Colloquium financial institutions in the global south

The Role of Financial Institutions in Value Chain Finance in the Global South

Mohamed Ali Trabelsi

Plan

I.Introduction

II.Literature Review

III.Methodology and Data

IV.Analysis and Results

V.Limitations and further research needs

VI.Conclusion

2

VII.Recommendations

Smallhold

price and market risks

Result

3

Low profit...!

Financial institutions are less interested in financing the agricultural sector !

Result

Why...?!

Lack of collateral...!

4

5

Result

Farmers often face multiple challenges to access the finance they require

Financial Institutions (FIs) consider farmers as "non-bankable», or not creditworthy

Result

6

«There is little systematic data available on which to make global or regional generalizations. ... how well the industry is performing...»

7

! Research questions !

1) What are the key underlying characteristics of credit provision of different types of financial institutions in the Global South?

2) To what extent financial institutions promote gender issues and include digital solutions?

3) What kind similarities and differences can be observed between financial institutions?

8

*** Expected results from the research ***

Database of Financial institutions

Data-driven evaluation of financial institutions' services

Agenda for agricultural finance policy recommendation

9

Plan

I.Introduction

II.Literature Review

III.Methodology and Data

IV.Analysis and Results

V.Limitations and further research needs

VI.Conclusion

10

VII.Recommendations

	*** Literature Review ***
Technische Universitet München

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11

Plan

I.Introduction

II.Literature Review

III.Methodology and Data

IV.Analysis and Results

V.Limitations and further research needs

VI.Conclusion

12

VII.Recommendations

*** Description of the study ***

Database of financial institutions

Global Map of financial institutions

13

*** Building the database ***

37

201

109

347

14

*** Statistical Analyses ***

Descriptive statistics

Cluster Analyses

15

*** Data Types and Variables ***

Continent Attribute

Africa 0

Asia 1

South America 2

Global 3

Institutional type	Attribute
Agricultural Bank	0
Commercial Bank	1
cooperative	2
Credit union	3
Development Bank	4
Insurance company	5
International FI	6
International Fund	7
Islamic Bank	8
MFI	9
NGO	10
state development bank	11

16

Agricultural loans Attribute

Credit facility for

women

Career development to female staff

Gender Programmes G3

G2

G1

Online Banking DS1

E-Products: DS2

Online Loan Application

DS3

^{Checking the rubric «Products and Services» AL1, AL2 0-1}

Gender Variables

Digital solution Variables

Farmer credit AL1

Agri-business credit AL2

^Continent

^{Institutional Type}

^{Foundation year}

^{Number of Branches}

^{Agricultural Loans}

^Gender

^{Digital solutions}

^{Total assets}

^{Total Equity}

^{Gross Loan Portfolio}

^{Variables Search Method Name/ Scale}

^{checking the institute's website C 0-3}

^{checking the rubric «about us» T 0-11}

^{checking the rubric «our history» F Year}

^{checking the rubric «locate us» B Number}

^{Checking the rubric «our value» and «events» G1, G2, G3 0-1}

^{Verifying if «online banking» or other e-products}

^{DS1, DS2,}

^0-1

^{investigating the most recent «annual report» AS} $

^available

^DS3

^{investigating the most recent «annual report» EQ} $

^{investigating the most recent «annual report» LP} $

*** financial institutions sample ***

Financial
institutions from
the literature
review

201

Africa

Sample FIs: 200

Global

Sample FIs: 16

Total of 347 financial institutions

144

17

Plan

I.Introduction

II.Literature Review

III.Methodology and Data

IV.Analysis and Results

V.Limitations and further research needs

VI.Conclusion

18

VII.Recommendations

*** Geographic distribution ***

Global

9%

America

24%

Africa

47%

Asia

20%

Continent		No of FIs	Share
Africa		67	47%
South America		35	24%
Asia		29	20%
Global		13	9 %
	Total		144

Africa Asia America Global

19

	*** Distribution by institutional type ***

60

50

48 47

5 3 3 2 2 2 1 1

0

40

30

20

10

21

9

Institutional type Commercial Bank

	Number 48	% 33%
Cooperative	47	33%
MFI	21	15%
Development Bank	9	6%
Islamic Bank	5	3%
International FI	3	2%
International Fund	3	2%
Agricultural Bank	2	1%
Credit union	1	1%
Insurance company	1	1%
NGOs	2	1%
State development bank	2	1%
Total		144

20

	*** Foundation Year ***

32

33

60

FREQUENCY

19

21

< 1950 1950 -1970 1970 -1990 > 1990

> 1000

100 - 1000

7

1

5

23

12

5

2

< 10

10 - 100

31

14

13

5

0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%

Africa America Asia Global

1

2

4

1

*** Number of Branches per FIs ***

Number of Branches per Region

Range	Africa	Number of Branches per Region America Asia Global Total				%
< 10	23	12	5	2	42	29%
10 - 100	31	14	13	5	63	44%
100 - 1000	12	7	7	5	31	22%
> 1000	1	2	4	1	8	6%
Grand Total	67	35	29	13	144	100%

