a study on financial inclusion in aspirational …joics.org/gallery/ics-1592.pdf · a study looks...

A STUDY ON FINANCIAL INCLUSION IN ASPIRATIONAL

DISTRICTS OF INDIA

SHOUNAK DAS

Guest Lecturer in Commerce, Vivekananda College(Thakurpukur)

E-MAIL: [email protected]

ABSTRACT

Financial inclusion is most vital for developing a healthy economy and for ensuring sustainability in the health

of the economy. The way blood ensures healthy body, the finance; the blood of the economy ensures healthy

economy. Financial inclusion means development of formal and adequate no of financial institutions in

different parts of the country, so that people and other economic units can avail and use them economically to

save and borrow finance and thereby ensures its free flow.

The study is basically deals with how far these 115 backward districts of India are financially included. In my

study information has been collected regarding various items like no of bank branches, ATMs, banking

correspondents, Bank Mitras, etc. in some of the the backward Districts. Data has also been collected

regarding various social parameters; districts and state wise. I tried to find out correlations among those

quantitative data and also performed various calculations based on those data. Based on the analysis of

various results I conclude that backward districts of different states are not equally financially excluded or

included. Several factors including social and economic; impacted financial inclusion both district wise and

state wise in respect to their backward Districts. Based on the results and analysis I put forward several

recommendations for taking better initiative to make financial inclusion more and more feasible and successful

in backward Districts of the country.

Keywords: Financial Inclusion, Bank Mitras, Banking correspondents, ATM.

Journal of Information and Computational Science

Volume 9 Issue 10 - 2019

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mailto:[email protected]

BACKGROUND:-

India being a developing country, India’s primary need is to develop those underdeveloped backward people

who are economically week and marginalized. The primary requirement to develop those people is to provide

them with adequate no of formal financial institutions to avail cheap and adequate amount of finance when

they need it and to invest their surplus when they need it. It is also for making available to them government’s

various financial assistance and various social security benefits. these not only ensure their economic

improvement but also sustain it by ensuring improvement in social security net. India’s backward districts

basically lack enough no of formal financial institutions and hence are basically not so much financially

included, for which they mostly remain poor and marginalized. It is extremely important to gather information

about how far these places are financially included and what factors are contributing toward their financial

inclusion and exclusion. It is very important to find out those contributing factors, so that adequate steps can be

taken to remove obstacles in the path of their better financial inclusion.

Backward Districts:- The central government has launched a program for the development of the 115 most

backward districts of the country and termed them as Aspirational Districts, in January 2018. The aim of the

government is to develop these backward districts economically, socially and from infrastructure point of view

so as to make India more developed.

NITI Ayog along with Lupin foundation act as a nodal agency in implementing various schemes for the

development of those backward districts in a time bound manner.

Financial inclusion:- It means there is adequate presence of cheap formal financial institution in all the parts of

a country so that individual and other economic units avail various financial services to meet their needs for

savings and deposit of finance, transfer of finance, etc.

In a word Financial Inclusion is the theme word for free flow of finance in an economy and thereby ensures

health and depth in an economy and equity in economic development in different parts of the country. Over the

years government has taken several initiatives for the financial inclusion of backward areas and there are

various results of those initiatives. Some schemes for financial inclusion are holistic in nature; which are

focuses on overall development of the backward areas and this Aspirational Districts development initiative is

such a scheme, it is not focused only on financial inclusion.

LITERATURE REVIEW:-

There has been lot of study regarding the level of and factors impacting the financial inclusion of different parts

of the country, as financial inclusion is always an important area of study for a vast and diverse county like

India; to achieve its aim of economic development through path of greater financial mobility.

A study looks into status of financial inclusion of tribal people of 6 villages in tribal concentrated districts of

Bolangir and Mayurbhanj, It was found that about 71.7 per cent of households had no savings bank accounts;

70.7 per cent were not involved in self-help group activities and 97.7 per cent did not have post office savings

accounts Additionally, a logit regression model was basically used to identify the various determinants of

financial inclusion of tribal households in villages. The results revealed that years of education attained by the

household head, size of private-owned land, total annual income of the household and participation in

MGNREGS scheme were significant determinants for financial inclusion among tribal people (Sahoo, A.K.,

Pradhan, B. B.& Sahu, N. C. February-2017. Determinants of Financial Inclusion in Tribal Districts of Odisha:

An Empirical Investigation. Social Change journal. SAGE Publications). A study has been conducted based on



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primary survey of rural households of Ujjain district of Madhya Pradesh to find level of financial inclusion and

factors affecting it. It has been found various social and economic factors impacted financial inclusion (

Shastri, A. December 2014. Financial inclusion in Madhya Pradesh, a study with reference to rural population.

