankingandinformalserviceprovidersonbasis,couldbeareflectionofincreasing liquidityneedsof therespondents,convenienceand ease of access.
3.3 Useoffinancialserviceprovidersbydemographics
Financialserviceprovidersservedifferentclassesofpeople
located in different geographical areas in the country. Welook at how education level, residence, sex and wealthinfluenceuseofdifferentfinancialserviceproviders.
3.3.1 Education level
Usageofmobilemoney, informalgroupsanddigital loansapps have traction across all the education levels (Figure 3.4). We however note the 11 percent adults with no any form of educationusing financial services frombanks, implyingnodiscriminatorytendencieseducationbasisbybanks.
Figure 3.4: Usage by education level (%)
E
18 2019 FinAccess Household Survey
3.4 drivers of usage
Mobilemoneyisthekeydriverofnarrowingthegapbetweenruralandurbanusersoffinancialservices.Theimproveduptakeinbothruralandurbanareasby10percentagepointsand5percentagepointsrespectively,signifiesitsimportance.
Figure 3.6: Usage by residence (%)
Figure 3.5: Usage by sex (%)
3.3.2 Narrowing gap between male and female
Digitalfinancialservicesprovidetheoptimalmarket-basedsolutioninnarrowingthegapinusageoffinancialservicesbetween male and female. The gap in Mobile money usage betweenthetwogendernarrowedto7percentin2019from8 percent in 2016. For banks and insurance, gender gapswere14percentand13percent in2019comparedwith16percentand13percentrespectivelyin2016infavourofmale.
There is no gap between male and female in the use of digitalappsloans,reflectingstronguptakeinjustthreeyears(Figure 3.5).
Although the female gender remains the majority users of informalgroupsinbothyears,thegapinthegenderdividehasnarrowedfrom20percentin2016to14percentin2019,underlining the roleofdigital financial services inbringingmorewomenintoformalfinancialservices.
2019 FinAccess Household Survey 19
Theuseofinformalfinancialservicesremainssignificantinbothruralandurbandwellingshighlightingafinancialneedthis group serves. The double digit gap in usage of banks(29%),mobilemoney(16%),andinsurance(22%)infavourof theurbanresidents in2019 isan improvement fromthe31percentand20percentforbanksandmobilemoneybutworsening gap for insurance.
3.5 Financial services by wealth quintile
Use of mobile money and bank remain key providers offinancial services across all the social strata (Figure 3.7). Informal group usage plays an important role to all social class.
3.6
3.7
3.8
27.3
57.7
28.6
58.4
11.5 15
.5
10.3 12.8
3.2 4.4
1.6
1.8
16.7
34.4
22.7
44.5
6.6
20.4
64.4
83.5
73
88.6
40.1 43
.8
28.6 32.2
0102030405060708090
100
Rural Urban Rural Urban
2016 2019
Bank SACCOs MFIs Insurance (Incl.NHIF) Pension Mobile Money Informal Group Digital Apps Loans
11.4
1.9
0.3 6.
3
1.3
59
18.6
3.2
26.3
6.4
0.8
16.4
6.4
73.8
27.1
5.3
41.2
10.8
2
28.1
10.3
86.8
33.6
8.6
61.9
16.5
2.3
42.4
20.7
90.1
34.8
10.9
72.1
24.1
3.4
53.3
26.1
92.3
39.4
15.1
0102030405060708090
100
Bank SACCO MFI Insurance (incl.NHIF)
Pension Mobile money Informal group Digital Apps Loans
Lowest Second Lowest Middle Second Highest Highest
87.9
91
66
62
78
72
69
75
0
81
86.8
62
83
24
18
43
43
42
37
13
56
63
61
81
24
18
38
37
36
32
12
46
62
0 10 20 30 40 50 60 70 80 90 100
% with access to mobile money
Access a mobile phone (own or borrow)
% Advanced DFS users
% Female advanced DFS users
% Active account owners
% Active digital account owners
% Active mobile money users
% Female active account owners
% Gender gap active accounts
% Registered account owners
% with access to a digital account
Uganda (2017) Tanzania (2017) Kenya (2019)
Figure 3.7: Usage by wealth quintile (%)
20 2019 FinAccess Household Survey
3.6 digital activity in usage
Significantgrowthindigitalaccountsownershipandregistrationwasrecordedin2019comparedto2016,reflectinghighadoptionof digital accounts (Figure 3.8).
Figure 3.8: Active digital accounts in Kenya: 2016 versus 2019 (%)
*Active digital account refers to the use of a bank, mobile bank, mobile money, or regulated MFI, SACCO through transactions or access via mobile phone app, website, debit/credit card or other means, without using cash, in the past 90 days.
Despitedifferences in theyearsof thesurvey, the2019surveydata indicatesignificantdigitalaccountsusage forbothsavings,borrowing and for transactions purposes (Figure 3.9).
Figure 3.9: Active digital accounts: Country comparisons (%)
87.9
91
66
62
78
72
69
75
0
81
87
62
83
24
18
43
43
42
37
13
56
6362
61
81
24
18
38
37
36
32
12
46
0 10 20 30 40 50 60 70 80 90 100
% with access to mobile money
Access a mobile phone (own or borrow)
% Advanced DFS users
% Female advanced DFS users
% Active account owners
% Active digital account owners
% Active mobile money users
% Female active account owners
% Gender gap active accounts
% Registered account owners
% with access to a digital account
Uganda (2017) Tanzania (2017) Kenya (2019)
3.9
3.17
3.18
33.5
22.3
16.1
0.9
0.1
36.0
20.6
21.8
1.2
0.5
27.118.9Access to money for help through life
events/emergencies
To give each other in a lump sum (Pot) or gift in turn
Offer svaings and lending product
Deposits for future sharing
Get a lump sum for assets purchase
Commitment to save
UrbanRural
Records on members money paid / received
Elect officials through voting
Written constitution
A certificate of registration
Bank account
A group cheque book with more than one signatory
Borrow money from a bank
Have a mobile money account
Urban Rural Female Male Overall
0 10 20 30 40 50 60 70 80 90 100
91
2019 FinAccess Household Survey 21
3.7 Useofaportfoliooffinancialserviceproviders
ThenumberofKenyansusingmorethanonetypeoffinancialserviceshasincreasedsignificantlyovertheperiodbetween2016and2019 (Figure 3.10), perhapshighlighting interlinkagesbetweenmobilemoney, digital platformsand traditional financialservices providers.
Figure 3.10: Overlaps in the use of financial services 2006 – 2019 (%)
3.8 Financial services usage by products
3.8.1 Bank account usage
While the usage of traditional accounts declined from 31.7 percent in 2016 to 29.6 percent in 2019, mobile bankingaccountsusageincreasedto25.3percentin2019from17.5
percent in 2016. Growth inmobile banking account usageis mainly driven by young people below the age of 35 years (Figure 3.11).Notehoweverthatregardlessoftheage,userscombinemobileandtraditionalbankingservices.
Figure 3.11: Mobile bank versus traditional bank accounts usage by age in 2016 and 2019 (%)
3.10
3.11
3.12
39.8
36.1
26.9
22.6
15.3
18.8
31.2
47.8
60
73.7
41.3
32.7
25.4
17.4
11
0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%
2006
2009
2013
2016
2019
One type of financial service Two or more types of financial services none (excluded)
31.7
17.5
29.6
25.3
22.7
23.2
22.8 24
37.9
22.7
33.3
39.1
36.3
17.5
34.1
19.7
36.4
11.4
33.7
10.2
25.5
3.7
24.9
6.3
T r a d i t i o n a l b a n k s M o b i l e b a n k a c c o u n t T r a d i t i o n a l b a n k s M o b i l e b a n k a c c o u n t
2016 2019
Overall 18-25yrs 26-35yrs 36-45yrs 46-55yrs >55yrs
31.7
17.5
29.6
25.3
21.8
10.5
19.7
16.2
48.8
29.5
44
38.4
T r a d i t i o n a l b a n k s M o b i l e b a n k a c c o u n t T r a d i t i o n a l b a n k s M o b i l e b a n k a c c o u n t
2016 2019
Overall Rural Urban
3.10
3.11
3.12
39.8
36.1
26.9
22.6
15.3
18.8
31.2
47.8
60
73.7
41.3
32.7
25.4
17.4
11
0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%
2006
2009
2013
2016
2019
One type of financial service Two or more types of financial services none (excluded)
31.7
17.5
29.6
25.3
22.7
23.2
22.8 24
37.9
22.7
33.3
39.1
36.3
17.5
34.1
19.7
36.4
11.4
33.7
10.2
25.5
3.7
24.9
6.3
T r a d i t i o n a l b a n k s M o b i l e b a n k a c c o u n t T r a d i t i o n a l b a n k s M o b i l e b a n k a c c o u n t
2016 2019
Overall 18-25yrs 26-35yrs 36-45yrs 46-55yrs >55yrs
31.7
17.5
29.6
25.3
21.8
10.5
19.7
16.2
48.8
29.5
44
38.4
T r a d i t i o n a l b a n k s M o b i l e b a n k a c c o u n t T r a d i t i o n a l b a n k s M o b i l e b a n k a c c o u n t
2016 2019
Overall Rural Urban
22 2019 FinAccess Household Survey
On average as measured by male/female versus rural/urban indicators,mobilebankingaccountusage increasedby 8 percent in 2019 compared to usage in 2016 but useof traditional bank account declined by an average of2.1 percent during the same period (Figure 3.12). Rapid adoption of mobile banking accounts usage was moreamong the male/urban users at 8 percent growth rate,although adoption among the female/urban mobilebankingaccountsusagewasjust1percentagepointbelow,
at 7 percent growth rate. Thismay reflect closure of bankbranchesbysomebanksandrapiduptakeoftechnologicalsolutions by young people.
Reasons for non-use of bank account
Of the twenty-two (22) reasons surveyed for non-use of abank account, eight (8) reasons emerged top with a totalresponserateof88.3percent(Figure 3.13).Lackofmoneytosave,inabilitytomaintainanaccountandlackofregular
Figure 3.12: Mobile bank versus traditional bank accounts by sex and residence (%)
Figure 3.13: Top reasons for non-use of a bank account 3.13
3.14
3.16
35.1
19.315.5
6.1 4.0 3.5 2.5 2.2
11.7
0.0
5.0
10.0
15.0
20.0
25.0
30.0
35.0
40.0
No money to Save No regular Income Other Options thana bank
No ID/Passport OthersReasons:
35.4
37.9
33.6
38.1
33.0
27.4
31.4
30.5
12.7
14.0
12.7
13.5
10.6
11.8
11.9
10.6
8.2
8.9
10.3
7.4
0.0 10.0 20.0 30.0 40.0 50.0 60.0 70.0 80.0 90.0 100.0
Male
Female
Rural
Urban
ATM or Card Swipe machine not working Unexpected charges
Poor service received at a branch/agent/customer care Lost money/Money Missing from my account
Other
27.932.3
22.8
10.9
55.7
35.9
24.3
12.2
31.724.1
5.5
19.2
35.839.9
13.6 15.4
23.630.1 30.1
18.8
0
10
20
30
40
50
60
70
80
Secret Hiding Place Group or Chama Usage Cash and Goods and serviceson credit from a shopkeeper
Family/Friends/Neighbourand Group of Friends
2006 2009 2013 2016 2019
No
mon
ey
to sa
ve
Can’ta
ffordto
No
regu
lar i
ncom
e
Hav
e no
job
Otheroptions
th
anaban
k
Nee
dno
ban
k a
ccou
nt
NoID/Pas
sport
Others
Prefersc
ash
2019 FinAccess Household Survey 23
incomewerethetopthreereasonscited,intotalaccountingfor 70 percent of response rate. This concludes that demand sidefactorsratherthansupplysideconstraintsdoinfluenceuse of bank services.Other reasons such as longdistancetonearestbank, lackof trust, financial literacy limitations,amongotherswerenotsignificant.
Challenges faced in use of a bank account
There are two main challenges customers cited in the use
of a bank account. These are; Automated Teller Machine(ATM)or cardmachinenotworking, andbeing leviedwithunexpected charges (Figure 3.14).
TheATM/cardmachinenotworkingwasmorepronouncedin the urban areas and among the female users while the unexpected charges was more cited by male and rural users. The lossofmoney in thebankaccountwascitedmorebyfemale users and those residing in rural areas.
Figure 3.14: Top challenges cited in bank account usage (%)
3.13
3.14
3.16
35.1
19.315.5
6.1 4.0 3.5 2.5 2.2
11.7
0.0
5.0
10.0
15.0
20.0
25.0
30.0
35.0
40.0
No money to Save No regular Income Other Options thana bank
No ID/Passport OthersReasons:
35.4
37.9
33.6
38.1
33.0
27.4
31.4
30.5
12.7
14.0
12.7
13.5
10.6
11.8
11.9
10.6
8.2
8.9
10.3
7.4
0.0 10.0 20.0 30.0 40.0 50.0 60.0 70.0 80.0 90.0 100.0
Male
Female
Rural
Urban
ATM or Card Swipe machine not working Unexpected charges
Poor service received at a branch/agent/customer care Lost money/Money Missing from my account
Other
27.932.3
22.8
10.9
55.7
35.9
24.3
12.2
31.724.1
5.5
19.2
35.839.9
13.6 15.4
23.630.1 30.1
18.8
0
10
20
30
40
50
60
70
80
Secret Hiding Place Group or Chama Usage Cash and Goods and serviceson credit from a shopkeeper
Family/Friends/Neighbourand Group of Friends
2006 2009 2013 2016 2019
Figure 3.15: Usage by number of groups
1 group 2 groups 3 groups >3 groups
3.8.2 Informal usage
Informal usage consists of groups or chamas(ROSCAsandASCAs).In2019,amajorityofKenyans,at70percent, used one group/chama in the last 12 months as a source offinancialservices(Figure 3.15).