22

*** Agricultural loans***

160%

140%

120%

100%

80%

24%

0% 0%

50%

11%

20%

50%

0%

0% 0%

TYPE OF CREDIT OFFERED BY FINANCIAL

INSTITUTIONS

0%

44% 40%

Farmer credit Agribusiness Credit

60%

40%

79%

33%

0%

71%

67%

29%

0%

100%

100%

100%

33%

23

	*** Gender Equality ***

GENDER PROGRAMMES OFFERED BY FIS

160%
140%
120%		50%
100%
80%			33%
		50%
60%				67%	29%
	0%		33%
40%					19%
				0%
	50%	50%
20%
			33%	33%	29%
0%

0%

60%

50%

4%

13%

22%

9%

13%

33%

35%

21%

0%

0% 0% 0% 0%

Credits facility for women Career development opportunities to female staff Gender Programmes	24

*** Digital Solutions ***

Digital solutions offered by FIs Again

40% 20% 80%		23% 21%
		77%
						5% 19%
				0% 50%
							6% 9%
						24%
							21%

0% 0% 0% 0% 0% 0% 0%

11%

160%

Online Banking E-Products Online Loan Applications

25

140%

120%

100%

80%

60%

40%

20%

0%

Plz sum it up !

26

	*** Summary***

Seven key characteristics of financial institutions

1. Geographic distribution

2. institutional type

3. Foundation Year

4. Branches

5. Agricultural credit

6. Gender Equality

7. Digital solutions

1. Geographic distribution

47%

from Africa

24%

from America

4. Branches

29%

<10 branches

44%

10-100 branches

2. institutional type

33%

commercial bank

33%

cooperative

5. Agricultural credit

58%

Farmer credit

19%

Agribusiness credit

3. Foundation Year

42%

> 1990

6. Gender Equality

15% credit

facility for women

10% Career

development

7. Digital solutions

58% Online

27

banking

Okay descriptive Statistics ...

What about

cluster Analysis ?

28

*** Cluster Analysis ***

Descriptive statistics of the dataset

^{Mean Median Standard}

^{Range Mi}

^Sample

^Variance

^Deviation

^{C 0.96}

^{T 3.44}

^{F 1976}

^{B 215.}

^{AL1 0.58}

^{AL2 0.19}

^{G1 0.15}

^{G2 0.10}

^{G3 0.30}

^{DS1 0.42}

^{DS2 0.13}

^{DS3 0.13}

Wrong !

29

*** k-means Clustering ***

Scale Data

s

30

*** k-means VS hierarchical Clustering ***

31

*** k-means Clustering ***

Cluster no. 1	Observations Number 3 18 35 36 42 48 49 50 62 63 76 84 111 125	Total 14
2	2 7 17 20 26 37 67 75 82 88 114 120 134 135	15
	137
3	10 41 43 47 57 59 64 72 73 74 78 90 92 94 101	29
	102 103 104 117 124 126 127 132 133 139 140
	142 143 145
4	4 12 21 22 23 30 32 34 39 40 52 53 54 56 60 69	19
	70 80 81
5	1 5 6 8 9 11 13 14 15 16 19 24 25 27 28 29 31	67
	33 38 44 45 46 51 55 58 61 65 66 68 71 77 79
	83 85 86 87 89 91 93 95 96 97 98 99 100 105
	106 107 108 109 110 112 113 115 116 118 119
	121 122 123 128 129 130 131 136 138 141

betweenss_totss (1? 10) Silhouette plot

32

*** k-means Clustering ***

How good is 0.14?

Average silhouette width:

·

Si > 0 indicates that the observations are well clustered.

· Si < 0 indicates that the observation was placed in the wrong cluster.

· Si = 0 indicates that the observation is in between two clusters

33

	*** Extracting Results ***

34

Cluster Number

	Average Cluster Name Foundation	Average number of Branches
1	1948 Value chain oriented FIs	517
2	1967 Gender Staff FIs	433
3	1975 Farmer credit provider FIs	215
4	1990 Innovative digital newcomers	95
5	1982 Traditional Banking approaches	137