Journal of Business Management and Social Sciences Research. Blue Ocean Publications).

To understand the perception of economically backward sections regarding important aspects of financial

inclusion and how far perception vary among different groups are looked into and it has been found that most

people believe that banking personnel are taking enough initiatives to motivate them in taking services of

formal financial institutions(Singh, R.I. May-June 2015. Perceptions of People from Economically Backward

Section towards Financial Inclusion: An Empirical Study of Ludhiana District Singh. Journal of Economics

and Finance. International Organization of Scientific Research Publications). A study was conducted to

identify the factors determining the level of financial inclusion in geographically remote areas of North East

by primary survey of 411 households of Assam and Meghalaya, matters significantly contributing to inclusion

were identified using a logistic regression model and finding is, Level of financial inclusion in north‐east India

remains very low. Income, awareness of self-help groups (SHGs), financial information from various channels

and education are influential factors leading to inclusion. Factors like area terrain and receipt of government

benefit individually do not facilitate inclusion. However, recipients of government benefits in plain areas show

increased level of inclusion. Nearness to post offices and banks increases the likelihood of inclusion in rural

area ( Bhanot, D., Bapat V.& Bera S. September 2012. Studying financial inclusion in north‐east India.

International Journal of Bank Marketing. Emerald Group Publications). A study was conducted to identify

success of various government schemes in ensuring financial inclusion in India over different economic phases

of India based on secondary data and finding is, despite various attempts by RBI and after lot of spending it

failed to reach expected or targeted level of inclusion (Bedi, A. September 2015. Recent Vision of Financial

Inclusion in India. International Journal of Advance Research in Computer Science and Management

Studies.IJARCSMS Publications). NABARD has conducted an all India Rural Financial Inclusion Survey

2016-2017 by collecting sample data from 245 districts, it measures financial inclusion in terms of loans,

savings, investment, pension, remittances and insurance. It also looks into behavioural aspect of rural people

regarding financial inclusion.

RESEARCH GAP:

Through my literature review I have not found any study which has been conducted on financial inclusion

aspect of different backward districts of all the parts of India at a time. The research conducted by NABARD

considered rural areas of 245 districts in its study, irrespective of its level of overall development. The above

papers are the papers which I used as my reference and brief review of literature in writing this paper. For this I

considered an overall study on financial inclusion in backward Districts from different parts of India can be

considered as a research gap.

OBJECTIVES OF THE STUDY:-

In order to know the level of financial inclusion and factors responsible for it in different backward Districts,

the following are my research objectives.

1. To find out the level and variance of financial inclusion achieved by different backward districts in terms of

no of different types of formal financial outlets. The research will also try to find out level and variance of



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financial inclusion in different states in terms of average no of outlets and percentage of active outlets in their

backward districts.

2. Determination of different correlations and logical analysis of those results to identify the major factors

which are impacting the level of financial inclusion in different backward districts and states as a whole in

terms of their backward districts

.

3. To find out possible policy measures and giving of recommendations for better financial inclusion of

different backward districts.

RESEARCH METHODOLOGY:-

My study is based on the data of the population (115 backward districts identified by Government of India as

backward districts and termed them as Aspirational Districts). Quantitative data has been collected on various

items regarding financial inclusion and social parameters of the backward districts and of the states to which

backward districts belong. There form calculation of various new quantitative data regarding backward districts

and states to which they belong has been done. Finally various correlations between those quantitative data has

been calculated. Based on the analysis of collected data, calculated data and correlation results it has been

concluded to what extant different districts and states(in respect to their backward districts) are financially

included, what are the different factors influencing the financial inclusion and what are the possible remedies

for these problems regarding financial inclusion.

Financial inclusion is defined in terms of number of 1) Active Bank Mitras, 2) Banking Correspondent,

3)ATM, 4)Bank Branch 5) Total number of outlets on an average in a backward district of a state 6)

Percentage of Active Bank Mitras, 6) Total number of outlets in backward districts-state-wise.

Factors impacting financial inclusion is defined in terms of 1) Social Progress Index, 2) Rural Electrification,

3) Literacy Rate, 4)Level of economic development, 5) Level of Central and State government fundings, 6)

State specific features, by calculating below mentioned correlations and by analyzing those correlations on the

basis of various informations.