70%
8%
3%
19%
24 2019 FinAccess Household Survey
Over time,useof informalgroupshasaveragedabout32percentand is volatile,but stillhigher thanother formsof informalusage (Figure 3.16).Ofimportancetonoteisthesignificantdeclineintheuseofasecrethidingplace,(initiallydefinedundertheExcluded),from55.7percentin2009to23.6percentin2019,perhapsreflectingtheincreaseduseofmobilemoney.
Thesignificantincreaseintheuseofshopkeeperfinancingbetween2016and2019maysignalincreasingroleofsocialnetworks.
Figure 3.16: Breakdown in informal group over time (%)
3.13
3.14
3.16
35.1
19.315.5
6.1 4.0 3.5 2.5 2.2
11.7
0.0
5.0
10.0
15.0
20.0
25.0
30.0
35.0
40.0
No money to Save No regular Income Other Options thana bank
No ID/Passport OthersReasons:
35.4
37.9
33.6
38.1
33.0
27.4
31.4
30.5
12.7
14.0
12.7
13.5
10.6
11.8
11.9
10.6
8.2
8.9
10.3
7.4
0.0 10.0 20.0 30.0 40.0 50.0 60.0 70.0 80.0 90.0 100.0
Male
Female
Rural
Urban
ATM or Card Swipe machine not working Unexpected charges
Poor service received at a branch/agent/customer care Lost money/Money Missing from my account
Other
27.932.3
22.8
10.9
55.7
35.9
24.3
12.2
31.724.1
5.5
19.2
35.839.9
13.6 15.4
23.630.1 30.1
18.8
0
10
20
30
40
50
60
70
80
Secret Hiding Place Group or Chama Usage Cash and Goods and serviceson credit from a shopkeeper
Family/Friends/Neighbourand Group of Friends
2006 2009 2013 2016 2019
Amajority of groups have records on theirmemberswho have paid or receivedmoney, legitimately elected officials, validlyregistered and governed under a constitution (Figure 3.17).Thesearekeyrequirementsforwell-runorganizationsthatprovideorganizedfinancialservicesandcanattractexternalfinancing.
Figure 3.17: Features of groups in 2016 and 2019 (%)
90.2
79.6
66.6
46.5
42.0
78.7
68.3
59.2
44.5
36.6
0.0 10.0 20.0 30.0 40.0 50.0 60.0 70.0 80.0 90.0 100.0
Records on members money paid / received
Elect officials through voting
Written constitution
A certificate of registration
Bank account
2016 2019
35.5 37.828.6
34.2
50.452 51.558.4
66.4 69.9
0.0
10.0
20.0
30.0
40.0
50.0
60.0
70.0
80.0
2006 2009 2013 2016 2019
Credit/Loans Savings
25.6
21.9
21
6.6
4.8
3.4
2.7
2
48.7
39.3
32.8
21.7
6.2
5.9
5.2
8.2
0 10 20 30 40 50 60
Day-to-day household needs
For big emergencies (burial/medical)
Education(self, child, sibling)
For old age
Expand business/Buy equipment
Improving/buy a house
Buy land
Personal reasons(new clothes,shoes)
2016 2019
2019 FinAccess Household Survey 25
Figure 3.18: Features of groups by sex and residence (%)
87.9
91
66
62
78
72
69
75
0
81
87
62
83
24
18
43
43
42
37
13
56
6362
61
81
24
18
38
37
36
32
12
46
0 10 20 30 40 50 60 70 80 90 100
% with access to mobile money
Access a mobile phone (own or borrow)
% Advanced DFS users
% Female advanced DFS users
% Active account owners
% Active digital account owners
% Active mobile money users
% Female active account owners
% Gender gap active accounts
% Registered account owners
% with access to a digital account
Uganda (2017) Tanzania (2017) Kenya (2019)
3.9
3.17
3.18
33.5
22.3
16.1
0.9
0.1
36.0
20.6
21.8
1.2
0.5
27.118.9Access to money for help through life
events/emergencies
To give each other in a lump sum (Pot) or gift in turn
Offer svaings and lending product
Deposits for future sharing
Get a lump sum for assets purchase
Commitment to save
UrbanRural
Records on members money paid / received
Elect officials through voting
Written constitution
A certificate of registration
Bank account
A group cheque book with more than one signatory
Borrow money from a bank
Have a mobile money account
Urban Rural Female Male Overall
0 10 20 30 40 50 60 70 80 90 100
To establishwhether there are differences on how groupsare run, the survey assessed group features in rural-urbandimension as well as between the two sexes. The results indicatethatmostgroups,whether inruralorurbanareas,or whether they are run by male or female have important records and documentation (Figure 3.18).
Most of the groups are yet to embrace use of mobile money orevenborrowing frombanks toundertake their financialobligations.
Toestablishthesocio-economiccontributionsofgroups,aquestionwasaskedonthemainactivitiesdrivingtheuseofgroups. The survey results were compared with the results in 2016. Overall, while the groups remain very importantin providing money to support their members overcome challenges in life, they have emerged strongly as avenuesforfinancialintermediation(savingandlendingforareturn)and safe keeping (deposits for future sharing) (Table 3.1). However, theuseofgroups inobtaining lumpsummoneytopurchaseassetshasdeclinedsignificantly.
Table 3.1: Key activities driving groups (%)
Activity 2016 2019 Change
Access to money for help through life events/emergencies 25.4 23.7 -1.7
To give each other a lump sum (pot) or gift in turn 22.2 34.5 12.3
Offer savings and lending product 15.7 21.6 5.9
Deposits for future sharing 12.2 18.5 6.3
get a lump sum for assets purchase 11.6 1.0 -10.6
commitment to save 6.4 0.3 -6.1
26 2019 FinAccess Household Survey
ThemostcitedreasonbyamajorityofKenyansforjoiningagroup,whetherbymaleorfemaleacrossruralandurbanareas,istheneedtocollectmoneyinordertogiveeachotheralumpsum(pot)orasagiftinreturn.Thisismoresoforfemaleusersinurbandwelling.Malesresidinginruralareasfindthisproductmoreimportantinaccessinglumpsummoneytomeetemergencies(Figure 3.19).
Figure 3.19: Key activities of groups by gender and residence (%)
87.9
91
66
62
78
72
69
75
0
81
87
62
83
24
18
43
43
42
37
13
56
6362
61
81
24
18
38
37
36
32
12
46
0 10 20 30 40 50 60 70 80 90 100
% with access to mobile money
Access a mobile phone (own or borrow)
% Advanced DFS users
% Female advanced DFS users
% Active account owners
% Active digital account owners
% Active mobile money users
% Female active account owners
% Gender gap active accounts
% Registered account owners
% with access to a digital account
Uganda (2017) Tanzania (2017) Kenya (2019)
3.9
3.17
3.18
33.5
22.3
16.1
0.9
0.1
36.0
20.6
21.8
1.2
0.5
27.118.9Access to money for help through life
events/emergencies
To give each other in a lump sum (Pot) or gift in turn
Offer svaings and lending product
Deposits for future sharing
Get a lump sum for assets purchase
Commitment to save
UrbanRural
Records on members money paid / received
Elect officials through voting
Written constitution
A certificate of registration
Bank account
A group cheque book with more than one signatory
Borrow money from a bank
Have a mobile money account
Urban Rural Female Male Overall
0 10 20 30 40 50 60 70 80 90 100
Just like other financial services providers, groups alsoface numerous challenges. The survey results indicate that dishonesty and high defaults rates on money given out to membersandnon-memberswasthemainchallengecited
byamajorityofrespondentsat48.7percentin2019upfrom12percent in2016.Thiswasfollowedbyfraudandtheftoffunds by committee members of the groups (Table 3.2).
Table 3.2: Top challenges facing groups in 2016 - 2019 (%)
Challenges 2016 2019 Change
Dishonesty or default by members 12.0 48.7 36.7
Theft or fraud by a committee member 6.2 25.6 19.4
Theft or fraud by a non-group member 3.7 7.4 3.8
Bad investment of funds 2.9 5.1 2.2
Acting as a guarantor* n/a 11.3 n/a
Other* n/a 1.9 n/a
* these questions were not in the 2016 survey.
2019 FinAccess Household Survey 27
Figure 3.20: Overall savings and credit usage, 2006 – 2019 (%)
90.2
79.6
66.6
46.5
42.0
78.7
68.3
59.2
44.5
36.6
0.0 10.0 20.0 30.0 40.0 50.0 60.0 70.0 80.0 90.0 100.0
Records on members money paid / received
Elect officials through voting
Written constitution
A certificate of registration
Bank account
2016 2019
35.5 37.828.6
34.2
50.452 51.558.4
66.4 69.9
0.0
10.0
20.0
30.0
40.0
50.0
60.0
70.0
80.0
2006 2009 2013 2016 2019
Credit/Loans Savings
25.6
21.9
21
6.6
4.8
3.4
2.7
2
48.7
39.3
32.8
21.7
6.2
5.9
5.2
8.2
0 10 20 30 40 50 60
Day-to-day household needs
For big emergencies (burial/medical)
Education(self, child, sibling)
For old age
Expand business/Buy equipment
Improving/buy a house
Buy land
Personal reasons(new clothes,shoes)
2016 2019
3.8.3 Savings and credit usage
The gap between savings and credit has narrowed in the period 2016 - 2019. Credit uptake has been rising steadilywhile savings rate remains gradual (Figure 3.20).
Growthinbankaccountsavingsinstrument,ismainlydrivenbyuptakeintheuseofmobilebankingaccounts(Table 3.3). Use of secret hiding place still remains high.
Table 3.3: Savings instruments use by type of provider (%)
2006 2009 2013 2016 2019FormalBank savings Account 12.4 12.4 9.8 24* 25.4**
postbank Account 5.6 2.5 2.3 1.5 0.3
sAccO 12.8 8.9 10.6 12.6 9.4
mFi/mFB 1.5 3.2 3.1 3.3 0.7
mobile money n/a n/a 27 43.3 53.6
Informalgroup/Chama 34.7 37.1 26.8 39.2 30.1
group of Friends 10.9 5.5 12.2 9 4.6
Family/Friend 16.6 11.6 19.2 15.4 11.8
secret Hiding place 27.9 55.7 31.7 35.8 23.6
*constitutes 16.8% of savings in mobile bank accounts **constitutes 19.2% savings in mobile bank accounts
28 2019 FinAccess Household Survey
Saving
Inboth2016and2019,thetopthreereasonswhypeoplesaveweremeetingexpensesarisingfromemergencies(burial,medicalcosts),householdconsumerneedsandforeducation(Figure 3.21).
Figure 3.21: Key Reasons why people save in 2016 and 2019 (%)
90.2
79.6
66.6
46.5
42.0
78.7
68.3
59.2
44.5
36.6
0.0 10.0 20.0 30.0 40.0 50.0 60.0 70.0 80.0 90.0 100.0
Records on members money paid / received
Elect officials through voting
Written constitution
A certificate of registration
Bank account
2016 2019
35.5 37.828.6
34.2
50.452 51.558.4
66.4 69.9
0.0
10.0
20.0
30.0
40.0
50.0
60.0
70.0
80.0
2006 2009 2013 2016 2019
Credit/Loans Savings
25.6
21.9
21
6.6
4.8
3.4
2.7
2
48.7
39.3
32.8
21.7
6.2
5.9
5.2
8.2
0 10 20 30 40 50 60
Day-to-day household needs
For big emergencies (burial/medical)
Education(self, child, sibling)
For old age
Expand business/Buy equipment
Improving/buy a house
Buy land
Personal reasons(new clothes,shoes)
2016 2019
Security andconvenienceare themaindrivers influencing choiceof a given savings instrument (Figure 3.22). Together, theyaccountfor65.8percentofreasonsgivenbytherespondents.
Figure 3.22: Top Consideration in choosing a saving instrument in 2019 (%)
40.5
25.3
8.9 7.65.1 4 3.7
05
1015202530354045
Safe/secure Easy to put money in/
convenient
Can access in an emergency
When I save here, I can get
credit
When I save here, I can get a
lump-sum at the end of a
period
Confidential/no one knows you
have money
Most trusted
4.2
11.6
3.7
10.9
12.5 12.2
4.9 5.8 6.1 6 5.5
2.7 2.9
2006 2009 2013 2016 2019
NHIF Investments Pension (excl. NSSF) Insurance (regulated by IRA) NSSF
26.1
21.2
15.6
9.6
3.23.2
10.3
3.2
11.4
85.6 85.5 81.068.8
60.4 60.0 56.6
11.0 4.2 11.417.2
14.329.8 31.9
3.1 10.3 7.5 14.025.4
10.2 11.5
0
10
20
30
40
50
60
70
80
90
100
Medical (not NHIF)
Car Insurance NHIF Education Insurance
House Insurance
Other Insurance
Crop Insurance
In own name Jointly In someone else’s name
3.13
35.1
19.315.5
6.1 4.0 3.5 2.5 2.2
11.7
0.0
5.0
10.0
15.0
20.0
25.0
30.0
35.0
40.0
No money to Save No regular Income Other Options thana bank
No ID/Passport OthersReasons:
11.7
2019 FinAccess Household Survey 29
Challengesinhavingsufficientamountofmoneytosaveandlackofregular incomewerecitedasthemostconstrainingfactorstosavingsamongKenyans,at42.3percentand38.3percentrespectivelyin2019(Figure 3.23). This suggests that
Kenyans have been able to generate an income over theyears,butareunabletomakesavings,astheyarenotcertainofwhenthey’llmaketheirnextearnings.