*** Extracting Results ***

Geographic distribution

Value chain oriented FIs Gender Staff FIs

Farmer credit provider FIs Innovative digital newcomers

Traditional Banking approaches

Africa

Institutional type

Value chain oriented FIs Gender Staff FIs

Farmer credit provider FIs Innovative digital newcomers

Traditional Banking approaches

Agricultural Bank

35

South America

International FI

80%

60%

40%

20%

0%

Asia

Global

state development

bank

100%

Commercial Bank

80%

NGO

60%

40%

20%

MFI

0%

Islamic Bank

cooperative

Credit union

Development Bank

International Fund

Insurance company

	*** Extracting Results ***

Services

Value chain oriented FIs Gender Staff FIs

Farmer credit provider FIs Innovative digital newcomers

Traditional Banking approaches

Farmer credit

80%

Online Loan Applications

60%

40%

20%

E-Products

Online Banking

0%

agri-business credit

Credits facility for women

opportunities to female

staff

100%

36

Gender Programmes

	*** Extracting Results***
Technische Universitet München

Table 30 Cluster's characteristics

Cluster Name	Group 1 Value chain Fls	Group 2 Gender Staff Fls	Group 3 Farmer credit provider Fls	Group 4 Innovative digital newcomers	Group 5 Traditional Banking approaches
Region
Africa	71%	47%	24%	79%	42%
Asia	14%	13%	24%	21%	19%
South America	14%	20%	28%		34%
Global		20%	24%		4%
Institutional Type
Agricultural Bank					3%
Commercial Bank	86%	13%	21%	68%	22%
cooperative	7%	40%	31%	16%	42%
Credit union					1%
Development Bank	7%		10%		7%
Insurance company					1%
International Fl		7%	3%
International Fund			7%		1%
Islamic Bank			10%	5%	1%
MFI		27%	14%	11%	16%
NGD		7%	3%		1%
Average Foundation	1940	1967	1975	1990	1982
Average Branches	517	433	215	95	137
Agricultural Credit
Farmer credit	57%	67%	72%	37%	57%
agri-business credit	86%	20%	0%	26%	12%
Gender Programmes
Credits facility for women opportunities to female staff	7% 0%	47% 100%	7% 0%	16% 0%	13% 0%
Gender Programmes	71%	13%	100%	11%	0%
Digital Solutions
Online Banking	71%	47%	55%	84%	16%
E-P rod ucts	0%	20%	0%	84%	0%
Online Loan	50%	7%	7%	37%	1%
Applications
Total Fls	14	15	29	19	67

Plan

I.Introduction

II.Literature Review

III.Methodology and Data

IV.Analysis and Results

V.Limitations and further research needs

VI.Conclusion

38

VII.Recommendations

	*** Limitations ***

U This database was created based on an English literature review, so many financial institutions from North Africa, South America, and Asia were not considered.

U The structure of the database causes some information to be lost due to specific categories of data. Consequently, some of the information cannot be considered.

U Several categories of variables, such as Total assets, Total equity, Gross loan portfolio, and number of clients can not be considered since several websites did not have information on these variables, so we did not take them into account.

39

U Lack of credible or official websites of many financial institutions, which reduced the sample by 50 FIs.

	*** Further research needs ***

U Deeper analysis must be conducted of an expanded and more diverse set of financial institutions taking into account farmer information services providers, financial institutions from the Spanish and French literature review, etc....

U Research on gender equality programs and their relationship to agricultural finance needs to be done and if promoting credit facilities for women could reduce lending risk and increase farm profitability.

U Evaluation how digital tools can increase farmers' awareness of credit offers by financial institutions is a high priority

40

U Online survey should be conducted with FIs representatives to gather the maximum amount of information necessary for analysis. In this regard, this could analyze the way in which FIs currently fund the agriculture sector, including the approach AVCF.

Plan

I.Introduction

II.Literature Review

III.Methodology and Data

IV.Analysis and Results

V.Limitations and further research needs

VI.Conclusion

41

VII.Recommendations

	*** most important questions ***
1) What are the key underlying characteristics of credit provision of different types of financial institutions in the Global South?		2) To what extent financial institutions promote gender issues and include digital solutions?

42

3) What kind similarities and differences can be observed between financial institutions?

Based on 144 financial institutions

67from Africa

35 from South America

29 from Asia

13 International FI

Agricultural credit

58%

Farmer credit

19%

Agribusiness credit

6. Gender Equality

31% program to empower women

7. Digital solutions

42% digital

solutions

Plan

I.Introduction

II.Literature Review

III.Methodology and Data

IV.Analysis and Results

V.Limitations and further research needs

VI.Conclusion

43

VII.Recommendations

q More SMS o

manag

q Mo

ion of

44

	Source of images

Global South IFS pathways Database

Financial institutions Finance gap Evaluation

Value Chain finance Farmer finance Global Map

Database LFS pub. Finance in common

Farmer problems IFAD pub. Literature review

Climatic factors World Bank pub. Search Engine

Price and market risks CGAP pub. Descriptive statistics

Farm loan Meyer article Cluster analyses

Low profit Key underlaying Excel

collateral Gender Equality R

Bank Digital solutions IFAD pub.