Following data has been collected regarding 115 backward districts of India as notified by government of

India.

1) Number of fixed location Bank Mitras deployed 2) Number of inactive Bank Mitras 3) Number of active

Bank Mitras doing transactions. 4) Number of ATMs 5) Number of Banking Correspondents 6) Number of

Bank Branches 7) Average literacy Rate of backward districts; state wise.

The above data from serial no. (1 to 6) are data upto 02/03/2018 and sourced from Official website of ministry

of finance (under Jan Dhan Yojna data).

Data on serial no 7 has been as per Census 2011.

Following data has been collected regarding states to which Aspirational Districts belong.

1) Literacy Rate(census 2011) 2) Village Electrification(2014-15) 3) Social Progress Index( 2017,The

study released by Institute for Competitiveness, India in collaboration with Social Progress Imperative

and Prof. Michael E Porter of Harvard Business School is the first edition of a sub-national Social

Progress Index for India.)



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Following information has been calculated.

1) State wise percentage of Active Bank Mitras 2) State wise average literacy rate in terms of Aspirational

Districts 3) Total number of outlets on an average in a backward district of a state. 3) Difference between state

wise literacy rate and state wise average literacy rate in terms of backward districts 4) Total number of outlets

in backward districts-state-wise. 5) Percentage of active Bank Mitras on an average in a backward district of a

state.

Following correlations has been calculated based on the above data for finding factors impacting financial

inclusion.

1) State wise percentage of Active Bank Mitras (dependent variable) and Social Progress Index(independent

variable) 2) State wise percentage of Active Bank Mitras(dependent variable) and rural

electrification(independent variable) 3) Social Progress Index(dependent variable) and rural

electrification(independent variable) 4) State wise percentage of Active Bank Mitras (dependent variable)

and Aspirational Districts average literacy rate-state wise(independent variable) 5) Total no of outlets in

average(independent variable) and State wise percentage of Active Bank Mitras (dependent variable) 6)Total

no of outlets in average(dependent variable) and Social Progress Index(independent variable) 7) Total no of

outlets in average(dependent variable) and rural electrification(independent variable) 8) Average literacy rate

of Aspirational Districts-state wise (independent variable) and total no of outlets in average(dependent

variable) 9) Average literacy rate of Aspirational Districts-state wise (independent variable) and State wise

percentage of Active Bank Mitras (dependent variable) . 10) Average literacy rate of Aspirational Districts-

state wise (dependent variable) and Social Progress Index(independent variable) 11) average literacy rate of

Aspirational Districts-state wise(dependent variable) and rural electrification(independent variable) 12)

Difference in literacy rate(dependent variable) and state wise literacy rate (independent variable) 13)

Difference in literacy rate(dependent variable) and Social Progress Index (independent variable) 14)

Difference in literacy rate(independent variable) and State wise percentage of Active Bank Mitras (dependent

variable). 15) Difference in literacy rate(independent variable) and total no of outlets in average(dependent

variable) 16) Active Bank Mitras(dependent variable) and total fixed location Bank Mitras (independent

variable) 17) Bank Branch(independent variable) and Banking Correspondent(dependent variable) 18) Bank

branch(independent variable) and ATMs(dependent variable) 19) Bank Branch(independent variable) and

total fixed location Bank Mitras(dependent variable) 20) Bank Branch(independent variable) and active Bank

Mitras(dependent variable).

The correlation values are classified in following categories

Strength of Association Positive Negative

Small .1 to .3 -0.1 to -0.3

Medium .3 to .5 -0.3 to -0.5

Large .5 to 1.0 -0.5 to -1.0



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ANALYSIS OF DATA:-

BANK MITRA REPORT FOR ASPRIATIONAL DISTRICTS, AS ON 02.03.2018

Table-1.

StateName DistrictName Number of fixed

location Bank

Mitras deployed.

Number of

inactive

Bank Mitras

deployed.

