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Savings Groups and the SAVIX database
The SAVIX database
• Quarterly information of over 5 million members
from 200000 savings groups over several quarters
in more than 50 countries.
• Based on a reporting system (the SAVIX MIS)
• 1,200 projects worldwide report to SAVIX
• Developed by VSL Associates (Hugh Allen ++)
• Supported by the Bill & Melinda Gates Foundation, CARE,
Catholic Relief Services, Oxfam America and Plan
International.
How can this be used for Academic Research with
practical relevance?
Big data
The SAVIX Project at CERSEM UiA: Agreement with FAHU
• Centre for Research on Social Enterprises and
Microfinance (CERSEM, https://cersem.uia.no/)
• Funding from FAHU and University of Agder/CERSEM
• From January 2018 to June 2021
Roy Mersland
Project manager
Bert D’Espallier
Deputy leader
Rolando Gonzales
Ph.D. candidate
Linda Nakato
Ph.D. candidate
The SAVIX Project at CERSEM: objectives
In the interest of both practitioners and academics, the project
seeks to provide research findings to answer the general
question of “How can development actors contribute to poverty
alleviation in a cost-effective way through the use of savings
groups?”:
1. What are the group-level characteristics that enhance better group
performance?
2. What type of delivery/implementation mechanisms facilitate better
group performance including group survival?
3. How is the macro-economic environment influencing the possible
success of savings groups?
The SAVIX database
• The SAVIX is an unbalanced panel dataset that contains
quarterly information from 2010-Q1 to 2017-Q4.
SGs % Cum.
Africa 222,427 87.47 87.47
Asia 23,942 9.42 96.89
Americas 7,304 2.87 99.76
Europe 612 0.24 100
Total 254,285 100
SGs in the SAVIX database: countries and regions
SGs in the SAVIX database: Urban and rural
SGs Percent Cum.
Rural 129838 65 65
Rural+Urban 67050 33 98
Urban 4436 2 100
Total 201324 100
SGs in the SAVIX database: donors
SGs in the SAVIX database: facilitating agencies
SGs in the SAVIX database: SGs+ Is it wise or not wise to use SGs as
platforms for other
development efforts?
SGs in the SAVIX database: group formation
SGs in the SAVIX database: group status
The SG model is
sustainable
SGs in the SAVIX database: Financial Linkages
SGs in the SAVIX database: Members
Members at
start of the
cycle
Dropouts since
start of the
cycle
Members attending
meetings
Mean 21 1.99% 91.02%
Median 20 0% 95.71%
Standard deviation 7 7.51% 12.02%
Min 3 0% 8.57%
Max 100 100% 100%
Percentile 5 10 0% 66.67%
Percentile 10 12 0% 74.29%
Percentile 25 15 0% 86.21%
Percentile 75 25 0% 100%
Percentile 90 30 5% 100%
Percentile 95 30 12.5% 100%
SGs in the SAVIX database: Gender of members
Number of
members Male members Female members
Mean 21 4 17
Median 22 3 17
Standard deviation 7 5 7
Min 3 0 0
Max 100 91 100
Percentile 5 10 0 5
Percentile 10 12 0 7
Percentile 25 16 0 12
Percentile 75 26 8 23
Percentile 90 30 12 26
Percentile 95 30 15 29
Balance sheet: Assets
Cash in
group box
(USD)
Cash in
other
funds
(USD)
Bank
balance
(USD)
Value of
loans out-
standing
(USD)
Value of
loans past
due
(USD)
Mean 284.8 23.9 4.2 302.4 0.5
Median 85.3 9.8 0.0 132.7 0.0
Std. deviation 491.5 44.3 46.3 454.6 11.7
Minimum 0.0 0.0 0.0 0.0 0.0
Maximum 4795.0 3426.0 2584.8 4843.0 1477.0
Percentile 5 0.0 0.0 0.0 0.0 0.0
Percentile 10 2.1 0.0 0.0 0.0 0.0
Percentile 25 20.8 0.0 0.0 0.3 0.0
Percentile 75 313.0 30.3 0.0 393.3 0.0
Percentile 90 822.9 62.5 0.0 828.1 0.0
Percentile 95 1306.7 91.5 0.0 1210 0.0
Why do groups keep so much money in the box?