45

Farmer Similarities FIs Angry farmer

Technische Universitet München

***Appendix***

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File Home Insert Page Layout Formulas Data Review View Help

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Synopsis

Af7

Africa

Asia

America

R_€Tata

Fls Literature

D E						F
2	Colour	Signification Africa
4		Asia			limMEMEM
		America		Africa	200
		Global		Asia	52
		Fls from the literature review		America	63
		Notice		Oceania	16
9		Sources		Global	16
10		incomplete information		Total	347
11		Synopsis
12			FI: Financial	Institution
13
14		List of Fls-countries		No. of countries
15	Belgium	Afghanistan	Global South	98
16	France	Algeria	developed cous	8
17	rGermany	Bangladesh
18	Italy	Barbados
19	Lutembou	Belize
20	Netherland	Benin		Attribt
21	UK	Bermuda		N~A 0
22	USA	Bhutan		Credit facility for 1
23		Bolivia		career developm 2
24		Brazil		Gender Program 3
25		Burkina Faso
28		Burundi
27		Cambodia
28		Cameroon		Agricultural Bank	0
29		Cayman Islands		Commercial Ban4	1
30		Central African Republic		cooperative	2
31		Chad		Credit union	3
32		Colombia		Development Bai	4
33		Congo		Insurance comp<	5
34		Cook Island		International FI	6
35		Costa Rica		International Fun	7
36		Côte d'ivoire		Islamic Bank	8
37		Curacao		MFI	9
38		Djibouti		NGO	10
39		Dominica		state developmei	11

J

H I

K

L

Q

R

,nt

Attribute

0

Africa

1

2

Asia

America

3

Global

nn N o I P

Ca

Institutional typtaM^-Number Agricultural Bank	46	13%
Commercial Bank	68	20%
cooperative	76	22%
Credit unions	12	3%
Development Agency	7	2%
Development Bank	52	15%
Development Fund	1	0%
Insurance company	5	1%
International H	6	2%
International Fund	5	1%
MFI	55	16%
NGO	5	1%
state development bank	4	1%
Islamic Bank	5	1%
Total:	347	100%
Digital solution	Attribut
NA	0
Online Banking	1
[-Products: (SMS Bank	2
Online Loan Application	3
Digital foot prints Partner	4