Number Of

Active Bank

Mitras doing

transactions

Andhra Pradesh Vizianagaram 429 20 409

Andhra Pradesh Visakhapatnam 479 24 455

Andhra Pradesh Y.S.R. 370 15 355

Arunachal

Pradesh

Lohit 2 1 1

Assam Dhubri 184 11 173

Assam Goalpara 94 5 89

Assam Barpeta 175 6 169

Assam Hailakandi 77 5 72

Assam Baksa 95 8 87

Assam Darrang 101 4 97

Assam Udalguri 113 5 108

Bihar Sitamarhi 406 2 404

Bihar Araria 385 2 383

Bihar Purnia 426 6 420

Bihar Katihar 347 7 340

Bihar Muzaffarpur 606 5 601

Bihar Begusarai 284 14 270

Bihar Khagaria 161 5 156

Bihar Banka 282 13 269

Bihar Sheikhpura 58 1 57

Bihar Aurangabad 270 5 265

Bihar Gaya 300 3 297

Bihar Nawada 161 3 158

Bihar Jamui 194 8 186

Chhattisgarh Korba 105 16 89

Chhattisgarh Rajnandgaon 105 7 98

Chhattisgarh Mahasamund 123 6 117

Chhattisgarh Kanker 78 15 63

Chhattisgarh Bastar 103 14 89

Chhattisgarh Narayanpur 65 17 48

Chhattisgarh Dantewada 40 15 25

Chhattisgarh Bijapur 40 5 35

Chhattisgarh Sukma 46 18 28

Chhattisgarh Kondagaon 67 17 50



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Gujarat

Gujarat

Hryana

Himachal

Pradesh

Jammu &

Kashmir

Jammu &

Kashmir

Jharkhand

Jharkhand

Jharkhand

Jharkhand

Jharkhand

Jharkhand

Jharkhand

Jharkhand

Jharkhand

Jharkhand

Jharkhand

Jharkhand

Jharkhand

Jharkhand

Jharkhand

Jharkhand

Jharkhand

Jharkhand

Jharkhand

Karnataka

Karnataka

Kerala

Madhya Pradesh

Madhya Pradesh

Madhya Pradesh

Madhya Pradesh

Madhya Pradesh

Madhya Pradesh

Madhya Pradesh

Madhya Pradesh

Maharashtra

Maharashtra

Dohad

Narmada

Mewat

Chamba

Kupwara

Baramula

Garhwa

Chatra

Giridih

Godda

Sahibganj

Pakur

Bokaro

Lohardaga

Purbi Singhbhum

Palamu

Latehar

Hazaribagh

Ramgarh

Dumka

Ranchi

Khunti

Gumla

Simdega

Pashchimi

Singhbhum

Raichur

Yadgir

Wayanad

Chhatarpur

Damoh

Barwani

Rajgarh

Vidisha

Guna

Singrauli

Khandwa

Nandurbar

Washim

195

124

128

115

104

72

123

149

245

158

144

89

161

54

129

192

81

209

93

170

236

48

117

77

148

155

103

50

250

386

203

244

167

133

168

177

316

219

3

1

10

14

2

2

0

11

12

4

1

1

6

1

7

7

2

14

5

3

12

5

7

2

12

4

8

19

30

71

21

25

1

9

8

13

44

27

192

123

118

101

102

70

123

138

233

154

143

88

155

53

122

185

79

195

88

167

224

43

110

75

136

151

95

31

220

315

182

219

66

124

160

164

272

192



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Maharashtra

Maharashtra

Manipur

Meghalaya

Mizoram

Nagaland

Odisha

Odisha

Odisha

Odisha

Odisha

Odisha

Odisha

Odisha

Punjab

Punjab

Rajasthan

Rajasthan

Rajasthan

Rajasthan

Rajasthan

Sikkim

Tamil nadu

Tamil nadu

Telangana

Telangana

Telangana

Tripura

Uttar Pradesh

Uttar pradesh

Uttar pradesh

Uttar pradesh

Uttar pradesh

Uttar pradesh

Uttar pradesh

Uttar Pradesh

Uttarakhand

Uttarakhand

West Bengal

West Bengal

West Bengal

West Bengal

West Bengal

Gadchiroli

Osmanabad

Chandel

Ribhoi

Mamit

Kiphire

Dhenkanal

Gajapati

Kandhamal

Balangir

Kalahandi

Rayagada

Koraput

Malkangiri

Moga

Firozpur

Dhaulpur

Karauli

Jaisalmer

Sirohi

Baran

West District

Virudhunagar

Ramanathapuram

Adilabad

Warangal

Khamma

Dhalai

Chitrakoot

Fatehpur

Bahraich

Shrawasti

Balrampur

Siddharthnagar

Chandauli

Sonbhadra

Udham Singh N.