Figure 3.23: Top Reasons for not saving (%)
Kenyans need to generate a regular income to save
30 2019 FinAccess Household Survey
Credit uptake
Credit uptake through formal andnon-formal digital channels as wellas informal sources, in particularshopkeepercreditandfamily/friendsrecorded notable increase in 2019compared to 2016. The highestgrowthwasinshopkeepercreditanddigital app loans (Table 3.4).
Table 3.4: Credit uptake by institution (%)
Credit 2006 2009 2013 2016 2019
Formal
personal Bank loan 1.8 2.6 3.6 4.4 4.3
House/land Bank/Building society loan 0.5 0.2 0.9 0.6 0.3
Overdraft 0.3 0.2 0.5 0.4 0.2
credit card 0.8 0.8 1.8 1.2 0.5
mobile banking loan n/a n/a n/a 5.9 9.5
sacco loan 4.2 3.1 4 5 5.1
mFi loan 0.8 1.8 1.6 1.8 0.9
government loan 0.9 0.3 0.6 1.3 1.3
Hire purchase 0.6 0.1 0.2 0.1 0.6
Informal
employer loan 0.9 0.5 1 5.1 1.4
Chama loan 1.7 1.8 6 8.3 8
informal moneylender 0.7 0.4 0.4 0.4 0.5
shopkeeper 22.8 24.3 5.5 9.9 29.7
Buyer credit 0.9 1.2 1.1 0.3 1
Digital loan apps n/a n/a n/a 0.6 8.3
Family/friend/neighbor loan 12.6 12.2 5.2 6.6 10.1
2019 FinAccess Household Survey 31
Reasons for being denied credit
TherearevariousreasonswhymanyKenyansaredeniedcredit,whichvarybyinstitution.Overall,bad/nocredithistoryisthemainreason cited by respondents for being denied credit by providers (Figure 3.24).
Figure 3.24: Reasons for being denied credit by institution in 2019 (%)
58.4
44.5
88.6
1.8
12.8
32.2
20.428
.622
.773
.01.
6 10.3
28.6
6.6
57.7
34.4
83.5
4.4
15.5
43.8
27.3
16.7
64.4
3.2 11
.540
.1
2.4
1.0
6.7
2.8
37.6
34.0
9.1
11.7
17.5
5.4
5.2
37.8
13.5
8.1
8.1
18.9
14.5
15.0
35.3
55.1
28.0
13.3
30.3
23.8
11.6
8.3
5.8
36.3
37.8
14.0
25.7
18.2
4.6
3.4
16.2
18.6
9.7
9.8
3.6
7.9
3.1
5.2
7.8
3.9
13.4
Bank
Sacco
MFI
Mobile money
Mobile Banking
Chama
Digital Loans
Long process/tedious Still had debt to pay off No guarantor
Was not given a reason Bad/no credit history Insufficient income/ savings
Lack of collateral Did not have records Others
57.9
16.5 14.1
4.0 3.6 3.0
54.5
13.618.3
2.7 4.7 4.1
Major sickness/accident injury
Loss/damage of business/livestock or
crop by natural disasters
Death of a family member/ relative
Death of main income earner
Child birth Loss/damage of major asset/ money because
of theft, disaster or other causes
Poorest 60% of Kenyans Wealthiest 40% of Kenyans
32 2019 FinAccess Household Survey
Differentcreditprovidersdenycustomerscredit forvariousreasons. The survey results indicate that banks mainlydeniedpotentialborrowerscreditonlackofcollateralat20.9percent.Saccocustomers,ontheotherhand,weredeniedcredit on account of failure to clear outstanding loans. Mobile money,mobilebankinganddigitalloanappsprovidersdenycustomers credit on abador no credit history,whileMFIsmainly deny customers credit who have no guarantor. For thoseusinggroups,themainreasonforbeingdeniedcredit
arelowsavingsat26percent.
Reasons for non-use by provider
Amongthe leading reasonscited for lackofusingbanks isthelackofaffordabilityorfinancialsituationofhouseholds,with the highest score at 77 percent. Formobile banking,most people prefer not to use it for their own reasons (Figure 3.25).
Figure 3.25: Top reasons for non-use by provider (%)
Banks Sacco Mobile money Mobile banking
Financial situation/ affordability 76.7 9.9 0.5 1.1
Service charges 1.3 1.2 37.7 13.7
Convenience/ Service quality 2.0 6.3 1.0 0.7
Risk of use 1.2 1.6 2.2
Preference 11.5 27.5 21.4 64.3
Eligibility & Identification requirements 3.2 2.8 16.4 5.3
Literacy 2.1 3.4 0.6 3.1
Trust 0.7 15.1
Account/ device 18.3 5.7
N/A 0-20% 21-49% 50%andabove
2019 FinAccess Household Survey 33
3.8.4 Insurance, pensions and investments usage
SurveyfindingsshowasignificantuptakeinNHIFdrivenbygovernmentpolicyonuniversalhealthcare(Figure 3.26).However,investments insecurities, sharesandmutual funds,despite innovationssuchasM-Akiba recordedasteepdecline requiringadeeper analysis.
Figure 3.26: Use of insurance, pension and investments providers (%)
40.5
25.3
8.9 7.65.1 4 3.7
05
1015202530354045
Safe/secure Easy to put money in/
convenient
Can access in an emergency
When I save here, I can get
credit
When I save here, I can get a
lump-sum at the end of a
period
Confidential/no one knows you
have money
Most trusted
4.2
11.6
3.7
10.9
12.5 12.2
4.9 5.8 6.1 6 5.5
2.7 2.9
2006 2009 2013 2016 2019
NHIF Investments Pension (excl. NSSF) Insurance (regulated by IRA) NSSF
26.1
21.2
15.6
9.6
3.23.2
10.3
3.2
11.4
85.6 85.5 81.068.8
60.4 60.0 56.6
11.0 4.2 11.417.2
14.329.8 31.9
3.1 10.3 7.5 14.025.4
10.2 11.5
0
10
20
30
40
50
60
70
80
90
100
Medical (not NHIF)
Car Insurance NHIF Education Insurance
House Insurance
Other Insurance
Crop Insurance
In own name Jointly In someone else’s name
3.13
35.1
19.315.5
6.1 4.0 3.5 2.5 2.2
11.7
0.0
5.0
10.0
15.0
20.0
25.0
30.0
35.0
40.0
No money to Save No regular Income Other Options thana bank
No ID/Passport OthersReasons:
11.7
Most of the insurance products are directly owned by the individuals (Figure 3.27)
Figure 3.27: Ownership of insurance products by category, 2019 (%)
40.5
25.3
8.9 7.65.1 4 3.7
05
1015202530354045
Safe/secure Easy to put money in/
convenient
Can access in an emergency
When I save here, I can get
credit
When I save here, I can get a
lump-sum at the end of a
period
Confidential/no one knows you
have money
Most trusted
4.2
11.6
3.7
10.9
12.5 12.2
4.9 5.8 6.1 6 5.5
2.7 2.9
2006 2009 2013 2016 2019
NHIF Investments Pension (excl. NSSF) Insurance (regulated by IRA) NSSF
26.1
21.2
15.6
9.6
3.23.2
10.3
3.2
11.4
85.6 85.5 81.068.8
60.4 60.0 56.6
11.0 4.2 11.417.2
14.329.8 31.9
3.1 10.3 7.5 14.025.4
10.2 11.5
0
10
20
30
40
50
60
70
80
90
100
Medical (not NHIF)
Car Insurance NHIF Education Insurance
House Insurance
Other Insurance
Crop Insurance
In own name Jointly In someone else’s name
3.13
35.1
19.315.5
6.1 4.0 3.5 2.5 2.2
11.7
0.0
5.0
10.0
15.0
20.0
25.0
30.0
35.0
40.0
No money to Save No regular Income Other Options thana bank
No ID/Passport OthersReasons:
11.7
34 2019 FinAccess Household Survey
The inability toafford insurancehasbeencitedas themain reasonas towhymostKenyans lack insurancecover in2019ascomparedto2016wherethemajorreasonwaslackofunderstandinginsuranceproducts(Figure 3.28).
Figure 3.28: Top reasons for lack of insurance (%)
A majority of respondents indicated that the cost of insurance premium is the main reason for choosing insurance products (Figure 3.29).
Figure 3.29: Reasons for choosing an insurance policy (%)
53.9
40.9
12.09.2
60504030201000
Others Do not know about insurance
Would like to have but cannot afford
Do not know where to get it
Do not see the benefits
2019
2016
2019 FinAccess Household Survey 35
Mobilemoneyhasemergedasadominantchannelforpayinginsurancepremiums,especiallyinruralareas(Figure 3.30).
Figure 3.30: Channels for paying insurance premiums (%)
25.7
24.3
19.3
7.9
8.9
3.9
3.1
0.0 5.0 10.0 15.0 20.0 25.0 30.0
Lowest Cost of premiums
Level of cover / benefit it offers
Recommended by family /friend/colleague
Reputation/brand/advertisement of company
Employer / Government choice
It was the only policy that I knew
The agent convinced me
31.1
33.4
36.3
29.0
21.5
23.9
23.8
21.4
1.8
0.4
0.40
1.8
8.9
6.7
9.6
6.7
34.4
31.7
25.8
39.1
0.00 10.00 20.00 30.00 40.00 50.00 60.00 70.00 80.00 90.00 100.00
Male
Female
Rural
Urban
Mobile money Cash Cheque Account transfer/ Standing order Employer pays
0.0
10.0
20.0
30.0
40.0
50.0
60.0
70.0
80.0
90.0
100.0
Bank Transfer Mobile money account Cash Pay bill/Till No.
pay monthly bills
Pay school fees
Paid Government
Paid Pension
Paid Daily Expenses
Sent/Gave money inside Kenya
Sent money outside Kenya
Received money from inside Kenya
Received money from outside Kenya
Paid for Assets
Slightly over 30 percent of the respondents cited lack of money, as the main reason why they cannot invest in securities (Figure 3.31).
Figure 3.31: Reasons for not investing in securities (%)
1.0
1.1
1.2
1.6
2.0
9.9
10.0
21.6
21.9
Contacted by third parties
Being unbale to get to an agent
Unexpected charges
Unclear transaction charges/fees
Difficulty operating the phone
Lost money/wrongly sent money
Agent float unavailability
Service system downtime
Fraud/ Attempted fraud
0.9
0.9
1.6
1.9
5.1
5.3
11
20.6
22.7
30.2
You need an ID and/or a referee to invest
I have better option to invest in instead of securities
I do not like taking risk in the securities market
I don’t trust securities markets and stockbrokers
It’s too complicated
Other
I don’t need to invest
Don’t understand how invest in securities
I have never heard of securities markets
I don't have the kind of money
36 2019 FinAccess Household Survey
3.8.5 Transactions usage
The most used device for undertaking transactions iscash. Cash is used widely for daily expenses, monthlybills payments, fee payments, sent or receive money andpurchase of assets (Figure 3.32).
It is closely followed by use of mobile money account. Use
of other devices, such as bus or matatus, courier, moneytransfer services, international mobile transfers, Hawala,postoffice,mobilebanking,credit/debitcards,chequesorin-kind,had lessthan1percentusageacrossamajorityofuses.
Figure 3.32: Top four transactions instruments and purpose in 2019 (%)
25.7
24.3
19.3
7.9
8.9
3.9
3.1
0.0 5.0 10.0 15.0 20.0 25.0 30.0
Lowest Cost of premiums
Level of cover / benefit it offers
Recommended by family /friend/colleague
Reputation/brand/advertisement of company
Employer / Government choice
It was the only policy that I knew
The agent convinced me
31.1
33.4
36.3
29.0
21.5
23.9
23.8
21.4
1.8
0.4
0.40
1.8
8.9
6.7
9.6
6.7
34.4
31.7
25.8
39.1
0.00 10.00 20.00 30.00 40.00 50.00 60.00 70.00 80.00 90.00 100.00
Male
Female
Rural
Urban
Mobile money Cash Cheque Account transfer/ Standing order Employer pays
0.0
10.0
20.0
30.0
40.0
50.0
60.0
70.0
80.0
90.0
100.0
Bank Transfer Mobile money account Cash Pay bill/Till No.
pay monthly bills
Pay school fees
Paid Government
Paid Pension
Paid Daily Expenses
Sent/Gave money inside Kenya
Sent money outside Kenya
Received money from inside Kenya
Received money from outside Kenya
Paid for Assets
UgandaandTanzaniaaccountedforthelargestdestinationsofmoneysentoutofKenya.ThismightbeattributedtomanycitizensofthosecountrieswhoworkinKenyaordobusinessinKenyaandremitmoneybackhome.(Table 3.5).
Table 3.5: Top eight countries from where money sent or received (%)
Country Destination Country Origin
Uganda 24.0 United States of America 34.0
Tanzania 12.1 Uganda 9.2
United States of America 10.0 United Arab Emirates 8.4
Australia 7.9 Qatar 7.1
UK&NorthernIreland 3.4 Germany 6.0
India 3.4 UK&NorthernIreland 6.0
Canada 3.3 Tanzania 2.1
Rwanda 2.8 Saudi Arabia 2.4
United Arab Emirates 2.3 Canada 1.9
The U.S is the main source of remittances to Kenya,signifying the large population living and working in the U.S.Other significant sources ofremittancesareUganda,MiddleEast and Europe.