347

Total

45

8

17

2s

8

3

Finance in commo

44

37

109

48

46

0

Technische Universitet München

***Appendix***

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AutoSave (* Off) ® /

47

fx Agricultural Bank

A	A	B Country	C	D .ronym	E F G Type			H Website	I Notice	J I
1	id		Bank
2	1	Algeria	La Banque de 'agr cu turc et du	BA DR	Agricultural Bank	Mchand Bcura	ccntactghadr-hank dc	https:ffHadrLanque.dzf
3	2	Algeria	Caisse Nationale de MutuaJitéA	CNMA	Insurance company	Cherif Benhabiflès	cnma[afcnma-dz	https;//www-cnma-dz/
4	3	Algeria	Crédit Agricole CIB Algérie Spa	CIB	Agricultural Bank	Xavier thom as	https://www.ca-cih.com/contact-us	https//www.ca-cib.c am/
5	4	Benin	institution mutualiste ou coopér	UNACREP	cooperative	TOLOME LAURENT	contact@unacrep-bj	https;//unacrep-bj/
6	5	Benin	REseau NAtional des Caissesvill	RENACA	MFI	Léon GDUKPANIAN	[e-mail]	https;//www.renac abenin.org/		Entreprises	(BC-PA
7	6	Benin	Credit Agric ole Group	CAG	Agricultural Bank	Jean-Guy LARRIVIÈRE	https://international,graupecreditagricale.camffrfcont	https://international,graupecreditagricale.camffrfaccampagneme
8	7	Burkina Faso	Systèmes Financiers DécentralisSFD		MFI	na	[e-mail]	https//www-femme-entrepreneur-bf/structures-de-micro-finances/
9	S	Burkina Faso	Ada microfinance		MFI	Soulemane Djobo	s.djobo@ada-microfinanceiu	https://www.ada-microfinancf	several countries
10	9	Burkina Faso	SOCIAL MICROFINANCE IN BURKI	YIRKI	MFI	Elarik Philouze	elarik_philouzeentrepreneursdumonde_org	https;//www.entrepreneursdumande.arg/en/program/yikri-sodal-
11	10	Burkina Faso	African development Bank	AfDB	Development Bank	Mr Pascal Yembiline	P-YEMBILINEcAFDBARG	https;//www-afdb-org/en/documents/document/burkina-faso-sup
12	11	Burkina Faso	Banque Agricole du Faso	BADF	Agricultural Bank	W AimeZoungrana CLinkedln	[e-mail]	https://www.badf.bf/
13	12	Burundi	Banque Communautaire etAgriE	BCAB	Agricultural Bank	Thierry Willy NIKUZE	[e-mail]	https;//bcab.bi/
14	13	Burundi	confédération des associations	CAPAD	cooperative	Annick Sezibera	capad shirukubute@yahoak	https;//www-capad-info/spip-php?rubrique25&langer
15	14	Cameroon	Credit Agric ale Group	CAG	Agricultural Bank	Jean-Guy LARRIVIÈRE	https://international,groupecreditagricale.cam/fr/tont	https://international,groupecreditagricale.cam/fr/accampagneme
16	15	Cameroon	Banque Camerounaise des Petits	BC-PME	MFI	AMADOU HAMAN& ON	[e-mail]	Banque Camerounaise des Petites et Moyennes
17	16	Cameroon	Ecobank in Cameroon	ECM	MFI	FALL MOUSTAPHA	ecobankenquiries?ecobankcom	https;//ecobank-com/cm/personal-banking/products-services/mi
18	17	Central Africa	Banque de Crédit Agricole et del	BCAD	Development Bank	na	na	https://www goafricaonline.com/en/cf/314491-bcad-banque-de-c
19	18	Central Africa	Credit Agricole Group	CAG	Agricultural Bank	na	https;//international,groupecreditagricole.cam/en/can	https;//international,groupecreditagricole.cam/en/internationak
20	19	Chad	Banque Agricole et commerciale	BAC	Agricultural Bank	na	bac_bank@hactchad-cam	https//bactchad-com/indexapropos-html
21	20	Chad	International Fund for Agri cultu	IFAD	Development Bank	ValantineAchancho	v-achancho@ifad-org	https;//www-ifad-org/fr/web/operations/w/pays/chad
22	21	Chad	Agence FrancaisededevelappenAFD		Development Agency	na	[e-mail]	https://www.afdir/fr/page-region-pays/tchad
23	22	Congo	Equity Bank Congo SA	na	Commercial Bank	James MWANGI	mailiequitybank.cd	https;{/equitybank.cd/index.php
24	23	Congo	African development Bank	AfDB	Development Bank	Alexis Adélé	a-adelecafdb-org	https;//www-afdb-org/fr/news-and-events/press-releases/congo-1
25	24	Côte d'ivoire	Credit Agricole Group	CAG	Agricultural Bank	Jean-Guy LARRIVIÈRE	https;//international,groupecreditagricole-com/fr/tont	https;//international,groupecreditagricole-com/fr/accompagneme
26	25	Côte d'ivoire	Banque Agricole et Investisseme	BAICI	Agricultural Bank	na	info@ hanqueagricoleinv-cam	https;//www-banq ueagricoleinv-cam/index-html
27	26	Côte d'ivoire	Banque Nationale d'Investisseur	BN I	Development Bank	Sauleymane CISSÉ	info ibni.ci	https^-// www.bni.ci/groupe-bni/bni-bref
4 I Synopsis			Africa Asia I America	I Oceall Fls Literature I I R_data
							Cli ... 0 14 I

