How to “formalize
theinformals”:
Case Study: Timiza – Barclays Kenya Mobile Lending Proposition
Presenter: Chrispus Muhia: Head of Consumer Credit
Barclays Bank of Kenya
| Presentation to CCI Ivato Antananarivo MADAGASCAR26 November 2019
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Preamble
• Increasing pace of technology adoption for financial services calls for banks and other financial institutions to
adopt new delivery channels to reach key target markets.
• Africa’s population is characterised by low banking and credit penetration rates, with access tocredit being a key concern
• Mobile telephony has been well adopted and embraced by Africans, sidestepping key physical
infrastructural challenges like transport networks
• Banks can thus leverage m-banking solutions to reach to African populations to deliver access to
| Presentation to CCI Ivato Antananarivo MADAGASCAR26 November 2019
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• Banks can thus leverage m-banking solutions to reach to African populations to deliver access to
banking and credit.
• Use of alternative data sources is critical where most of the population do not have historical banking and
credit histories. Mobile Network Operator (MNO) data, both airtime and wallet, is critical in bridging these
gaps.
• Credit bureaus supplement these alternative data sources by enabling credit information to be shared regularly,
enabling customers to build credit profiles that enhance access to higher credit limits, and better risk based pricing decisions that benefit good customers with lower interest rates.
Drivers to Mobile Banking/Virtual Banking
Ease of access:• Mobile Banking offers easier accessibility to banking services anytime and anywhere - consumers are able to
access their account at a click of a button with or without need of internet connectivity (USSD access is critical)
User friendly interface:• Mobile banking offers a friendly and easier way to access one’s account.
Convenience:• Not time consuming
| Presentation to CCI Ivato Antananarivo MADAGASCAR26 November 2019
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• Mobile Banking offers instant banking services that initially could require hours queuing in the banking hall
• one can withdraw/save money in the account at the comfort of their home/office
• Cuts unnecessary human interface. Offers dignity and avoids humiliation
Secure way to access and use your money• One can pay bills (schools fees, utility bills, buy good and services) without physical withdrawal of money
• Offers minimal risk of theft –password protected
Background: The Kenyan market is characterised byhigh demand for digital loans with approximately 6.3million unique digital borrowers
48.5Millions
KenyanPopulation
23.5Millions
KenyanAdults
18.2MillionsMillions
Phone Owners
6.3Millions
Digital Borrowers 27% of
Kenyan Adults
35% of Phone
OwnersSource: Financial Sector Deepening Kenya, March 2018, The digital credit revolution in Kenya: An assessment of market demand, 5 years on.
| Presentation to CCI Ivato Antananarivo MADAGASCAR26 November 2019
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Competitivedigital financing operating environment
| Presentation to CCI Ivato Antananarivo MADAGASCAR26 November 2019
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Customer Value Proposition
Ease of Access & Convenience =
Transactional, simple and
secure way to manage your
finances
+
Quick and easy
loans
+ +
Efficient 24/7 Contact
Centre for assistance
Enable me to grow
=
Bank - Anywhere
anytime
#Mobile first
+
Fund your Timiza account & pay
loans from your Mpesa wallet
with ease
No credit record
required to borrow
++Access group loans and
group savings facilities
Access to in-store financing
to access goods on credit
Flexibility = + +
More than just aBank: Protection
and Value adds
+
Last expense Cover to your
next of Kin - Funeral Cover
No Minimum balance
requiredNo limit on transactions to
access funds in your account
Personalaccident Cover
Pay your bills conveniently
from your mobile phone.
Ability to book a tax ride on
Timiza App (Little cabs)
+
Open a second/additional
account on mobile with
ease
Personal Finance
Management
+
| Presentation to CCI Ivato Antananarivo MADAGASCAR26 November 2019
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=
Key relationships during on-boarding
Customer dials short code /
downloadsTimiza App and enters
National ID
Retrieve data from MNO, IPRS andBureau with ID
Number
Provides KYC as per Government
Database using ID Number
Through a Data Sharing API
service, it verifies mobile number and ID Number match
Providescustomer credit history from
credit bureau
Matching Algorithm
KYC Lite matches ID number to to
KYCprocess• Automated, integrated customer on
boarding where customer enters only ID and eco system relies on Govt Population registry (IPRS – Integrated Population Registry System) as the golden source for
Customer Technology
Partner
MNO
Partner
Credit Reference
Bureau
ID number to to IPRS
Customerreceives SMS message–„Sorry, unable to
verify your details, please contactCall
Centre
Match es ?
Timiza Account is opened, OTPis generated
Credit Scoring and Limit Assignment initiated
Welcome to Timiza SMS Message
Credit approval process• Transition from rule based decisioning to
data driven decisioning supported by scorecards
• 2nd Generation application scorecard in place, with 3rd generation scorecard under development.