2019 FinAccess Household Survey 37
3.8.6 Mobile money usage
Mobile money was mainly used for deposits and withdrawals and safe keeping (Figure 3.33). Safekeeping money andpurchase of airtime followed.
Figure 3.33: Purpose having mobile money (%)
Fraud and system downtime were reported as the main challenges that face users (Figure 3.34).
Figure 3.34: Challenges in use of mobile money
1.0
1.1
1.2
1.6
2.0
9.9
10.0
21.6
21.9
Contacted by third parties
Being unbale to get to an agent
Unexpected charges
Unclear transaction charges/fees
Difficulty operating the phone
Lost money/wrongly sent money
Agent float unavailability
Service system downtime
Fraud/ Attempted fraud
0.9
0.9
1.6
1.9
5.1
5.3
11
20.6
22.7
30.2
You need an ID and/or a referee to invest
I have better option to invest in instead of securities
I do not like taking risk in the securities market
I don’t trust securities markets and stockbrokers
It’s too complicated
Other
I don’t need to invest
Don’t understand how invest in securities
I have never heard of securities markets
I don't have the kind of money
27.0
22.6
41.0
4.9
0.9
1.6 1.9
Summary Conclusion
� Usage of financial services and products vary across providers. While the use of banks, mobile money, NHIF and digital apps loans increased, the use of insurance, Saccos, MFIs, investment and pension products declined in 2019 compared to 2016.
� The narrowing gap between sexes, residence and education level reflects the expansion in inclusion.
� The digital transformation noted in mobile banking and digital apps space raises cyber security, credit risk and consumer protection concerns.
� It is essential that policy makers and regulators pay attention to barriers and reasons that limit access to a wide range of financial service providers and products in order to come up with customer-centric solutions.
38 2019 FinAccess Household Survey
Building a consumer centric inclusive financial system
KSH
2019 FinAccess Household Survey 39
04
Consumers have different goals and needs in life be they in their daily lives or for the future. Finance can play a significant role in attaining these human desired life outcomes and impact. This is the essence of building a financial system that works for Kenyans. The goal of financial inclusion is to have a financial system that drives the use of financial solutions.
Financeplaysasignificant role inattainingouraspirationsand needs. Most measures of financial inclusion havefocused on financial service providers and products withminimal attention on their relevance in meeting consumer needs.
The needs-based measurement framework reverses thistraditional approach by focussing on consumer needs. This
isinrecognitionthatusersdonotthinkintermsofproducts;theythinkintermsofneeds.
4.1 The biggest priority
This section gives an overview of the biggest priority in the livesofKenyans,andindicatesdifferencesinprioritiesbasedoneducation,wealth,sexandresidence.
4.1.1 Biggest priority by education level
EducationistheleadinglifegoalforKenyans,cuttingacrossincomegroups.IthighlightshowKenyansvieweducationasameanstoaccessopportunities(upwardmobility)andsocialstatus.Kenyanswithnoeducationprioritizeputtingfoodonthetableasthemain goal at 41.7 percent (Figure 4.1).
Figure 4.1: Biggest priority by level of education
35.5
30.6 33
.8
38.9
38.2
28.5
41.7
32.5
23.0
15.9
16.1
9.7
15.3 17
.9 21.1
13.2
11.5
11.8 14
17.0
5.1
3.3 5.
2
5.2 5.9
0.8 2.
1
0.7
0.4 0.8
0
5
10
15
20
25
30
35
40
45
National None Primary Secondary Tertiary
Educating yourself or your family Putting food on the table Improving your business/farm, or developing your career
Health (yourself or family/ others) Buying land/ Building a house/improving your house Buying assets (e.g. TV, refrigerator, livestock)
35.9
35.1
37.0
33.0
26.6
30.4
32.4
23.0
17.8
14.5
14.1
19.0
12.7
13.8
11.2
16.0
5.6
4.6
3.6 7.
0
0.6
0.9
0.9
1.0
0 5
10 15 20 25 30 35 40
Male Female Rural Urban
Educating yourself or your family Putting food on the table Improving your business/farm, or developing your career
Health (yourself or family/ others) Buying land/ Building a house/improving your house Buying assets (e.g. TV, refrigerator, livestock)
37.3
37.1
9.7
10.4
3.4
1.3
35.7
34.0
12.8
10.3
5.0
1.0
33.7
27.1
18.9
13.7
4.9
0.5
35.0
21.9
21.2
14.8
6.0
0.8
35.5
19.7
19.8
18.1
6.3
0.3
Educating yourself or your family
Putting food on the table
Improving your business/farm, or developing your
career
Health (yourself or family/others)
Buying land/ Building a house/improving your
house
Buying assets (e.g. TV, refrigerator,livestock)
Lowest Second Lowest Middle Second Highest Highest
62.1
36.2
59.2
Meeting day to day needs
Experienced shocks
Meeting future goals
finAnCiAL ReLeVAnCe
40 2019 FinAccess Household Survey
4.1.2 Biggest priority by wealth quintile
Educating self or family members is the main goal for majority of Kenyans regardless of their wealth quintile status. Thesecondmostimportantlifegoalshiftsfrombeingabletocover
basics (i.e. food) to improving livelihoods as income increases. Kenyan population in the lowest wealth quintile prioritizeshealth as their 3rd main goal compared to the population in all the other quintiles where health is the 4th main life goal (Figure 4.2).
Figure 4.2: Biggest priority by wealth quintile
35.5
30.6 33
.8
38.9
38.2
28.5
41.7
32.5
23.0
15.9
16.1
9.7
15.3 17
.9 21.1
13.2
11.5
11.8 14
17.0
5.1
3.3 5.
2
5.2 5.9
0.8 2.
1
0.7
0.4 0.8
0
5
10
15
20
25
30
35
40
45
National None Primary Secondary Tertiary
Educating yourself or your family Putting food on the table Improving your business/farm, or developing your career
Health (yourself or family/ others) Buying land/ Building a house/improving your house Buying assets (e.g. TV, refrigerator, livestock)
35.9
35.1
37.0
33.0
26.6
30.4
32.4
23.0
17.8
14.5
14.1
19.0
12.7
13.8
11.2
16.0
5.6
4.6
3.6 7.
0
0.6 0.9
0.9
1.0
0 5
10 15 20 25 30 35 40
Male Female Rural Urban
Educating yourself or your family Putting food on the table Improving your business/farm, or developing your career
Health (yourself or family/ others) Buying land/ Building a house/improving your house Buying assets (e.g. TV, refrigerator, livestock)
37.3
37.1
9.7 10.4
3.4 1.3
35.7
34.0
12.8
10.3
5.0
1.0
33.7
27.1
18.9
13.7
4.9
0.5
35.0
21.9
21.2
14.8
6.0
0.8
35.5
19.7
19.8
18.1
6.3
0.3
Educating yourself or your family
Putting food on the table
Improving your business/farm, or developing your
career
Health (yourself or family/others)
Buying land/ Building a house/improving your
house
Buying assets (e.g. TV, refrigerator,livestock)
Lowest Second Lowest Middle Second Highest Highest
62.1
36.2
59.2
Meeting day to day needs
Experienced shocks
Meeting future goals4.1.3 Biggest priority by sex and residence
Womenareslightlymoreconcernedaboutfood,whilemenare slightly more concerned about livelihood (business/farming etc). There are however significant differences
between urban and rural residents in putting food on the table, health and improving livelihoods. Rural residentsprioritizefood,whileurbanresidentsputprioritiesonbetterhealth and improved livelihood (Figure 4.3).
Figure 4.3: Biggest priority by sex and residence
35.5
30.6 33
.8
38.9
38.2
28.5
41.7
32.5
23.0
15.9
16.1
9.7
15.3 17
.9 21.1
13.2
11.5
11.8 14
17.0
5.1
3.3 5.
2
5.2 5.9
0.8 2.
1
0.7
0.4 0.8
0
5
10
15
20
25
30
35
40
45
National None Primary Secondary Tertiary
Educating yourself or your family Putting food on the table Improving your business/farm, or developing your career
Health (yourself or family/ others) Buying land/ Building a house/improving your house Buying assets (e.g. TV, refrigerator, livestock)
35.9
35.1
37.0
33.0
26.6
30.4
32.4
23.0
17.8
14.5
14.1
19.0
12.7
13.8
11.2
16.0
5.6
4.6
3.6 7.
0
0.6
0.9
0.9
1.0
0 5
10 15 20 25 30 35 40
Male Female Rural Urban
Educating yourself or your family Putting food on the table Improving your business/farm, or developing your career
Health (yourself or family/ others) Buying land/ Building a house/improving your house Buying assets (e.g. TV, refrigerator, livestock)
37.3
37.1
9.7
10.4
3.4
1.3
35.7
34.0
12.8
10.3
5.0
1.0
33.7
27.1
18.9
13.7
4.9
0.5
35.0
21.9
21.2
14.8
6.0
0.8
35.5
19.7
19.8
18.1
6.3
0.3
Educating yourself or your family
Putting food on the table
Improving your business/farm, or developing your
career
Health (yourself or family/others)
Buying land/ Building a house/improving your
house
Buying assets (e.g. TV, refrigerator,livestock)
Lowest Second Lowest Middle Second Highest Highest
62.1
36.2
59.2
Meeting day to day needs
Experienced shocks
Meeting future goals
2019 FinAccess Household Survey 41
4.2 The Needs-based Framework
Consumerschoosefinancialservicesandproductsbasedontheirneeds,whicharereflectedintheiruseofavailablesolutionseitherformaland/orinformal.ThissectionexplorestheneedsofKenyansanddemonstrateswhatfinancialsolutionstheyrelyon.The needs are summarised as follows;
� liquidity or meeting day to day needs: People’sability to meet expenses in each income cycle. It is essential for survival and to maintain productive capacity through meeting day to day needs
� resilience/dealing with shocks: Resilience refers to theability todealwithunexpectedshocks thathaveafinancialimpact
� Meeting future goals: The extent to which individuals utilisefinancialservicestomeetforeseeable,desiredlifeobjectives
4.2.1 Financial needs
Thesurveyresultsindicatethat62.1percentofKenyanswereunable to meet their daily expenses in each income cycle. Aboutathird(36.2%)ofthemhavebeenfacedwithashockinthepasttwelvemonths.Theresultsalsoindicatethat59percentofKenyansareworkingtowardsmeetingtheirfuturegoals (Figure 4.4).
Figure 4.4: Proportion of adults mentioningafinancialneed(%)
35.5
30.6 33
.8
38.9
38.2
28.5
41.7
32.5
23.0
15.9
16.1
9.7
15.3 17
.9 21.1
13.2
11.5
11.8 14
17.0
5.1
3.3 5.
2
5.2 5.9
0.8 2.
1
0.7
0.4 0.8
0
5
10
15
20
25
30
35
40
45
National None Primary Secondary Tertiary
Educating yourself or your family Putting food on the table Improving your business/farm, or developing your career
Health (yourself or family/ others) Buying land/ Building a house/improving your house Buying assets (e.g. TV, refrigerator, livestock)
35.9
35.1
37.0
33.0
26.6
30.4
32.4
23.0
17.8
14.5
14.1
19.0
12.7
13.8
11.2
16.0
5.6
4.6
3.6 7.
0
0.6 0.9
0.9
1.0
0 5
10 15 20 25 30 35 40
Male Female Rural Urban
Educating yourself or your family Putting food on the table Improving your business/farm, or developing your career
Health (yourself or family/ others) Buying land/ Building a house/improving your house Buying assets (e.g. TV, refrigerator, livestock)
37.3
37.1
9.7
10.4
3.4
1.3
35.7
34.0
12.8
10.3
5.0
1.0
33.7
27.1
18.9
13.7
4.9
0.5
35.0
21.9
21.2
14.8
6.0
0.8
35.5
19.7
19.8
18.1
6.3
0.3
Educating yourself or your family
Putting food on the table
Improving your business/farm, or developing your
career
Health (yourself or family/others)
Buying land/ Building a house/improving your
house
Buying assets (e.g. TV, refrigerator,livestock)
Lowest Second Lowest Middle Second Highest Highest
62.1
36.2
59.2
Meeting day to day needs
Experienced shocks
Meeting future goals
Meetingday-to-dayneedsandkeepingmoneyasidetomeetfuture goals is determined by the socio-economic statusand the resilience of the source of income (employed/runown business are more stable sources than agriculture and casuallabour).Ontheotherhand,shocksaffectallinsimilarmagnitude (Figure 4.5).
Figure 4.5: Needs by livelihood sources and wealth quintiles (%)
Meeting day to day needs
75.0
37.9
46.2
67.3
39.2
56.563
.8
37.9
61.6
53.7
32.7
66.2
46.5
32.5
68.5
Meeting day to day needs
Experienced shocks Meeting future goals
Lowest Second Lowest Middle Second Highest Highest
72.2
34.9
59.864
.6
33.9
47.3
60.2
40.1
50.356
.4
37.0
73.3
52.3
33.4
74.1
Experienced shocks Meeting future goals
Casual Dependent Agriculture Own business Employed
55.4
20.1
3.7
13.2
3.1 3.6
58.9
8.63.4
19.0
3.8 4.4
0.0
10.0
20.0
30.0
40.0
50.0
60.0
70.0
Major sickness/accident injury
Loss/damage of business/livestock or crop because ofnatural disasters
Death of income earner
Death of a family member or relative
Loss/damage of major asset/
money because of theft or other human
causes
Child birth
RuralUrban
.8
1.3
1.8
2.2
2.9
7.3
9.4
12.7
18.1
45.4
.0 5.0 10.0 15.0 20.0 25.0 30.0 35.0 40.0 45.0 50.0
Shylock loan
Government loan
Cash loan from shopkeeper
Bank loan
SACCO loan
Chama loan
Digital App loans
Loan from friends and family
Mobile bank loan
Goods/services on credit from shopkeeper
42 2019 FinAccess Household Survey
Shocks
Themost commonshock thatfinancially impactedmostKenyanswashealth related,withnomajordistinctionbetween thewealthquintiles.However,theimpactwasmorefeltamongthepoorest.Deathofafamilymemberimpactedtherichmorethanthe poor (Figure 4.6).