E7

Technische Universitet München

***Appendix***

is Share P Comments

File Home Insert Page Layout Formulas Data Review View Help

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	B	C	D		E	F	G	H	1	J	K	L	M	N S1	O DSO	P OS3	Q Total Ass =	R Total E · uit	S Gross loan p ·	T	U	V	W	X	Y page	Z Aut	AA	y --
1	r - r -	- r - r - - r - - · r	r y v		· y	y · -	r --L
2	Africa	Cameroon Cooperative i	CamCCUL		Cameroon	cooperative	1968	12	1	0	0	0	0	0	0	0	$ 306,000,000.00	na	$ 188,000,000.00	Fombon l	https:llwr	https:lloa	https:#ca	World Co	1	World Co	mail® woc
3	Africa	Société Générale Côte r	SGBCI		Côte divoir	Commercial Bank	1962	28	0	0	0	1	0	1	0	0	na	$ 27,844,490.00	$ 268,500,450.00	Aymeric ^1	https:llwr	cotedivoi	https:#sc	Enquête	90	CGAP	°gap@ w c
4	Africa	Banque Nationale Dinar	BNI		Côte divoir	Commercial Bank	1959	22	0	1	0	0	1	1	0	0	na	na	na	M. Yousc	https:llwti	info@bni	https:llwt	Enquête	81	CGAP	°gap@wc
5	Africa	Ecobank	ECO		Côte divoir	Commercial Bank	1989	47	0	0	0	0	0	0	1	0	na	$ 195,967,000.00	$ 1,555,378.00	Mr. Paul-	https:llwti	ecobank	https:llwt	Enquête	90	CGAP	cgap@wc
6	Africa	Société Ivoirienne de Ba	SIB		Côte divoir	Commercial Bank	1962	66	0	0	0	0	0	0	0	0	na	$ 17,900,030.00	na	Daouda I	https:llwti	http:llww	http:live	Enquête	90	CGAP	cgap@ w c
7	Africa	Nouvelle Société Interaf	NSIA		Côte divoir	Insurance ocmpar	1906	0	0	0	0	0	0	0	0	0	na	$ 265,475,344.00	na	BJanine		https:llwtiinfo@grohttps:#wt		Enquête	90	CGAP	cgap@wc
8	Africa	Advans Côte d'Ivoire	ADVANS		Côted'ivoir	MFI	2005	9	1	0	1	1	1	0	1	0	na	$ 12,530,021.00	$ 82,340,138.00	Mariamf	https:llwti	https:ller	https:llwt	Enquête	95	CGAP	cgap@wc
9	Africa	MicroCred Côte d'Ivoire	EIB		Côte divoir	MFI	2010	23	0	0	0	0	0	0	0	0	na	$ 5,728,009.00	na	Missa Hil<	https:llw%	https:ller	https:llwr	Enquête	95	CGAP	cgap@ w c
10	Africa	MUCREFAB - Microfinar	MUCREFAI		Côted'ivoir	MFI	1994	9	0	0	1	0	0	0	0	0	na	na	na	na	remuci@	info@mu	https:llwt	Enquête	95	CGAP	cgap@wc
11	Africa	Fonds International pouiFIORA			Côte divoir	MEl	2011	8	0	0	0	0	1	0	0		Dna	na	na			Franck Ahttps:llw%info@fidrhttps:llwtEnquête			85	CGAP	cgap@wc
12	Africa	Union Nationale des Car	UNACOOF		Côte divoir	MFI	1976	4	0	0	1	0	0	0	0	0	na	na	na	SAVANE	https:llci.	info@un:	https:llwr	Enquête	85	CGAP	cgap@ w c
13	Africa	Eswatini Association of`.SA000s			Eswatini	cooperative	1964	40	0	0	0	0	0	1	1	1	na	na	na	na	na		info@sasshttp:llww	World Co	1	World Co	mail@woc
14	Africa	Nib International Bank	NIB		Ethiopia	Commercial Bank	1999	189	1	0	0	0	0	1	0	0	$ 682,278,953.00	$ 605,495,148.00	$ 550,649,573.00	Haimano	https: lier	nibconta	https:lier	AVCF To	38	Calvin Mil	copyright
15	Africa	Harbu Microfinance	HARBU		Ethiopia	MFI	2005	13	0	1	0	0	0	0	0	0	$ 1,300,000.00	na	na	Alazar Ta	https:llwr	harbumfi	https:llbt	Value Ch	246	KIT and II	publicatio
16	Africa	Commercial Bank of Eth	CBE		Ethiopia	Islamic Bank	1942	1714	0	0	0	0	0	1	0	0	###############	na	na	Abreham	https:llwr	cbe@col	https:llcc	Risks anc	29	Rauno 2	die@die-
17	Africa	National Association of f	NACCUG		Gambia	cooperative	1992	6	0	0	0	0	0	0	0	0	$ 40,108,030.00		$ 24,483,575.00	Pa Mend	https:llwr	infonacc	https:ller	World Co	1	World Co	mail® woc
18	Africa	Ghana Co-operative CrE	CUAgh		Ghana	cooperative	1955	11	0	0	0	1	0	0	0	0	$ 27,754,675.00	$ 93,766,590.00	$ 48,067,968.00	Emmanu^,	https:ller	brongah,	https:llwr	World Co	1	World Co	mail® woc
19	Africa	Equity Bank	Equitykeny		Kenya	Commercial Bank	1984	10	1	1	0	0	1	1	0	0	$3,000,000,000.00	na	na	Elizabeth	https:ller	info@eqt	https:llec	AVCF To	8	Calvin Mil	copyright