• 1st Gen Behavioural scorecard in place
• Collection process• Call centre based• On roll forward, no punitive / predatory
compounding interest rates or accumulated collectionfees
• No new loans extended before existing loan paid off
Registry System) as the golden source for KYC. Customer and Account record created with IPRS details
• MNO service enables verification ofmobile number ownership to the IDnumber
Customers with Limits can apply for loan
| Presentation to CCI Ivato Antananarivo MADAGASCAR26 November 2019
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Typical Scoring Process
| Presentation to CCI Ivato Antananarivo MADAGASCAR26 November 2019
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Activity Model is used to
assess customers with NO or
Immature CRB footprint
Performance Model is used
to assess customers with
mature CRB footprint. This
thus uses both CRB and MNO
data at assessment.
• Bad Rate was defined as 30 days past due
Bureau Information Critical in enhancing Credit Decisioning
ActivityModel PerformanceModel
y = -0.0038x + 2.922
R² = 0.2877
20.00%
30.00%
40.00%
50.00%
60.00%
Ba
dra
te
No Bureau Info
y = -0.0024x + 1.894
R² = 0.9254
25.00%
20.00%
15.00%
10.00%
30.00%
Ba
dra
te
Bureau Info supplementing MNO
Data
0.00%
10.00%
640 650 660 680 690 700670
Mean score
Rule Based ModelBad Rate33.34%
Score cut-off 695
Rejection Rate 92.51%
Expected Echo Bad Rate 20.37%
Gini 23.8%
5.00%
0.00%660 680 700 720 740 760
Mean score
Rule Based ModelBad Rate15.63%
Score cut-off 685
Rejection Rate 19.61%
Expected Echo Bad Rate 14.49%
Gini 41.8%
| Presentation to CCI Ivato Antananarivo MADAGASCAR26 November 2019
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5.0%
10.0%
15.0%
20.0%
25.0%
30.0%
CRB data critical in managing default
0.0%A B C D E X (No CRB)
default rate. Additional CRB data helpsdistinguish performance of existing
borrowersCustomers are not allocated a credit limit
Customers with low probability of
defaults will be allocated limitsbased on their proven track record.
customers
Customers with no previous
borrowing history will be scored purely based on their
Full limits allocated to these Cut out CRB grades D&E based on high telco data.The default rates are high
hence full limits not allocated
| Presentation to CCI Ivato Antananarivo MADAGASCAR26 November 2019
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Portfolio Distribution Outcome
| Presentation to CCI Ivato Antananarivo MADAGASCAR26 November 2019
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Impact of Bureau Data in Credit Decisioning
Phase 1:
Post Launch
Testing launchassumptions
Phase 2:
Decision made to cut out Bureau
score Grades D and E, and to limit initial ticket size for
‘No Score’ customers
Phase 3:
Bureau score built into application
and Behavioural scorecards.
| Presentation to CCI Ivato Antananarivo MADAGASCAR26 November 2019
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Key Lessons Learnt
1.
Customer
2. Technology
Partnership
4.
Business Mix
Key
Lessons
Learnt• Availability of alternative datain
absence of traditional financial and credit data. MNO, Social
• Customers concerned with ease of access to finance
• Customers do not typically have previous financial or credithistories, (providingbanking and credit to the informals)
• Customers require basic financial and credit solutions to run their lives (personal and business)
• Fit for purpose scorecards, both application and behavioral (to assess customer profiles)
• Criticality of building and retainingrepeat customers to drive revenueand profitability
• Focus on vulnerable agegroups; educating and offering them payment plans
• Major difference in loan performance acrossdemographics
• Use of credit Bureau input incredit decisioning
• Lack of skill & resources on agile product development and DevOps
5.
Agility/Speed &
Marketing
Intensity
3.
Data
• Third party may provide hosted solution for scorecard and customer data if this is not available internally however, there needs to be constant monitoring of the scorecardand data changes
• Availability of in-house dataanalytics vital for unlockinggrowth
media• Leveraging Bureau data to
enhance creditdecisioning• Real time monitoring and
oversight on system performance key fordigital products
• Misalignment of culture between Banks and technology providers on strategicroadmap may posechallenges
• Scalability challenges with increased customer demand& transaction volume necessitating frequent optimization and system investments
• Response time of partnersa consistentchallenge
development and DevOps with technologyproviders may be a potential challenge
• Clearly articulated operating model forDigital Business is important across the different business units to drive ecosystemopportunities
• Adequate resourcing is key to fully monitor the day to day monitoring of the product andevolve the proposition
• The new ecosystem requires unconventional marketing tactics & intensity
| Presentation to CCI Ivato Antananarivo MADAGASCAR26 November 2019
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Customer Feedback – Timiza Making a difference in customers lives – Bringing their possibilities to life
| Presentation to CCI Ivato Antananarivo MADAGASCAR26 November 2019
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| Presentation to CCI Ivato Antananarivo MADAGASCAR26 November 2019
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