Figure 4.6: Shocks experienced by wealth quintile and livelihood (%)
Meeting day to day needs
75.0
37.9
46.2
67.3
39.2
56.563
.8
37.9
61.6
53.7
32.7
66.2
46.5
32.5
68.5
Meeting day to day needs
Experienced shocks Meeting future goals
Lowest Second Lowest Middle Second Highest Highest
72.2
34.9
59.864
.6
33.9
47.3
60.2
40.1
50.356
.4
37.0
73.3
52.3
33.4
74.1
Experienced shocks Meeting future goals
Casual Dependent Agriculture Own business Employed
55.4
20.1
3.7
13.2
3.1 3.6
58.9
8.63.4
19.0
3.8 4.4
0.0
10.0
20.0
30.0
40.0
50.0
60.0
70.0
Major sickness/accident injury
Loss/damage of business/livestock or crop because ofnatural disasters
Death of income earner
Death of a family member or relative
Loss/damage of major asset/
money because of theft or other human
causes
Child birth
RuralUrban
.8
1.3
1.8
2.2
2.9
7.3
9.4
12.7
18.1
45.4
.0 5.0 10.0 15.0 20.0 25.0 30.0 35.0 40.0 45.0 50.0
Shylock loan
Government loan
Cash loan from shopkeeper
Bank loan
SACCO loan
Chama loan
Digital App loans
Loan from friends and family
Mobile bank loan
Goods/services on credit from shopkeeper
Ruralhouseholdsweremostfinancially impactedby the lossof livelihoods,whileurbanhouseholds felt thedeathofa familymemberimpactedontheirfinancesmost(Figure 4.7).
Figure 4.7: Shocks experienced by residence (%)
Meeting day to day needs
75.0
37.9
46.2
67.3
39.2
56.563
.8
37.9
61.6
53.7
32.7
66.2
46.5
32.5
68.5
Meeting day to day needs
Experienced shocks Meeting future goals
Lowest Second Lowest Middle Second Highest Highest
72.2
34.9
59.864
.6
33.9
47.3
60.2
40.1
50.356
.4
37.0
73.3
52.3
33.4
74.1
Experienced shocks Meeting future goals
Casual Dependent Agriculture Own business Employed
55.4
20.1
3.7
13.2
3.1 3.6
58.9
8.63.4
19.0
3.8 4.4
0.0
10.0
20.0
30.0
40.0
50.0
60.0
70.0
Major sickness/accident injury
Loss/damage of business/livestock or crop because ofnatural disasters
Death of income earner
Death of a family member or relative
Loss/damage of major asset/
money because of theft or other human
causes
Child birth
RuralUrban
.8
1.3
1.8
2.2
2.9
7.3
9.4
12.7
18.1
45.4
.0 5.0 10.0 15.0 20.0 25.0 30.0 35.0 40.0 45.0 50.0
Shylock loan
Government loan
Cash loan from shopkeeper
Bank loan
SACCO loan
Chama loan
Digital App loans
Loan from friends and family
Mobile bank loan
Goods/services on credit from shopkeeper
2019 FinAccess Household Survey 43
Goals
Themaingoalforthehighestwealthquintileisexpandingbusinesses,whilethelowestwealthquintileiseducation(Figure 4.8).
Figure 4.8: Most important future goal by wealth quintile (%)
1.0
1.0
2.0
7.1
9.7
19.2
28.0
28.9
2.6
0.5
4.7
5.1
18.0
17.6
31.0
17.7
Buy or pay for things for personal use
Improve house
Buy or build a house / apartment for renting or re-sale
Buy inputs / assets for business / agricultural activities
Buy land
Buy or build a house / apartment to live in
Start or expand a business
Education for self or family
Richest (20%)Poorest (60%)
4.8
4.9
33.7
33.1
13.1
10.0
3.0
34.7
15.4 19
.4
16.3
5.1
28.5
26.0
18.8
14.6
5.3
20.8
27.9
17.4
13.7
11.9
19.3 23
.3 25.5
8.8 10
.4
Start or expand a business Education for self or family Buy or build a house /apartment to live in
Buy land Buy inputs / assets forbusiness/agriculture
18 - 25 years 26 - 35 years 36 - 45 years 46 - 55 years Over 55 years
NB: others include paying for holidays, weddings, clearing debts, getting employment
The young adults aged below 35 years cited starting a business or education as their important life goal. For the population above 55yearsold,theirmaingoalisowningahouse(Figure 4.9).
Figure 4.9: Most important future goal by age (%)
1.0
1.0
2.0
7.1
9.7
19.2
28.0
28.9
2.6
0.5
4.7
5.1
18.0
17.6
31.0
17.7
Buy or pay for things for personal use
Improve house
Buy or build a house / apartment for renting or re-sale
Buy inputs / assets for business / agricultural activities
Buy land
Buy or build a house / apartment to live in
Start or expand a business
Education for self or family
Richest (20%)Poorest (60%)
4.8
4.9
33.7
33.1
13.1
10.0
3.0
34.7
15.4 19
.4
16.3
5.1
28.5
26.0
18.8
14.6
5.3
20.8
27.9
17.4
13.7
11.9
19.3 23
.3 25.5
8.8 10
.4
Start or expand a business Education for self or family Buy or build a house /apartment to live in
Buy land Buy inputs / assets forbusiness/agriculture
18 - 25 years 26 - 35 years 36 - 45 years 46 - 55 years Over 55 years
NB: others include paying for holidays, weddings, clearing debts, getting employment
44 2019 FinAccess Household Survey
4.2.2 Financial solutions used
Social networks are the main solutions to meeting dayto day needs when the income cycle gets depleted before theendofthecycleandalsodealingwithshocksformost
Kenyans. Formal solutions aremainly used tomeet futuregoals though gettingmore jobs/cutting back on expensesare more commonly done to achieve these (Figure 4.10).
Figure 4.10: Financial solutions used towards meeting financial needs
36.050.2
33.1
17.0 17.7
9.9
14.9
2.82.4 2.0
10.9
0.2
13.3
15.7
26.8
29.0
12.0
2.0 4.0
Future goal device Dealing with shocks device Meeting day to day needs devices
Classifications
social networks Borrow from friends and family
personal Sellassets/livestock/poultry,getadditionalwork,cutbackonexpenses
Formal Usesavingsorborrowfromformalinstitutionssuchasbanks/MFIs/SACCOs,excludinginsurance
informal Borroworsavingsfrominformalproviderssuchasshylocks,chama,employers,shopkeeper,secrethiding place
2019 FinAccess Household Survey 45
Solutions for day-to-day needs
FriendsandfamilyarethemainfinancialsolutionsusedbymajorityofKenyanswhentheyrunoutofmoneytomeettheirday-to-dayneeds(Figure 4.11).
Figure 4.11: Financial solutions used towards meeting day to day needs (%)
0.10.40.40.60.8
1.41.41.61.82.0
2.52.82.8
3.73.9
5.85.9
6.56.5
10.913.1
24.7
Loan from shylock Loan from digital app
Sell cropsA loan / advance from my employer
Sold other assets, not livestock Loan from mobile banking
Loan from a bank / Sacco / MFI Savings in mobile banking
Savings with friends / family Savings in group / chama
Goods/items on credit Loan from group / chama
Savings at bank / Sacco / MFI Secret hiding place
Shopkeeper creditSavings in mobile money
Sold livestockLoan from friends and family
Cut back on expenses Did nothing
Worked moreHelp from friends and family
42.8
20.1
12.37.9 7.7
3.4 3.8 1.9
38.2
19.0
7.5
16.1
3.5 5.4 3.26.8
Borrow Informally Working More/Additional Jobs/
Cut Expenses
Do Nothing Save Formally Selling /Liquidation of
Assets
Save Informally Secret Hiding Place
Borrow Formally
Poorest 60% of KenyansWealthiest 40% of Kenyans
35.3
22.6
9.6 13
.9
7.2
3.5
3.4 4.3
46.9
17.1
12.2
6.9
6.3
4.2
4.0
2.2
Male Female
Borrow Informally
Working More/Additional Jobs/Cut Expenses
Did Nothing Save Formally Selling /Liquidation
of Assets
Save Informally
Secret Hiding Place
Borrow Formally
Useof informal solutions fordealingwithday-to-dayneedswhenmoney runsoutcutsacross thewealthquintiles.However,formal solutions are mainly used by the highest wealth quintile (Figure 4.12)
Figure 4.12: Solutions for day-to-day needs by wealth quintile (%)
0.10.40.40.60.8
1.41.41.61.82.0
2.52.82.8
3.73.9
5.85.9
6.56.5
10.913.1
24.7
Loan from shylock Loan from digital app
Sell cropsA loan / advance from my employer
Sold other assets, not livestock Loan from mobile banking
Loan from a bank / Sacco / MFI Savings in mobile banking
Savings with friends / family Savings in group / chama
Goods/items on credit Loan from group / chama
Savings at bank / Sacco / MFI Secret hiding place
Shopkeeper creditSavings in mobile money
Sold livestockLoan from friends and family
Cut back on expenses Did nothing
Worked moreHelp from friends and family
42.8
20.1
12.37.9 7.7
3.4 3.8 1.9
38.2
19.0
7.5
16.1
3.5 5.4 3.26.8
Borrow Informally Working More/Additional Jobs/
Cut Expenses
Do Nothing Save Formally Selling /Liquidation of
Assets
Save Informally Secret Hiding Place
Borrow Formally
Poorest 60% of KenyansWealthiest 40% of Kenyans
35.3
22.6
9.6 13
.9
7.2
3.5
3.4 4.3
46.9
17.1
12.2
6.9
6.3
4.2
4.0
2.2
Male Female
Borrow Informally
Working More/Additional Jobs/Cut Expenses
Did Nothing Save Formally Selling /Liquidation
of Assets
Save Informally
Secret Hiding Place
Borrow Formally
46 2019 FinAccess Household Survey
Thesurveyresultsindicatethatmorewomenthanmenuseinformalsolutionscomparedtotheuseofformal,whichisdominatedby men (Figure 4.13).
Figure4.13:Solutionsforday-to-dayneedsbysex(%)
0.10.40.40.60.8
1.41.41.61.82.0
2.52.82.8
3.73.9
5.85.9
6.56.5
10.913.1
24.7
Loan from shylock Loan from digital app
Sell cropsA loan / advance from my employer
Sold other assets, not livestock Loan from mobile banking
Loan from a bank / Sacco / MFI Savings in mobile banking
Savings with friends / family Savings in group / chama
Goods/items on credit Loan from group / chama
Savings at bank / Sacco / MFI Secret hiding place
Shopkeeper creditSavings in mobile money
Sold livestockLoan from friends and family
Cut back on expenses Did nothing
Worked moreHelp from friends and family
42.8
20.1
12.37.9 7.7
3.4 3.8 1.9
38.2
19.0
7.5
16.1
3.5 5.4 3.26.8
Borrow Informally Working More/Additional Jobs/
Cut Expenses
Do Nothing Save Formally Selling /Liquidation of
Assets
Save Informally Secret Hiding Place
Borrow Formally
Poorest 60% of KenyansWealthiest 40% of Kenyans
35.3
22.6
9.6 13
.9
7.2
3.5
3.4 4.3
46.9
17.1
12.2
6.9
6.3
4.2
4.0
2.2
Male Female
Borrow Informally
Working More/Additional Jobs/Cut Expenses
Did Nothing Save Formally Selling /Liquidation
of Assets
Save Informally
Secret Hiding Place
Borrow Formally
Solutions for dealing with shocks
ThesurveyoutcomesshowthatmorethanhalfofKenyansreportedrelyingonfriendsandfamily(socialnetworks)tomitigateshocksandemergencies(Figure 4.14).
Figure 4.14: solutions for dealing with shocks (%)
2019 FinAccess Household Survey 47
Solutions for future goals
The2019surveyresultsrevealedthatKenyansareusedifferentdevices/instrumentstomeettheirfuturegoals.Specifically,banks/Sacco/MFIloansandsavingswereusedforbuylandandotherassets,andconstructionofahouse(Figure 4.15).