20	Africa	Agricultural Finance Cor	AFC		Kenya	Agricultural Bank	1963	8	1	1	1	0	0	0	0	0	$6,600,000,000.00	na	na	JACKSO	https:ller	info@agr	https:llwt	AVCF To	12	Calvin Mil	copyright
21	Africa	Faulu Kenya	FAULU		Kenya	MFI	1991	67	1	1	0	1	0	0	0	1	$ 270,615,033.00	na	na		Apollo Nihttps:llerinfo@f		auhttps:llwtAVCFTo		50	Calvin Mil	copyright
22	Africa	Family Bank	FAMILY		Kenya	Commercial Bank	1984	92	1	1	0	0	0	1	1	1	$ 696,000,000.00	$ 114,785,459.00	$ 660,471,889.00	Rebecca	https:ller	info@fan	https:llfa	AVCF To	50	Calvin Mil	copyright
23	Africa	Cooperative Bank	co-opbanl		Kenya	Commercial Bank	1931	100	0	1	1	0	0	1	1	0	$3,900,000,000.00	na	na	William N.	https:ller	customer	https:llwt	AVCF To	50	Calvin Mil	copyright
24	Africa	Unity Finance	k-Unity		Kenya	cooperative	1974	15	1	0	0	0	0	1	1	1	$2,900,000,000.00	na	na	stella war	https:ller	INFO @K		https:llwtAVCFTo	50	Calvin Mil	copyright
25	Africa	Eclof Kneya	ECLOF		Kenya	MFI	1994	43	1	1	0	0	0	0	0	0	na	na	na	Mary Mur	https:ller	info@ecl	https:llwt	AVCF To	50	Calvin Mil	copyright
26	Africa	JuhudiKilimo	JUHUDI		Kenya	MFI	2004	39	1	0	1	0	0	0	0	0	na	na	na	Bernardi	https:ller	info@juh	https:lllul	Agriculta	143	DanielaF	bidem@iE
27	Africa	Malawi Union of Savings	MUSCCO		Malawi	cooperative	1962	47	1	0	1	1	0	0	0	0	na	na	na	Banda	ww.linke	muscccti	https lier	World Cc	1	World Co	mail@woc
28	Africa	Millenniumbim - Particul	BIM		Mozambiq	Commercial Bank	1995	138	0	0	1	0	0	0	0	1	na	na	na	Miguel	ww.linke	cac@mill	https:llmi	UserGuir	10	CGAP	cgap@wc
29	Africa	socremo banco de micrt	SOREMCC		Mozambiq	Commercial Bank	1998	13	0	0	0	0	0	0	0	0	na	na	na	Manjate	ww.linke	secretari.	http:llww	User Guit	21	CGAP	cgap@ w c
30	Africa	African Banking Corpora	BancABC		Mozambiq	Commercial Bank	1999	10	0	0	0	0	0	0	0	0	$1,810,000,000.00	na	na	Silva	wwlinke		mz-callc,https:llwr	User Guit	77	CGAP	cgap@wc
31	Africa	Banco Mais	BANCOMP		Mozambiq	Commercial Bank	1999	7	0	0	0	0	0	1	0	1	na	na	na	Jivane	ww.linke		info@bahttps:llwt	User Gus	77	CGAP	cgap@wc
32	Africa	Banco Unico	BANCOUN		Mozambiq	Commercial Bank	2010	2	0	0	0	0	0	0	0	0	na	na	na	Carlos	we linke		https:llwr	User Guit	77	CGAP	cgap@ w c
33	Africa	Barclays Bank	ABSA		Mozambiq	Commercial Bank	1991	3	0	0	0	0	0	1	0	1	$9,100,000,000.00	na	na	Namarro	ww.linke		linhaclierhttps:llwr	User Guit	77	CGAP	cgap@wc
34	Africa	Central Bank of West Afr	BCEAO		Niger	International FI	1962	3	0	0	0	0	0	0	0	0	na	na	na	na		https:ller	https:llwt	AVCF To	104	Calvin Mil	copyright
35	Africa	SunTrust Bank	Suntrust		Nigeria	Commercial Bank	2009	8	0	1	1	0	0	1	1	0	$ 128,477,119.00	$ 28,770,351.00	$ 62,438,759.00	Ayodeji E	https:ller	helpdesk	https:lls.	CGAP Sr	92	CGAP	cgap@ w c
36	Africa	Keystonebank	KEWSTON		Nigeria	Commercial Bank	1981	154	0	1	0	0	1	1	0	0	$ 1,916,000,000.00	$ 213,300,000.00	na	Olaniran	https:ller	contactc	https:llwt	CGAP Sr	92	CGAP	cgap@wc
37	Africa	Union Bank of Nigeria	UBN		Nigeria	Commercial Bank	1917	320	1	1	0	0	1	1	0	1	$ 4,100,000,000.00	na	na	David Ad	https:ller	customei	https:llwt	CGAP Sr	92	CGAP	cgap@ w c
38	Africa	UBAGroupCorporate	UBAG		Nigeria	Commercial Bank	1948	67	0	0	0	1	1	1	0	0	###############	na	na	Kennedy		https:llwtiinfo@hbrhttps:llwt		CGAP Sr	92	CGAP	cgap@wc
i Irsynopsis ' Africa					I Asia I	America 1		Fls Literature			^1 Final_Database						R_data E ...
																		0i I I	I
				***Appendix***
Technische Universitet München