Hardwar

Dakshin Dinajpur

Maldah

Murshidabad

Birbhum

Nadia

190

177

20

13

5

7

163

86

136

206

198

130

202

94

105

118

124

184

153

127

222

20

347

247

330

512

446

36

139

236

322

77

197

637

250

226

159

116

219

386

680

472

458

128

13

5

6

1

4

5

25

22

29

46

25

89

30

5

4

5

9

18

12

11

5

8

9

14

23

54

2

4

3

3

1

8

110

41

4

25

5

0

1

5

13

1

62

164

15

7

4

3

158

61

114

177

152

105

113

64

100

114

119

175

135

115

211

15

339

238

16

489

392

34

135

233

319

76

189

527

209

222

134

111

219

385

675

459

457



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From Table 1 following results are presented.

Districts like Muzzafarnagar, Murshidabad and Siddharthnagar are best performing districts;

whereas districts like West District , Mamit, Ribhoi, Chandel, Kiphire, Gumla, Ranchi, Dumka,

Lohit are worst performing districts in terms of number of active Bank Mitras. The determining

factors are level of development of cottage and small scale industries, food processing industries,

agricultural development, government funding and transport infrastructure.

Following correlation has been computed.

1. Correlation between Total number of Active Bank Mitras and Total number of fixed location

Bank Mitras is 0.801567

There is a extremely high and positive correlation exists between the two, it is because more no

of Bank Mitras signify the area is more and more economically developed hence more Bank

Mitras can run profitably and successfully so most of them are active, where economic

conditions are poor, small no of Bank Mitras are operating and many remained inactive due to

less use of those outlets. Its signify those areas which are more poor are and more backward they

remain so and those which are in better condition develop more. So more a place is developed its

surrounding areas also get development.



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BANKING INFRASTRUCTURE IN ASPIRATIONAL DISTRICTS AS ON (02.03.18) Table-2.

State Name

Districts Name

ATM

Banking

Corresponde

-nt

Bank

Branch

Andhra Pradesh

Andhra Pradesh

Andhra Pradesh

Arunachal Pradesh

Assam

Assam

Assam

Assam

Assam

Assam

Assam

Bihar

Bihar

Bihar

Bihar

Bihar

Bihar

Bihar

Bihar

Bihar

Bihar

Bihar

Bihar

Bihar

Chhattisgarh

Chhattisgarh

Chhattisgarh

Chhattisgarh

Chhattisgarh

Chhattisgarh

Chhattisgarh

Chhattisgarh

Chhattisgarh

Chhattisgarh

Gujarat

Gujarat

Haryana

Himachal Pradesh

Jammu & Kashmir

Jammu & Kashmir

Jharkhand

Visakhapatnam

Vizianagaram

Y.S.R.