Figure 4.15: Solutions for meeting future goals
1.5
1.5
1.6
2.0
2.4
2.4
2.4
2.7
2.9
3.3
5.2
5.5
5.6
6.4
6.6
43.0
Savings with friends / family
Loan from a bank / Sacco / MFI
Savings at mobile banking
Insurance
Savings at a group / chama
Loan from group / chama
Did nothing
Sold other assets, not livestock
Cut back on expenses
Secret hiding place
Savings at mobile money
Worked more
Loan from friends and family
Savings at a bank / Sacco /MFI
Sold livestock
Help friends and family
24.9 18.7 33.1 42.8 38.9
26.0
23.9 26.9
28.8 11.5 24.2
17.1
17 19
13 20
14
19
16.7 10.3 7.7 14.8 4.0
3.5
11.5 11.5 3.9 3.2 11.2
9.4
2.9 3.2 4.4 4.9 1.0
12.1
Start or expand a business
Education for self or family
Buy or build a house / apartment
to live in
Buy land Buy inputs / assets for business and /or agriculture
Buy or build a house / apartmentfor rent or resale
Bank/SACCO/MFI Mobile money savings
Chama/savings group Mobile bank
Friends/family Worked more / got additional jobs
40.2 40.0
7.0 5.9 3.6 2.2
48.2
33.6
5.6 7.0 1.9 2.4
9.5
51.9
16.3 12.4
.9 6.4
No choice/only option available/
required by group
Fast/easy to access
Feel most comfortable/trust
Reliable/funds will beavailable
Privacy Cheap/affordable/lowest fees
Meeting day to day needs Dealing with shocks Investing for the future
4.3 Selectionofsolutionsforafinancialneed
ThesurveyresultsshowthattheeaseofaccesstofinancialservicesandproductsisthemainfactordeterminingtheselectionofasolutionbymostKenyans(Figure 4.16)
Figure 4.16: Reasons for selecting day to day financial need solutions (%)
1.5
1.5
1.6
2.0
2.4
2.4
2.4
2.7
2.9
3.3
5.2
5.5
5.6
6.4
6.6
43.0
Savings with friends / family
Loan from a bank / Sacco / MFI
Savings at mobile banking
Insurance
Savings at a group / chama
Loan from group / chama
Did nothing
Sold other assets, not livestock
Cut back on expenses
Secret hiding place
Savings at mobile money
Worked more
Loan from friends and family
Savings at a bank / Sacco /MFI
Sold livestock
Help friends and family
24.9 18.7 33.1 42.8 38.9
26.0
23.9 26.9
28.8 11.5 24.2
17.1
17 19
13 20
14
19
16.7 10.3 7.7 14.8 4.0
3.5
11.5 11.5 3.9 3.2 11.2
9.4
2.9 3.2 4.4 4.9 1.0
12.1
Start or expand a business
Education for self or family
Buy or build a house / apartment
to live in
Buy land Buy inputs / assets for business and /or agriculture
Buy or build a house / apartmentfor rent or resale
Bank/SACCO/MFI Mobile money savings
Chama/savings group Mobile bank
Friends/family Worked more / got additional jobs
40.2 40.0
7.0 5.9 3.6 2.2
48.2
33.6
5.6 7.0 1.9 2.4
9.5
51.9
16.3 12.4
.9 6.4
No choice/only option available/
required by group
Fast/easy to access
Feel most comfortable/trust
Reliable/funds will beavailable
Privacy Cheap/affordable/lowest fees
Meeting day to day needs Dealing with shocks Investing for the future
48 2019 FinAccess Household Survey
Onhoweffectivethechoiceswere,mostKenyansreportedthattheformalfinancialsolutionswereeffectiveinkeepingmoneyasidetomeetfuturegoals.Informalsavingswereconsideredasmosteffectiveinmeetingday-to-dayneeds(Figure 4.17).
Figure 4.17: Effectiveness of selected solution in meeting needs (%)
97.0
85.2
92.4
75.0
93.7
82.5
72.9
4.4 Meeting needs for business and agriculture
4.4.1 Business enterprise finance
Thesurveyquestionnairecontainedabusinessmodulewhichinquiredthefinancingofbusinessenterprisesownedbyindividualhouseholdmembers.Thesurveyresultsshowsthatbusinessenterprisesusedre-investedearnings(24.3%)asthemainsourceoffinancing,followedbyformalsavings(Figure 4.18).
Figure 4.18: Sources of operating capital for enterprises (%)
4.12
33.7
33.1
13.1
10.0
3.0
34.7
15.4 19
.4
16.3
5.1
28.5
26.0
18.8
14.6
5.3
20.8
27.9
17.4
13.7
11.9
19.3 23
.3 25.5
8.8 10
.4
0.0
5.010.0
15.020.0
25.0
30.035.0
40.0
Start or expanda business
Education for selfor family
Buy or build a house /apartment to live in
Buy land Buy inputs / assets forbusiness / agricultural activities
(e.g. tractor, machi
18 - 25 years 26 - 35 years 36 - 45 years 46 - 55 years Over 55 years
2.7
3.2
3.8
14.3
14.7
15.3
21.1
24.3
Formal borrowing
Informal borrowing
Sale of assets/crops/livestock
Personal
Social network
Informal savings
Formal savings
Reinvested earnings
4.17
4.18
40.9
28.2
9.8 9.5
4.3 4.0 2.5
36.7
14.6
20.4 19.5
1.43.5 3.8
0.0
5.0
10.0
15.0
20.0
25.0
30.0
35.0
40.0
45.0
Personal Formal savings Informal savings Social network Formal borrowing Sale of assets/crops/livestock
Informal borrowing
Male Female
2019 FinAccess Household Survey 49
Thesurveyresultsindicatethatpersonalfinancingwasthemainsourceofoperatingcapitalforbusinesseswithmales(40.9%)andfemales(36.7%)asshowninFigure 4.19.
Figure 4.19: Operating capital for business enterprise by sex (%)
4.12
33.7
33.1
13.1
10.0
3.0
34.7
15.4 19
.4
16.3
5.1
28.5
26.0
18.8
14.6
5.3
20.8
27.9
17.4
13.7
11.9
19.3 23
.3 25.5
8.8 10
.4
0.0
5.010.0
15.020.0
25.0
30.035.0
40.0
Start or expanda business
Education for selfor family
Buy or build a house /apartment to live in
Buy land Buy inputs / assets forbusiness / agricultural activities
(e.g. tractor, machi
18 - 25 years 26 - 35 years 36 - 45 years 46 - 55 years Over 55 years
2.7
3.2
3.8
14.3
14.7
15.3
21.1
24.3
Formal borrowing
Informal borrowing
Sale of assets/crops/livestock
Personal
Social network
Informal savings
Formal savings
Reinvested earnings
4.17
4.18
40.9
28.2
9.8 9.5
4.3 4.0 2.5
36.7
14.6
20.4 19.5
1.43.5 3.8
0.0
5.0
10.0
15.0
20.0
25.0
30.0
35.0
40.0
45.0
Personal Formal savings Informal savings Social network Formal borrowing Sale of assets/crops/livestock
Informal borrowing
Male Female
Social networks: Borrow from friends and familyPersonal: Sell assets/livestock/poultry, get additional work, cut back on expensesFormal: Use savings or borrow from formal institutions such as banks/MFIs/ SACCOs, excluding insuranceInformal: Borrow or savings from informal providers such as shylocks, chama, employers, shopkeeper, secret hiding place
Ease of access was the main reason cited for use of formal and informal borrowing except for loans from a government institution (Table 4.1).
However, mobile banking loans were the most popularchoice for financing business enterprises due to ease ofaccess.
Table 4.1: Reasons for formal and informal borrowing
Type of loan/Fast/
easy to access
No choice/only option/required by
group
Cheap/affordable/lowest fees
Feels most comfortable/
trustPrivacy
Reliable/I know funds
will be available
I didn’t want to use my
own money/savings /assets
Formal borrowing
loan from bank / sacco / microfinance 59.9 10.3 3.0 17.8 1.7 7.3 0.0
loan from mobile banking 100.0 0.0 0.0 0.0 0.0 0.0 0.0
loan from a government institution 0.0 0.0 0.0 0.0 0.0 45.4 54.6
informal borrowing
loan from group / chama 45.4 13.2 21.4 19.9 0.0 n/a n/a
loan from family / friends / community / church / mosque
35.8 32.9 1.0 22.5 3.1 n/a n/a
loan from a shopkeeper 66.3 0.0 0.0 33.7 0.0 n/a n/a
50 2019 FinAccess Household Survey
Majorityof loans (41.5%)sourced frombanks/Saccos/MFIswereused forpurchaseofassetsandmachineryandexpansionofbusinesses(36.7%).Loansfrommobilebankingweremainlyusedforrestockinganddiversificationofbusiness(Table 4.20).
Figure 4.20: Use of business loans by source (%)
38.8
46.4
41.5
35.9
0.0
0.0
0.0
44.4
49.0
36.7
50.8
57.6
54.6
24.7
11.8
4.5 11
.4
13.2
42.4
45.4
33.7
5.0
0.0
10.5
0.0
0.0
0.0
41.6
Total Group / chama Bank / Sacco / microfinance
Social network Mobile banking Government institution
Loan from a shopkeeper
Buying assets/machinery Expansion of business Diversification of business activities Other
94.0
Mobile money
Bank transfer (e.g. EFT, SWIFT,
Pesalink),
1.4
Bank chequeIn-kind payments ingoods and/or services
0.1 Other
Cash
3.7
0.50.3
1.8 2.
8
0.93.
4
2.8 3.
9
17.2 20
.2
14.6
10.8
8.6
12.8
22.1
14.8
28.7
18.1
23.5
13.4
20.8 22
.4
19.3
Total Male Female
Formal borrowing Informal borrowing Formal savings Informal savings Social networks Personal Sale of assets/crops/livestock
Unlikethewidespreadperceptionthatmobilemoneyiswidelyused,surveyfindingsshowthatcashisthemainpaymentchannelusedbybusinessenterprisesat94percent(Figure 4.21).
Figure 4.21: Payment mode used by businesses (%) 4.4.2 Agriculturalfinance
Financial inclusion is important for agriculture in assisting farmers purchase farm inputs,assets,mitigaterisksandmanageday-to-daycashflowneeds.
Sourcesofagriculturalfinancebysex
Themainsourcesofagriculturalfinanceweresocialnetworks(22.1%),saleofassets/crops/livestock (20.8%) and formal borrowing(18.1%)asindicatedinFigure 4.22. Sources ofagriculturalfinancebyfemaleweremainlyfromsocialnetworks(28.7%),whileformen,itsformalborrowing(23.5%).
94.0
2019 FinAccess Household Survey 51
Figure 4.22: Sources of agricultural finance (%)
38.8
46.4
41.5
35.9
0.0
0.0
0.0
44.4
49.0
36.7
50.8
57.6
54.6
24.7
11.8
4.5 11
.4
13.2
42.4
45.4
33.7
5.0
0.0
10.5
0.0
0.0
0.0
41.6
Total Group / chama Bank / Sacco / microfinance
Social network Mobile banking Government institution
Loan from a shopkeeper
Buying assets/machinery Expansion of business Diversification of business activities Other
94.0
Mobile money
Bank transfer (e.g. EFT, SWIFT,
Pesalink),
1.4
Bank chequeIn-kind payments ingoods and/or services
0.1 Other
Cash
3.7
0.50.3
1.8 2.
8
0.93.
4
2.8 3.
9
17.2 20
.2
14.6
10.8
8.6
12.8
22.1
14.8
28.7
18.1
23.5
13.4
20.8 22
.4
19.3
Total Male Female
Formal borrowing Informal borrowing Formal savings Informal savings Social networks Personal Sale of assets/crops/livestock
Agriculturalfinancepaymentmodesused
Thesurveyresultsindicatethatthemainmodesofpaymentuseinagriculturalfinancewascash(92.6%)followedbybanktransfers(2.8%)asshowninFigure 4.23.
Figure 4.23: Top Payment modes used (%)
summary and conclusion
� The top priority goal for Kenyans is education.
� Poor segments of the population and rural residents also prioritise putting food on the table. While the highest wealth quintile and urban residents prioritise improving health and business.
� Cash is a still the dominant mode of payment for agriculture and business.
Cash 92.6
Mobile Money 2.6
Banktransfer2.8 1.4 Bankcheque
0.2 Inkind Payment
52 2019 FinAccess Household Survey
05finAnCiAL HeALtH AnD LiVeLiHooDS
Financial health refers to the ability of Kenyans to use financial services for managing daily needs, protecting themselves from shocks and helping to achieve their main goals. It is measured through a multidimensional financial health index covering three
dimensions: ability to manage everyday finances, ability to cope with risk and ability to invest in livelihoods and future.
Dividends of expanding financial inclusion for enhanced financial health
2019 FinAccess Household Survey 53
The index is arrived at by summing equally weighted score of 11.3 points assigned to nine survey questions that map tothethreedimensionsoffinancialhealth.An individualisconsideredtobefinanciallyhealthyifhe/shesatisfiesat least six of the nine questions. The survey results
indicated that at the national level 21.7 percent were financially healthy in 2019 compared to 39.4 percentrecordedin2016(Figure 5.1).However,financialhealthas measured by ability to put food on the table improved from58.1percentin2016to66.6percentin2019.
Figure 5.1: Overall financial health and its dimensions, 2016 and 2019 (%)
55.3
28
62.3
66.6
36.9
64.1
19.5
41.4
21.8
33.4
17.4
22.5
21.7
63
41.8
73.5
58.1
52.4
64.6
36.8
56.4
46.5
55.7
39.6
43.7
39.4
Ability to manage day to day
Manage: no trouble making money last
Manage: plan for allocating money
Manage: never went without food
Ability to cope with risks
Risk: never went without medicine
Risk: could raise lumpsum in 3 days
Risk: kept money aside for future
Invest: set money aside for future
Invest:money aside for productivity
Invest: saving for old age
Financially healthy adults
2016 2019
23.8
24.6
23.1
21.0
27.9
18.0
46.1
24.9
24.6
25.1
25.3
24.2
25.4
22.8
51.0
50.4
51.5 53
.3
47.6
56.1
31.1
0
10
20
30
40
50
60
National Male Female Rural Urban Not financially healthy
Financially healthy
Improved Remained the same Worsened
7.0
9.4
11.8
4.3
6.8
4.7
13.8
2.0
7.1
2.9 3.2
8.4
1.5
6.4
1.1
6.1
Banks Saccos Mobile Money Mobile Banking** Microfinance
Institutons
App-based Loans* Informal groups
20132016
2019
Ability to invest in livelihoods and the future
54 2019 FinAccess Household Survey
5.1 Financial health by categories
5.1.1 Financial health by sex and residence
Malepopulationweremorefinanciallyhealthyat24.4percentcomparedtothefemaleat19.2percent.Similarlyurbanresidentswerefinanciallyhealthyat32.5percentcomparedtoruralresidents14.3percent(Figure 5.2).