R5tudio

File Edit Code View Plots Session Build Debug Profile Tools Help

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R scriptR* X X20210922_database_Fls_144T PJ Clustering 1.R 9J Clustering 2.R tJ ??

I8 D Source on save I Q - I I. - Run Source

Packages clusterSim, dplyr, and 3 others required but are not installed, Install Don't Show Again

1 # Descriptive Analysis #

2 datai e- na.omit(x20210922_database_FIs__MAT)

3 data- data1[-1]

4 plot(data)

5 data

6 summary(data)

7 #Scale Data #

8- Data_scaled = apply(data, 2, function(r) f

9 if (sd(r) != 0)

10 res = (r - mean(r))/sd(r) else res D * r

11- res I)

12 summary(Data_5 caled)

13 # install packages#

14 # install.packages("dplyr")

15 # install. packages("ggplot2")

16 # install.packages("ygfortify")

17 # install.packages("factoextra")

18 # install.packages("stats")

19 # install. packages("clustersim")

20 # load required libraries #

21 library(stats)

22 library(dplyr)

23 library(ggplot2)

24 library(ggfortify)

25 library(factoextra)

26 # wss plot function #

27- wssplot r- function(Data_scaled, nc=15, seed=1234){

28 wss r- (nrow(Data_sealed)-1)*sum(apply(Data_5caled,2,var))

29- for (i in 2:nc){

30 set.seed(seed)

31- wss[ï] e- sum(kmeans(Data_scaled, centers=i)$withinss)]

32 plat(i:nc, wss, type="b", xlab="Number of clusters",

33- ylab="within groups sum of squares")}

34 # wss Plot to choose maximum number of clusters #

35 wssplot(Data_scaled)

11:9 8 <Function}() RScript

Environment History Connections Tutorial

LJIPIPIPIPIDILIDIP

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()data 143 obs. of 12 variables

Data_scaled num [1:143, 1:12] -0.93 -0.93 -0.93 -0.93 -0.93

O datai 143 obs. of 13 variables

O- final List of 9

O- fith List of 7

O- gap_stat List of 6

Q

- KM List of 9

Q- x20210922_database__FI... 161 obs. of 13 variables

- 'dist' num [1.10153] 4.35 4.4 3.65 2.06 3.03 ...

chr [1:300] "-0.3€32" "-0.586" "0.1408' ^.0.098" "0.6075' "-0._. int [1:143] 5 4 3 2 2 2 4 2 2 2 ...

'silhouette' num [1:143, 1:3] 5 4 3 2 2 2 4 2 2 2 ...

values

_d

- desc KM. cl usters

- sil Functions

wssplot function (Data_scaled, ne = 15, seed = 1234)

Console 5¹ Fie, Plots Packages Help Viewer 5¹

49

	***Appendix***
Technische Universitet München RStudio File Edit Code View Plots Session Build debug Profile Tools Help ak ^r - H _ · 4 Go to Pilejfundior Addins -		R Project: {None) -

K.max = 10, B = 50)

# Print the result

#print(gap_stat, method = "firstmax") #fviz_gap_stat(gap_stat)

# K-Means cluster #

Ki= kmeans(Data_scaled,5)#I

# Evaluating Cluster Analysis#

# Cluster plot 2#

autoplot(KM,Data_5caled,frame=TRUE)

# segmentation & visualization # KN1.clusters C- KM$cluster

rownames(Data_scaled) <- data1Sid

fviz_cluster(list(data=Data_scaled,cluster=KM.clusters))

# cluster Membership #

KM$cluster

table(Ktn.clusters, datal$id) table(datai$id, la+l.clusters)

# clusters center # KM$centers

# descriptive statistics at the cluster level library(clustersim) desc r- cluster.Description(Data_scaled,KM$cluster) print(desc)

summary(desc)

library(factoextra)

sil cents- silhouette(KM$cluster, dist(Data_scaled)) fviz_si1houette(sil)

# Hierarchical clustering .... d <- dist(Data_scaled) fith <- hclust(d, "ward.o2") piot(fith)

j RscriptR" ^--.X20210422_database_Frs_ht4T x P] Clustering 1.R lq] Clustering 2.R o Environment History Connections Tutorial

W J 18 D Source on Save _q 4
· - I I - Run I a Source = = 8 I ⁰ Import Dataset - _ 122 MiB - j

Packages elusterSim, dplyr, and 3 others required but are not installed. Install Don't Show Again % R - I ; Global Environment

§ Data

cl List of 10

O data 143 obs. of 12 variables

Data_scaled num [1:143, 1:12] -0.93 -0.93 -0.93 -0.93 -0,93

O datai 143 obs. of 13 variables

Ofinal List of 9

Ofith List of 7

ü gap_stat List of 6

Q K List of 9

Q x20210922_database_FI... 161 obs. of 13 variables

values

d

desc

KM.clusters

sil

Functions

wssplot function (Data_scaled, ne = 15, seed = 1234)

RScript

5 Fies Plots Packages Help Viewer

49

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55:27 [fop Level)

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Console

5171

'dist' num [1:10153] 4.35 4.4 3.65 2.06 3.03 ...

chr [1:300] "-0.3€32" "-0.586" "0.1408" '0.098' "0.6075" "-0._. int [1:143] 5 4 3 2 2 2 4 2 2 2 ...

'silhouette' num [1:143, 1:3] 5 4 3 2 2 2 4 2 2 2 ...

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