Lohit

Baksa

Barpeta

Darrang

Dhubri

Goalpara

Hailakandi

Udalguri

Araria

Aurangabad

Banka

Begusarai

Gaya

Jamui

Katihar

Khagaria

Muzaffarpur

Nawada

Purnia

Sheikhpura

Sitamarhi

Bastar

Bijapur

Dakshin Bastar

Dantewada

Kondagaon

Korba

Mahasamund

Narayanpur

Rajnandgaon

Sukma

Uttar Bastar Kanker

Morbi

Narmada

Mewat

Chamba

Baramula

Kupwara

Bokaro

1254

307

485

6

26

146

91

95

62

59

35

120

133

71

159

338

56

129

65

434

77

186

36

128

97

13

35

31

160

83

10

129

8

55

103

58

43

58

140

65

327

539

473

415

0

99

187

152

204

101

109

112

363

336

215

301

460

218

418

163

797

188

448

58

464

96

38

32

31

110

124

20

134

16

67

89

73

147

112

129

96

239

764

299

376

8

33

94

53

60

60

38

34

129

129

99

157

278

121

174

114

348

130

192

33

156

100

27

40

52

106

105

26

159

19

94

131

58

95

143

163

193

226



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Jharkhand

Jharkhand

Jharkhand

Jharkhand

Jharkhand

Jharkhand

Jharkhand

Jharkhand

Jharkhand

Jharkhand

Jharkhand

Jharkhand

Jharkhand

Jharkhand

Jharkhand

Jharkhand

Jharkhand

Jharkhand

Karnataka

Karnataka

Kerala

Madhya Pradesh

Madhya Pradesh

Madhya Pradesh

Madhya Pradesh

Madhya Pradesh

Madhya Pradesh

Madhya Pradesh

Madhya Pradesh

Maharashtra

Maharashtra

Maharashtra

Maharashtra

Manipur

Meghalaya

Mizoram

Nagaland

Odisha

Odisha

Odisha

Odisha

Odisha

Odisha

Odisha

Odisha

Punjab

Punjab

Rajasthan

Rajasthan

Rajasthan

Rajasthan

Chatra

Dumka

Garhwa

Giridih

Godda

Gumla

Hazaribagh

Khunti

Latehar

Lohardaga

Pakur

Palamu

Pashchimi Singhbhum

Purbi Singhbhum

Ramgarh

Ranchi

Sahibganj

Simdega

Gadag

Gulbarga

Wayanad

Barwani

Chhatarpur

Damoh

East Nimar

Guna

Rajgarh

Singrauli

Vidisha

Gadchiroli

Jalgaon

Nanded

Nandurbar

Chandel

Ribhoi

Mamit

Kiphire

Balangir

Dhenkanal

Gajapati

Kalahandi

Kandhamal

Koraput

Malkangiri

Rayagada

Firozpur

Moga

Barmer

Dhaulpur

Jaisalmer

Karauli

46

83

47

169

70

39

215

24

29

31

42

93

119

521

142

698

53

22

148

353

137

76

125

77

116

108

101

119

141

57

395

268

103

4

38

5

6

159

115

59

115

63

135

32

120

163

209

139

69

81

101

183

168

135

360

149

128

248

49

88

48

85

199

134

163

120

284

140

70

116

263

58

254

252

390

197

138

307

145

170

217

528

588

276

13

18

3

6

208

156

103

179

131

159

84

114

153

104

297

202

77

161

57

113

63

145

100

76

157

47

42

43

56

110

137

317

109

444

73

48

179

246

156

105

154

92

126

103

125

88

138

120

549

233

107

4

42

11

3

153

127

58

142

68

122

47

97

191

282

161

74

77

112



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Note: ATM: Automated Teller Machines.

From Table 2 following results are presented.

Rajasthan Sirohi 85 101 120

Sikkim East District 123 27 87

Tamil nadu Ramanathapuram 198 270 166

Tamil nadu Virudhunagar 351 276 248

Telangana Adilabad 61 97 88

Telangana Khammam 198 259 203

Telangana Warangal 337 105 193

Tripura Dhalai 28 47 49

Uttar pradesh Bahraich 124 287 211

Uttar pradesh Balrampur 71 172 131

Uttar pradesh Chandauli 121 209 169

Uttar pradesh Chitrakoot 37 124 90

Uttar pradesh Fatehpur 129 358 250

Uttar Pradesh

Uttar pradesh

Uttar Pradesh

Uttarakhand

Uttarakhand

West Bengal

West Bengal

West Bengal

West Bengal

West bengal

Shrawasti

Siddharthnagar

Sonbhadra

Hardwar

Udham Singh Nagar

Birbhum

Dakshin Dinajpur

Maldah

Murshidabad

Nadia

41

85

128

438

366

288

122

235

547

535

70

343

214

124

149

587

213

421

749

879

77

129

148

277

309

287

123

236

418

367



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Nadia, Murshidabad, Hridwar, Ranchi, Muzzafarpur, YSR, Vishakapattanam are best performing

districts; whereas Lohit, Nrayanpur, Sukma, Ribhoi, Mamit, Kiphire are worst performing

districts in terms of number of ATMs. Determining factors are development of tourism, centre of

trade, development of industries and agriculture and good infrastructure.

Vishakapattanam, Jalgaon, Nanded, Birbum, Murshidabad and Nadia are best performing

districts; whereas Lohit, Nrayanpur, Sukma, Ribhoi, Mamit, Kiphire are worst performing

districts in terms of Banking Correspondents. Determining factors are development of industries,

agriculture and tourism, good transport infrastructure and also internal disturbances.

Vishakapattanam, YSR, Jalgaon, Murshidabad are best performing districts whereas Lohit,

Bastar, Malkangiri, Ribhoi, Mamit, Kiphire are worst performing states in terms of Bank

Branches. Determining factors are development of industries and agriculture, transport

infrastructure and peace of the region.

Following correlations has been computed.

2. Correlation between Bank Branch and Banking Correspondent is 0.704853

This correlation is also high and positive as because banking correspondents are supported by or

established by bank branches, so if a district has more Bank Branches more banking outlets are

supported by it in rural areas of those districts. So more a place is developed its surrounding

areas also get development.

3. Correlation between Bank Branch and ATM is 0.928318

The correlation is extremely high and positive as because more a place is economically

developed more and more bank branches run profitably in those areas and Bank Branches

deployed ATMs.

STATE WISE DATA ON POPULATION AND LITERACY IN RESPECT OF ASPIRATIONAL DISTRICTS Table-3.