Figure 5.2 Financial health by sex and residence (%)
38.2
27.5
34.3
23.8
24.9
51.0
0
10
20
30
40
50
60
Improved Remained the same Worsened
2016 2019
24.4
19.2
14.3
32.5
0
5
10
15
20
25
30
35
Male Female Rural Urban
Sex Residence
23.8
11.8 17
.0
23.9
33.8 36
.2
24.9
23.9 27
.3
26.0
23.4
23.7
51.0
63.9
55.3
49.8
42.3
39.8
0
10
20
30
40
50
60
70
National Lowest Second Lowest Middle Second Highest Highest
Improved
Remained the same
Worsened
5.1.2 Financial health by wealth quintiles
More than half of the Kenyan population in the highestwealthquintilewerefinanciallyhealthy.(Figure 5.3).
Figure 5.3 Financial health by estimated wealth quintile
5.4
20.5 26.7 20 21.4 12.1
79.5 73.3 80 78.6 87.9
0%10%20%30%40%50%60%70%80%90%
100%
18 - 25 years 26 - 35 years 36 - 45 years 46 - 55 years Over 55 years
47.333.2
14.5 14.1 8.6
52.766.8
85.5 85.9 91.4
0%10%20%30%40%50%60%70%80%90%
100%
Employed Own Business Agriculture Dependent Casual
42.4 46.9 51.435
57.6 53.1 48.665
0
10
20
30
40
50
60
70
80
90
100
Male Female Rural Urban
98.1 91.682.2
64.447.7
1.9 8.4 17.8
35.652.3
0
10
20
30
40
50
60
70
80
90
100
Lowest Second Lowest Middle Second Highest
Financially healthy Financially not healthy
Financially healthy Financially not healthy
Financially not healthy Financially healthy
Financially not healthy Financially healthy
.5.1.3 Financial health by livelihood
Adult population with formal employment and or owning abusinessweremorefinanciallyhealthy compared to thethose engaged in other sources of livelihood. (Figure 5.4).
Figure 5.4 Financial health by livelihood in 2019 (%)
5.4
20.5 26.7 20 21.4 12.1
79.5 73.3 80 78.6 87.9
0%10%20%30%40%50%60%70%80%90%
100%
18 - 25 years 26 - 35 years 36 - 45 years 46 - 55 years Over 55 years
47.333.2
14.5 14.1 8.6
52.766.8
85.5 85.9 91.4
0%10%20%30%40%50%60%70%80%90%
100%
Employed Own Business Agriculture Dependent Casual
42.4 46.9 51.435
57.6 53.1 48.665
0
10
20
30
40
50
60
70
80
90
100
Male Female Rural Urban
98.1 91.682.2
64.447.7
1.9 8.4 17.8
35.652.3
0
10
20
30
40
50
60
70
80
90
100
Lowest Second Lowest Middle Second Highest
Financially healthy Financially not healthy
Financially healthy Financially not healthy
Financially not healthy Financially healthy
Financially not healthy Financially healthy
2019 FinAccess Household Survey 55
5.1.4 Financial health by age
Adult population aged between 26 – 35 years were morefinanciallyhealthycomparedtothoseover55years(Figure 5.5).
Figure 5.5 Financial health by age (%)5.4
20.5 26.7 20 21.4 12.1
79.5 73.3 80 78.6 87.9
0%10%20%30%40%50%60%70%80%90%
100%
18 - 25 years 26 - 35 years 36 - 45 years 46 - 55 years Over 55 years
47.333.2
14.5 14.1 8.6
52.766.8
85.5 85.9 91.4
0%10%20%30%40%50%60%70%80%90%
100%
Employed Own Business Agriculture Dependent Casual
42.4 46.9 51.435
57.6 53.1 48.665
0
10
20
30
40
50
60
70
80
90
100
Male Female Rural Urban
98.1 91.682.2
64.447.7
1.9 8.4 17.8
35.652.3
0
10
20
30
40
50
60
70
80
90
100
Lowest Second Lowest Middle Second Highest
Financially healthy Financially not healthy
Financially healthy Financially not healthy
Financially not healthy Financially healthy
Financially not healthy Financially healthy
5.2 Financial status perceptions
Overall, the perception of respondents on their financialstatusworsenedin2019comparedto2016(Figure 5.6).
Figure 5.6: Financial status, 2016 and 2019 (%)
38.2
27.5
34.3
23.8
24.9
51.0
0
10
20
30
40
50
60
Improved Remained the same Worsened
2016 2019
24.4
19.2
14.3
32.5
0
5
10
15
20
25
30
35
Male Female Rural Urban
Sex Residence
23.8
11.8 17
.0
23.9
33.8 36
.2
24.9
23.9 27
.3
26.0
23.4
23.7
51.0
63.9
55.3
49.8
42.3
39.8
0
10
20
30
40
50
60
70
National Lowest Second Lowest Middle Second Highest Highest
Improved
Remained the same
Worsened
5.2.1 Financial status perception by sex and residence
AttheNationallevel,51percentofthepopulationreportedthat their financial status worsened in 2019 compared to23.8percentwhoreportedimprovedstatus(Figure 5.7). In termsoffinancialstatusbybothmaleandfemalereportedan average of 51 percent worsening status. Rural residents reported53.3percentworseningfinancialstatuscomparedto47.6percentforurbanresidents.
Figure 5.7: Financial status by sex, residence and financial health (%)
55.3
28
62.3
66.6
36.9
64.1
19.5
41.4
21.8
33.4
17.4
22.5
21.7
63
41.8
73.5
58.1
52.4
64.6
36.8
56.4
46.5
55.7
39.6
43.7
39.4
Ability to manage day to day
Manage: no trouble making money last
Manage: plan for allocating money
Manage: never went without food
Ability to cope with risks
Risk: never went without medicine
Risk: could raise lumpsum in 3 days
Risk: kept money aside for future
Invest: set money aside for future
Invest:money aside for productivity
Invest: saving for old age
Financially healthy adults
2016 2019
23.8
24.6
23.1
21.0
27.9
18.0
46.1
24.9
24.6
25.1
25.3
24.2
25.4
22.8
51.0
50.4
51.5 53
.3
47.6
56.1
31.1
0
10
20
30
40
50
60
National Male Female Rural Urban Not financially healthy
Financially healthy
Improved Remained the same Worsened
7.0
9.4
11.8
4.3
6.8
4.7
13.8
2.0
7.1
2.9 3.2
8.4
1.5
6.4
1.1
6.1
Banks Saccos Mobile Money Mobile Banking** Microfinance
Institutons
App-based Loans* Informal groups
20132016
2019
Ability to invest in livelihoods and the future
56 2019 FinAccess Household Survey
5.2.2 Financial Status by wealth quintile
Thehighestproportionofthepopulationacrossthewealthquintilesindicatedthattheirfinancialstatushadworsenedin2019(Figure 5.8).
Figure 5.8: Financial status by wealth quintiles in 2019 (%)38
.2
27.5
34.3
23.8
24.9
51.0
0
10
20
30
40
50
60
Improved Remained the same Worsened
2016 2019
24.4
19.2
14.3
32.5
0
5
10
15
20
25
30
35
Male Female Rural Urban
Sex Residence
23.8
11.8 17
.0
23.9
33.8 36
.2
24.9
23.9 27
.3
26.0
23.4
23.7
51.0
63.9
55.3
49.8
42.3
39.8
0
10
20
30
40
50
60
70
National Lowest Second Lowest Middle Second Highest Highest
Improved
Remained the same
Worsened
summary and conclusion
� Overall,majorityofKenyansfeelsthattheirfinancialstatushasworsenedregardlessoftheirsex,residenceandmarital status.
� TheabilityofKenyanstousefinancialservicesandproductstomanagetheirdailyneeds,copewithshocksandachieve big goals has declined.
2019 FinAccess Household Survey 57
06
The 2019 survey questionnaire contained questions to assess levels of financial awareness, literacy and aspects of consumer protection.
6.1 Financial literacy
Financial literacy is a combination of awareness,knowledge,skill,attitudeandbehaviournecessarytomakesound financial decisions. The sources of financial advicefor individuals are indicative of attitude and trust in an institution(s) or person(s).
The survey results showed that the proportion of respondents relying on their own knowledge was 39.6percent compared to 34.7 percent who relied on family and friendsforfinancialadvice(Figure 6.1).
Figure 6.1: Sources of financial advice (%)
6.1.1 Financial advice by sex
Thesurveyresultsindicatedthat40.5percentofmalesand38.7percentoffemalesreliedontheirownknowledge,while37.0percentoffemalesand32.3percentofmalesreceivefinancialadvicefromfriendsorfamily(Figure 6.2).
Figure 6.2: Sources of financial advice by sex (%)
ConSUMeR PRoteCtion AnD finAnCiAL LiteRACY
58 2019 FinAccess Household Survey
6.1.2 Financial advice by education
Thesurveyresultsshowthat46.1percentofthepopulationwithnoeducationand41.6percentwithprimaryeducationreliedontheirownknowledge,indecisionmakingonfinancialissues(Figure 6.3).
Figure 6.3: Sources of financial advice by education (%)
Theresultsalso indicate thatmore residents in ruralareas (42.2%)dependontheirownknowledge indecisionmakingonfinancialmatterscomparedto35.8percentinurbanareas(Figure 6.4).
Figure 6.4: Financial advice by residence
6.2 Knowledge on cost of borrowing
Interest rates constitute an important component when determining the cost of borrowing. The survey tested the ability of respondentstoaccuratelycompute10percentinterestonaKSh10,000loan.Thesurveyfindingsindicatethat42.7percentofthepopulationansweredtheinterestcostscorrectly,while39percentgaveawronganswer(Figure 6.5).
2019 FinAccess Household Survey 59
Figure 6.5: Knowledge on cost of borrowing(%)
6.2.1 Cost of borrowing by sex
The survey findings indicate that 48.8 percent of malesansweredinterestcostscorrectly,comparedto36.9percentof females (Figure 6.6).
Figure 6.6: Knowledge on cost of borrowing by sex (%)
6.3 Knowledge of transaction costs
Respondents were shown a typical message showing value of transaction and associated transaction costs as a Short MessageService(SMS)/text.Thesurveyresultsindicatedthat58.1 percent of respondents were able to read correctly atypical message showing transaction costs on a mobile phone (Figure 6.7).
Figure 6.7: Knowledge on transaction costs (%)
63.7
16.9
3.9
52.7
17.6
6.3
Correctly read the screen and
interpreted the SMS
Correctly read thescreen, but did
not correctly interpret the SMS
Could not read the SMS
Male
Female
22.716.9 19.7
69.5 68.2 68.8
7.814.9 11.5
Male Female TotalAgree Disagree Don't Know
8.3%
46.5
%
79.1
% 93.4
%
58.1
%
12.8
% 25.7
%
13.3
%
3.7%
17.3
%
No Education
Primary Education
Secondary Education
Tertiary Education
Total
Correctly read the text and interpreted it Correctly read the text, but did not correctly interpret it
More males (63.7 %) than females (52.2 %) read andinterpreted transaction costs correctly in an SMS (Figure 6.8).
Figure 6.8: Knowledge of transaction costs by sex (%)
63.7
16.9
3.9
52.7
17.6
6.3
Correctly read the screen and
interpreted the SMS
Correctly read thescreen, but did
not correctly interpret the SMS
Could not read the SMS
Male
Female
22.716.9 19.7
69.5 68.2 68.8
7.814.9 11.5
Male Female TotalAgree Disagree Don't Know
8.3%
46.5
%
79.1
% 93.4
%
58.1
%
12.8
% 25.7
%
13.3
%
3.7%
17.3
%
No Education
Primary Education
Secondary Education
Tertiary Education
Total
Correctly read the text and interpreted it Correctly read the text, but did not correctly interpret it
60 2019 FinAccess Household Survey
6.4 Perceptions on betting
6.4.1 Perceptions on betting/gambling
Only20percentoftheadultpopulationconsideredbettingas a good income source. More males at 22.7 percent comparedto16.9percentoffemalesagreedthatbettingisagoodwaytomakemoney.(Figure 6.9)
Figure 6.9: Perception of gambling as a good source of income by sex (%)
63.7
16.9
3.9
52.7
17.6
6.3
Correctly read the screen and
interpreted the SMS
Correctly read thescreen, but did
not correctly interpret the SMS
Could not read the SMS
Male
Female
22.716.9 19.7
69.5 68.2 68.8
7.814.9 11.5
Male Female TotalAgree Disagree Don't Know
8.3%
46.5
%
79.1
% 93.4
%
58.1
%
12.8
% 25.7
%
13.3
%
3.7%
17.3
%
No Education
Primary Education
Secondary Education
Tertiary Education
Total
Correctly read the text and interpreted it Correctly read the text, but did not correctly interpret it
6.4.2 Perceptions on betting/gambling by residence
More Kenyans in rural areas (69.5%) than 67.9 percent inurban areas do not consider gambling as good way of makingmoney(Figure 6.10).
