GAUL: Microfinance Data What is it, how can I get it and what can it tell me?
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Transcript of GAUL: Microfinance Data What is it, how can I get it and what can it tell me?
The Premier Source for Microfinance
Microfinance Information Exchange
Microfinance DataWhat is it, how can I get it and what can it tell me?
The Premier Source for Microfinance
Data and Analysis
This presentation is the proprietary and/or confidential information of MIX, and all rights are reserved by MIX. Any dissemination, distribution or copying of this
presentation without MIX’s prior written permission is strictly prohibited.
• Twitter: 140 million users
• All income strata
• Microfinance: 140 million users
• Focus on the poor
Where should I look for data on the marginalized and excluded?
This presentation is the proprietary and/or confidential information of MIX, and all rights are reserved by MIX. Any dissemination, distribution or copying of this
presentation without MIX’s prior written permission is strictly prohibited.
• Range of uses
• Data easy to get
• Used for business investment,
household expenses, basic needs
• Data not-so-easy to get2
Where microfinance data comes from: inside the MFI
Back-office systems External reportingFront-office systems
This presentation is the proprietary and/or confidential information of MIX, and all rights are reserved by MIX. Any dissemination, distribution or copying of this
presentation without MIX’s prior written permission is strictly prohibited.
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Pros:
Frequent
Granular (client-level)
Cons:
Not standardized
Confidential
Pros:
Standardized
Public
Cons:
Slow
Aggregated (inst.-level)
Pros:
Close to clients
Likely frequent
Cons:
Not digitized
Not standardized
Aggregate data helps to understand sector dynamics
Number of clients
(normalized for sector peak)
This presentation is the proprietary and/or confidential information of MIX, and all rights are reserved by MIX. Any dissemination, distribution or copying of this
presentation without MIX’s prior written permission is strictly prohibited.
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Microfinance risk factors: early warning signalso
pe
rati
on
al
da
ta
Source: University
of Zurich, “Over-
indebtedness and
Microfinance
Constructing an
Early Warning
Index”
This presentation is the proprietary and/or confidential information of MIX, and all rights are reserved by MIX. Any dissemination, distribution or copying of this
presentation without MIX’s prior written permission is strictly prohibited.
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Ba
sic
op
era
tio
na
l d
ata
Su
rvey
/ sen
time
nt d
ata
Identifying supply and demand gaps: Kenya
Access points by % financially excluded Access points by district-level poverty and
provider type
This presentation is the proprietary and/or confidential information of MIX, and all rights are reserved by MIX. Any dissemination, distribution or copying of this
presentation without MIX’s prior written permission is strictly prohibited.
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Identifying industry hotspots: Bosnia (post crisis)
This presentation is the proprietary and/or confidential information of MIX, and all rights are reserved by MIX. Any dissemination, distribution or copying of this
presentation without MIX’s prior written permission is strictly prohibited.
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Tracking industry sentiment: news on Kyrgyzstan
This presentation is the proprietary and/or confidential information of MIX, and all rights are reserved by MIX. Any dissemination, distribution or copying of this
presentation without MIX’s prior written permission is strictly prohibited.
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Loan portfolios (10 years) Investment flows (5 years)
• Data comes from somewhere
– Understanding the supply chain for data is key to finding
scalable solutions
• Interpretation can be ambiguous
– Credit growth: positive investment outlook or debt spiral?
Key points for microfinance data
This presentation is the proprietary and/or confidential information of MIX, and all rights are reserved by MIX. Any dissemination, distribution or copying of this
presentation without MIX’s prior written permission is strictly prohibited.
– Credit growth: positive investment outlook or debt spiral?
– Savings growth: bad investment outlook or asset-building?
– Risk indicators help identification, but are harder to find
• Augmenting with outside data sources provides
additional context
– Reputation risk and political and regulatory factors
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MIX partners with a dedicated group of industry leaders:
MIX Global and Project Partners
This presentation is the proprietary and/or confidential information of MIX, and all rights are reserved by MIX. Any dissemination, distribution or copying of this
presentation without MIX’s prior written permission is strictly prohibited.
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www.themix.org ♦ www.mixmarket.org
Contact us: [email protected]
Regional Offices:
Baku, Azerbaijan 44 J. Jabbarli st. Caspian Plaza I, 5th Floor,
Microfinance Information Exchange
Headquarters:
1901 Pennsylvania Ave., NW, Suite 307Washington, D.C. 20006 USA
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presentation without MIX’s prior written permission is strictly prohibited.
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