State 1/(4) 2 3/(5)

Andhra Pradesh 67.4%(3.03%) 64.37% 6131(2043)

Arunachal Pradesh 66.95%(-1.23%) 68.18% 15(15)

Assam 73.18%(7.24%) 65.94% 2645(377)

Bihar 63.82%(4.66%) 59.16% 12266(943)

Chattisgarh 71.04%(14.84%) 56.52% 2659(265)

Gujarat 79.31%(1.33%) 77.98% 827(413)

Haryana 76.64%( 22.56%) 54.08% 403(403)

Himachal Pradesh 83.78%(11.61%) 72.17% 414 (414)

Jammu & Kashmir 68.74%(4.17%) 64.57% 958 (479)

Jharkhand 67.63%(3.68%) 63.95% 10213(537)

Karnataka 75.60%(5.61%) 69.99% 1551(775)



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Kerala 93.91%(4.88%) 89.03% 382 (382)

Madhya Pradesh 70.63%(7.59%) 63.04% 5197 (649)

Maharashtra 82.91%(9.81%) 73.10% 4210 (1052)

Manipur 79.85%(8.74%) 71.11% 36(36)

Meghalaya 75.48%(-0.19%) 75.67% 105(105)

Mizoram 91.58%(6.65%) 84.93% 23(23)

Nagaland 80.11%(10.57%) 69.54% 18(18)

Odisha 73.45(15.86%) 57.59% 3690(527)

Punjab 76.68%(6.88%) 69.80% 1316(658)

Rajasthan 67.06%(6.20%) 60.86% 2612(522)

Sikkim 82.20%(-1.65%) 83.85% 252(252)

Tamilnadu 80.33%(0.11%) 80.44% 2086(1043)

Telangana 66.5%(3.13%) 63.37% 2738(912)

Tripura 87.75%(2.03%) 85.72% 158(158)

Uttar Pradesh 69.72%(8.83%) 60.89% 5628(703)

Uttarakhand 79.63%(6.36%) 73.27% 1908 (954)

West Bengal 77.08%(7.72%) 69.36% 8202(1640)

Note: 1: State wise literacy rate, 2: Aspirational Districts average literacy rate/ Average literacy

rate of Aspirational Districts-state wise, 3: Total outlets in Aspirational Districts-state wise, 4:

Difference between state wise literacy rate and Aspirational Districts wise average literacy

rate/Difference in literacy rate, 5: Average number of outlets in an Aspirational District of a

state/ Total no of outlets in average.

Following result is presented from Table 3

Andhra Pradesh, Maharashtra, Tamil Nadu and West Bengal has highest average no of formal

banking outlets in an Aspirational District, the common reason may be all these four states have

high agricultural and industrial development; which economically sustain the banking outlets,

apart from these states are also economically strong which causes adequate fund disbursement to

the backward areas and also creation of demand for rural products. In comparison to this North

Eastern and Himalayan states are supported by very small no of formal banking outlets, as they

are mostly covered by rugged topography and are sparsely populated on one hand and on other

hand their economy is not so strong to sustain large no of banking outlets, apart from internal

disturbances.


4. Correlation between Average literacy rate of Aspirational Districts-state wise and Total no of

outlets in average. is -0.21811



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The relation is negative and low, still possible reason is many large states are having low literacy

rate but more no of branches and just opposite happens for some small and unfavourable climatic

condition related states. Still there is some exceptions.

5. Correlation between Difference in literacy rate and State wise literacy rate is 0.033869

No meaningful correlation exist.

6. Correlation between Difference in literacy rate and Total no of outlets on an average in an

Aspirational District of a state -0.05297


PERCENTAGE OF ACTIVE BANK MITRAS, DISTRICTS WISE AND SOCIAL

PROGRESS

Table-4.