Figure 6.10: Perception of gambling as a good source of income by residence
6.4.3 Use of mobile money account for betting
Overall, only 1.9 percent ofmobile users indicated havingused mobile money for betting (Figure 6.11)
The survey incorporated questions on the use of mobile money account by persons engaged in betting. The mobile money account has advantages due to unique characteristics of convenience and ease of use, privacy,andsecurityoffunds.Overall,1.9percentofmobilemoneyaccount use it for betting with the proportion higher for males at 2.7 percent and in urban areas at 2.1 percent. The use of mobile money accounts for betting was reported by 3.7percentofindividualsaged18to25years,withlowestusebeingpersonsaged46to55years.
Figure 6.11: Users of mobile money account for betting
36.430.9
13.2
65.1
15.4
4.7
19.5
1.7 0.50
20
40
60
80
ATM/ System or Card machine downtime
Unexpected charges Poor service (branch/ agent/customer care)
Banks Mobile Banking Mobile Money
40.333.6
22.4
1.7 1.0 0.3
I received a hoax SMS
I received a hoax phone
call
I Sent to the wrong number
Someone accessed my
mobile money account
Sender reversed genuine
transaction
Recipient did not get the money but my account was
deducted
1.9
2.7
0.9
3.7
2.0
1.3
0.7 0.8
1.6
2.1
0.0
0.5
1.0
1.5
2.0
2.5
3.0
3.5
4.0
Male Female 18 - 25 26 - 35 36 - 45 46 - 55 Over 55 Rural Urban Total
Sex Age Residence
2019 FinAccess Household Survey 61
6.4.4 Frequency of betting
Ofthe1.9percentwhorespondedthattheyusedmobilemoneyforbetting,majoritybetweekly(Table 6.1).
Table 6.1: Frequency of betting by sex, age and residence (%)
Frequency Sex Age Residence
Total Male Female 18 - 25 26 - 35 36 - 45 46 - 55 Over 55 Rural Urban
Daily 22.6 24.7 14.6 20.6 25.8 15.6 23.2 33.2 27.3 19.5
Weekly 51.7 53.0 46.7 48.7 55.3 53.6 57.0 31.1 38.6 60.2
monthly 6.9 4.2 17.3 7.0 3.9 7.5 6.3 30.4 7.3 6.7
intermittently (big prizes to win) 17.1 16.9 18.0 21.9 12.6 23.3 13.5 2.6 25.2 11.8
6.5 Consumer protection
Consumerprotectionpracticesentailmaintainingfinancialsystem integrity and safeguarding consumers against malpractices such as fraud, unfair pricing and lack ofcomplaint resolution.
The survey results indicate a downward trend in the instances of lost money by type of institution or device. Mobile money reported the highest incidence of money lost over all the three surveys. (Figure 6.12)
Figure 6.12: Lost money by different institutions 2016 and 2019 (%)
55.3
28
62.3
66.6
36.9
64.1
19.5
41.4
21.8
33.4
17.4
22.5
21.7
63
41.8
73.5
58.1
52.4
64.6
36.8
56.4
46.5
55.7
39.6
43.7
39.4
Ability to manage day to day
Manage: no trouble making money last
Manage: plan for allocating money
Manage: never went without food
Ability to cope with risks
Risk: never went without medicine
Risk: could raise lumpsum in 3 days
Risk: kept money aside for future
Invest: set money aside for future
Invest:money aside for productivity
Invest: saving for old age
Financially healthy adults
2016 2019
23.8
24.6
23.1
21.0
27.9
18.0
46.1
24.9
24.6
25.1
25.3
24.2
25.4
22.8
51.0
50.4
51.5 53
.3
47.6
56.1
31.1
0
10
20
30
40
50
60
National Male Female Rural Urban Not financially healthy
Financially healthy
Improved Remained the same Worsened
7.0
9.4
11.8
4.3
6.8
4.7
13.8
2.0
7.1
2.9 3.2
8.4
1.5
6.4
1.1
6.1
Banks Saccos Mobile Money Mobile Banking** Microfinance
Institutons
App-based Loans* Informal groups
20132016
2019
Ability to invest in livelihoods and the future
*Data for app-based loans was not collected in 2016 and ** data for mobile banking was not available in 2013
62 2019 FinAccess Household Survey
The main reason for loss of money through mobile money is attributed to fraudulent activities and sending money to the wrong mobile phone number (Figure 6.13).
Figure 6.13: Loss of money via mobile money, 2019 (%)
36.430.9
13.2
65.1
15.4
4.7
19.5
1.7 0.50
20
40
60
80
ATM/ System or Card machine downtime
Unexpected charges Poor service (branch/ agent/customer care)
Banks Mobile Banking Mobile Money
40.333.6
22.4
1.7 1.0 0.3
I received a hoax SMS
I received a hoax phone
call
I Sent to the wrong number
Someone accessed my
mobile money account
Sender reversed genuine
transaction
Recipient did not get the money but my account was
deducted
1.9
2.7
0.9
3.7
2.0
1.3
0.7 0.8
1.6
2.1
0.0
0.5
1.0
1.5
2.0
2.5
3.0
3.5
4.0
Male Female 18 - 25 26 - 35 36 - 45 46 - 55 Over 55 Rural Urban Total
Sex Age Residence
Intermsofexperienceswithfinancialservicesused,systemdowntimeposedthegreatestchallengeandinconvenience(Figure 6.14)
Figure 6.14: Challenges experienced on financial services used (%)
36.430.9
13.2
65.1
15.4
4.7
19.5
1.7 0.50
20
40
60
80
ATM/ System or Card machine downtime
Unexpected charges Poor service (branch/ agent/customer care)
Banks Mobile Banking Mobile Money
40.333.6
22.4
1.7 1.0 0.3
I received a hoax SMS
I received a hoax phone
call
I Sent to the wrong number
Someone accessed my
mobile money account
Sender reversed genuine
transaction
Recipient did not get the money but my account was
deducted
1.9
2.7
0.9
3.7
2.0
1.3
0.7 0.8
1.6
2.1
0.0
0.5
1.0
1.5
2.0
2.5
3.0
3.5
4.0
Male Female 18 - 25 26 - 35 36 - 45 46 - 55 Over 55 Rural Urban Total
Sex Age Residence
2019 FinAccess Household Survey 63
Loan defaults
Thehighestdefaultratewasreportedforshopkeepercreditfollowedbymobilebankingandfriend/familyloans(Figure 6.15).
Figure 6.15: Proportion of defaulters by loan type, 2019 (%)
Meeting day to day needs
75.0
37.9
46.2
67.3
39.2
56.563
.8
37.9
61.6
53.7
32.7
66.2
46.5
32.5
68.5
Meeting day to day needs
Experienced shocks Meeting future goals
Lowest Second Lowest Middle Second Highest Highest
72.2
34.9
59.864
.6
33.9
47.3
60.2
40.1
50.356
.4
37.0
73.3
52.3
33.4
74.1
Experienced shocks Meeting future goals
Casual Dependent Agriculture Own business Employed
55.4
20.1
3.7
13.2
3.1 3.6
58.9
8.63.4
19.0
3.8 4.4
0.0
10.0
20.0
30.0
40.0
50.0
60.0
70.0
Major sickness/accident injury
Loss/damage of business/livestock or crop because ofnatural disasters
Death of income earner
Death of a family member or relative
Loss/damage of major asset/
money because of theft or other human
causes
Child birth
RuralUrban
.8
1.3
1.8
2.2
2.9
7.3
9.4
12.7
18.1
45.4
.0 5.0 10.0 15.0 20.0 25.0 30.0 35.0 40.0 45.0 50.0
Shylock loan
Government loan
Cash loan from shopkeeper
Bank loan
SACCO loan
Chama loan
Digital App loans
Loan from friends and family
Mobile bank loan
Goods/services on credit from shopkeeper
Reasons for loan default vary by providers as indicated in Table 6.2.
Table 6.2: Reasons for loan default across selected providers, 2019 (%)
Did not plan well enough
interest/repayment rates went
up
Did not un-derstand the terms
poor business perfor-mance
All of my money went to basic needs such as food or utility
bills
Had to pay off other
loans
partner/someone else in household lost job/source of
income
payment was more
than i expected
Unexpected emergency
expendi-ture
Forgot to re-pay on
time
Bank loan 2.2 2.1 0.0 0.0 7.1 0.6 6.2 4.1 0.0 0.0
mobile phone banking loan 18.1 28.0 26.0 32.9 20.6 7.5 8.6 28.8 4.4 0.0
Digital app loans 9.4 12.2 7.3 19.8 4.8 6.6 21.6 8.3 0.0 50.0
goods/services on credit from shopkeeper 45.4 34.4 0.0 15.1 37.6 63.0 23.3 26.0 95.6 41.6
loan from friends and family 12.7 17.2 0.0 0.0 13.9 9.9 27.8 11.5 0.0 8.4
Chama loan 7.3 4.8 7.5 32.2 10.2 10.3 2.8 6.5 0.0 0.0
summary and conclusion
� Overall,Kenyansseekadvicefromfriendsandfamilyonfinancialmatters. � Promotionoffinancialliteracyisimportantinaddressingconsumerprotectionconcerns. � Fraud accounted for the highest incidences of loss of money on mobile money platforms. � Mobilephonebankinganddigitalappshaveintroducednewemergingrisks.
64 2019 FinAccess Household Survey
SUMMARY AnD ConCLUSionS
The 2019 FinAccess Household Survey report presents results of data collected during October - December 2018 covering 11,000 households across the country. The survey targeted individuals aged 16 years and above, from scientifically selected households, designed to provide significant estimates at the national and regional level and by residence (rural and urban areas).
The household sample selection was drawn from the fifth National Sample Survey and Evaluation Programme(NASSEPV)householdsamplingframe.Thesurveydatasetis robust and provide insightful findings to policymakers,regulators, private sector actors, development partners,researchers and academician.
The2019 survey focussedmoreon theusage,quality and impact/welfaredimensionsofmeasuringfinancialinclusion.Inaddition, thequestionnaire incorporatedaneeds-basedframeworktothemeasuretherelevanceoffinancialservicesandproducts;financialhealthandlivelihoodsmodules;andconsumer protection and financial literacy. Furthermore,the survey also included independent modules on business andagricultural finance to helpunravel usageof financialproducts and services within these livelihoods. This was in recognitionofthefactthatmereaccesstofinancialinclusionis not a sufficient requirement for usefulness of financialsector to households in meeting their needs and goals. This isanimportantstepinthedevelopmentofanall-inclusivefinancialecosystemforKenyans.
Thesurveyfindingsshow thatKenyahasmadesignificantmilestones in expanding the access to financial servicesandproductsto82.9percentin2019from26.7percentand75.3percent in2006and2016 respectively. Several factorscontribute to this impressive outcome – rapid uptakeof mobile money, adoption of transformative financialtechnologies and innovations, and government initiativesand policies.
We celebrate this achievement of increased access to formalfinancial inclusion,butweneedtoaddressthe11.0percent of adult population still excluded and the persistent financialinclusiongapsamongseveraldemographics-age
andeducationlevels,gender,incomeandlivelihoods,rural-urbandivide,andwealthquintiles.Otherareasweneedtoaddress include the 30.1 percent of the adult population relying on informal financial services and products, inparticular, ‘SecretHidingPlace’, credit in formof cashandgoodsfromashopkeeper,andgroupsakaChamas.
ThesurveyfindingsalsohighlightconsumerprotectionandfinancialeducationissuesaffectingKenyans.Theseinclude:–highcostofaccessingandmaintainingafinancialproductor service, unexpected charges, loss of money throughfraud, lack of transparency in pricing of financial servicesandproducts,andunreliablemarketinfrastructuresystemsdowntimeforATMs,PointofSale(POS)devicesandMobilemoney and electronic funds transfer systems. The survey further points out emerging areas that require attention and deepdivestudiessuchasrapiduptakeofunregulateddigitalapps loans, persistence reliance on informal groups forfinancialservices,andlowfinancialhealth.Thesedeepdivestudies are required to unravel unanswered questions by identifyingthemissinglinkbetweenrapidgrowthinfinancialinclusionandfinancialhealthofKenyans,withonlyafifthoftheadultpopulationbeingmeasuredasfinanciallyhealthy;andthedecliningroleofMFIs,InsuranceandPension.
Thesurveys’datasetsshouldencouragefurtherresearchtobetter understand the underlying dynamics and drivers in order to provide possible solutions and policies to emerging challenges. The datasets released by KNBS with linksprovided in CBK and FSD Kenya websites should enableresearchers andacademicians, amongother stakeholders,toundertake further analysis and research.KNBShasalsoestablished an interactive visualized web portal to enable usersinteractwiththedatasetsindifferentformats.
07
2019 FinAccess Household Survey 65
[email protected] • [email protected] www.centralbank.go.keHaile Selassie AvenueP.O. Box 60000 - 00200, Nairobi KenyaTel/fax: +254 (20) 2860000
[email protected] • www.knbs.or.keHerufi House • Lt Tumbo LaneP.O. Box 30266 - 00100, GPO NAIROBI.Tel: +254 (701) 244533, (735) 004401
[email protected] • www.fsdkenya.org3rd floor, 9 Riverside • Riverside Drive PO Box 11353 - 00100 Nairobi, Kenya Tel: +254 (20) 513 7300