Balance sheet: Liabilities & Equity
Debts
(USD)
Equity
(USD)
Mean 2.1 671.5
Median 0.0 396.9
Std. deviation 16.9 743.2
Minimum 0.0 0.1
Maximum 2319.3 4925.0
Percentile 5 0.0 22.4
Percentile 10 0.0 49.7
Percentile 25 0.0 146.1
Percentile 75 0.0 937.5
Percentile 90 0.0 1708.7
Percentile 95 11.1 2270.6
SGs in the SAVIX database: SGs’ performance
Annualized
Returns on
Savings
(ROS)
Annualized
Returns on
Assets
(ROA)
Average savings
per member
(USD)
Average assets
per member
(USD)
Mean 92.0% 66.8% 20.5 28.4
Median 57.8% 50.0% 13.8 19.0
Std. deviation 70.2% 46.2% 20.2 27.9
Minimum -578.8% -569.8% 0.0 0.0
Maximum 1566.0% 659.9% 117.1 161.5
Percentile 5 0.0% 0.0% 1.8 1.9
Percentile 10 0.0% 0.0% 3.2 3.8
Percentile 25 10.0% 9.4% 6.4 8.3
Percentile 75 126.4% 97.8% 27.6 39.1
Percentile 90 222.6% 157.2% 47.8 67.9
Percentile 95 305.0% 209.6% 63.9 89.0
Crosstabs: SG plus
Annualized Returns on
Assets
(ROA)
Annualized Returns on
Savings
(ROS)
Additional services
Without plus services 66.94% 91.98%
With plus services 66.64% 91.92%
Platform services do not seem to harm groups’ financial performance What about group dynamics?
Crosstabs: Group status
• Self-managed groups are more mature (older)
• Those that report can clearly manage themself
• What about the groups that do not report to SAVIX?
Annualized Returns on
Assets
(ROA)
Annualized Returns on
Savings
(ROS)
Group status
Self-managed 68.30% 93.90%
Supervised 53.98% 74.98%
Groups improve their performance when they are no longer supervised
Crosstabs: Regions
• Why do groups charge higher rates on loans in East Africa?
• Better business opportunities (higher margins)
• Less credit competition?
• More savings competition?
• Less educated members?
• Cultural reasons?
Annualized Returns on
Assets
(ROA)
Annualized Returns on
Savings
(ROS)
Regions
Eastern Africa 83.70% 116.64%
South America 24.98% 31.62%
Southern Asia 24.90% 34.76%
Western Africa 58.34% 78.24%
SAVIX research – a long list of research questions Some examples
• How does financial linkage influence group performance and
dynamics?
• How does facilitation of platform services influence group
performance and dynamics?
• How does gender composition of groups influence group
performance and dynamics?
• Which contextual factors influence interest rate levels in
groups?
• Which delivery model (field agent versus field officer) faciliates
the best performing groups?
Financial linkages
Savings Groups and the SAVIX database
Appendix: Financial Performance Indicators: Indicator Definition
Returns on Assets
(ROA)
Group returns were calculated by adding the value of the cash kept in a box to
the value of the bank balance and the property of the group and the value of
loans outstanding, minus the sum of the net value of savings, the property at
the start of the cycle and the debts of the group. These returns were divided by
the net value of assets, which was calculated as the sum of the value of the cash
kept in a box, the bank balance, the property of the group and the value of
loans outstanding. This performance measure was annualized by diving the
financial indicator between the duration (in days) of the group and multiplying
the results by 365. Finally it was multiplied by two to take account of the
average between start-up of a cycle (assuming zero in assets) and amount of
savings at the time of reporting.
Returns on Savings (ROS)
Group returns were calculated by adding the value of the cash kept in a box to
the value of the bank balance and the property of the group and the value of
loans outstanding, minus the sum of the net value of savings, the property at
the start of the cycle and the debts of the group. These returns were divided by
the net value of savings.
This performance measure was annualized by diving the financial indicator
between the duration (in days) of the group and multiplying the results by 365.
Finally it was multiplied by two to take account of the average between start-up
of a cycle (zero in savings) and amount of savings at the time of reporting.
Equity per member Equity was divided by the number of active members in a group to obtain equity
per member.
Average savings per member Net value of savings divided by the number of active members in a group
Average assets per member Assets were divided by the number of active members in a group to obtain
assets per member.