State 1 2 3

Andhra Pradesh 95.38 56.13 100

Arunachal Pradesh 50.00 55.24 58.40

Assam 94.76 48.53 90.93

Bihar 98.09 44.89 77.50

Chattisgarh 83.16 56.69 97.13

Gujarat 98.75 56.65 99.80

Haryana 92.19 57.37 100

Himachal Pradesh 87.83 65.39 99.53

Jammu & Kashmir 97.72 55.41 98.24

Jharkhand 95.92 47.80 88.46

Karnataka 95.35 59.72 99.95

Kerala 62.00 68.09 100

Madhya Pradesh 89.70 55.03 97.10

Maharashtra 86.70 57.88 99.77

Manipur 75.00 55.50 86.26

Meghalaya 53.85 53.51 66.45

Mizoram 80.00 62.89 87.99



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Nagaland 42.86 56.76 67.76

Odisha 77.70 51.64 76.48

Punjab 95.96 62.18 100

Rajasthan 93.21 52.31 95.05

Sikkim 75.00 62.72 94.44

Tamilnadu 97.14 65.34 100

Telangana 92.93 56.13 66.32

Tripura 94.44 53.22 88.27

Uttar Pradesh 91.65 50.96 88.27

Uttarakhand 89.09 64.23 98.93

West Bengal 99.10 54.37 99.52

Note: 1: Percentage of active Bank Mitras in Aspirational Districts-state wise/State wise

percentage of Active Bank Mitras , 2: Social Progress Index state wise, 3: Village electrification

state wise.

Social Progress Index has been calculated by taking into account following parameters: a) Basic

Human Needs b) Foundations of Wellbeing c) Opportunity, all three main parameters have equal

weight in determining the above Social Progress Index. Social Progress Index calculations put

6% weight on Rural Electrification and financial inclusion.

Table 4 represent following results.

West Bengal, Bihar and Gujarat are best performing states whereas Arunachal Pradesh,

Nagaland and Meghalaya are worst performing states. Possible reasons are level of economic

and social development, topography and peace of the region.


7. Correlation between Social Progress Index and Rural electrification is .40553

The above correlation is positive and medium, the correlation is positive because more a place is

electrified it will possess more social capital and automatically it will have more social progress

and economic strength and thereby banking penetration.

8. Correlation between State wise percentage of Active Bank Mitras and Social Progress Index is

-0.17104

Though the correlation is insignificant and small, still there lies a negative relation between the

two parameter. The possible reasons may be some areas which are less socially progressive but

more economically progressive and sustain more financial outlets, Northeastern states, Kerala

and Himachal Pradesh having good social progress but are less financially included and get less

government’s attention.



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9. Correlation between State wise percentage of Active Bank Mitras and Rural electrification is

.622908

There exist a large correlation between the above two parameters, it is very common more a area

is electrified it is more favourable for Bank Mitras to perform.

Some other correlations based on table from 1 to 4:

State Wise:

10. Correlation between State wise percentage of Active Bank Mitras (Table4) and Aspirational

Districts literacy rate(average)( Table 3) is

-0.2427

There is a negative correlation between the above parameters and correlation is low. Possible

reasons may be the places which are more economically strong than literally and have adequate

government funding can support more outlets. Hilly states and some southern states having good

social progress but less financially included due to less economic wellness and inadequate

government funding.

11. Correlation between Total no of outlets in average (Table 3). And state wise percentage of

Active Bank Mitras (Table4) is 0.55849

The above correlation is positive and very strong , it is because places which are economically,

socially more developed they are served by more no of Bank Branches and Bank Mitras and

Banking Correspondents are based on bank branches, so its automatically increases no of Bank

Mitras in a place.

12. Correlation between Total no of outlets in avg.(Table 3) and Social Progress Index is(Table

4) -0.03189


13. Correlation between Total no of outlets in average (Table 3) and Rural electrification (Table

4) is 0.38358

This correlation is positive and medium, it is very common, more a place is electrified more it is

favourable for banking outlets to function and also helps in economic wellbeing.

14. Correlation between Average literacy rate of Aspirational Districts-state wise and (Table 3)

State wise percentage of Active Bank Mitras (Table 1) is -0.2427

Correlation is low and negative, still the possible reasons may be; many places are economically

strong but have low literacy rate and financial inclusion depends mainly on economic condition

of a place for eg, Punjab, Haryana, and Maharashtra; whereas Himalayan, North Eastern and

some southern states are reverse in situation.



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Social Progress Index (Table 4) is 0.598054

This ratio is highly significant and positive, as because more a place is literate more it will be

socially progressive as literacy is one of the parameter in determining social progress.


Rural electrification (Table 4) is 0.130297

Correlation is positive and low, it is positive because more electrification to some extant ensures

higher literacy rate but it is low because many Himalayan state and northeastern states are not

electrified but literate to a large extent and many large states like Punjab, Haryana, Maharashtra,

West Bengal are more electrified than literate. Economic wellbeing is related to a great extant

with electrification but very less extant depends on social progress.

17. Correlation between Difference in literacy rate (Table 3) and Social Progress Index (Table 4)

is -0.04269


18. Correlation between Difference in literacy rate(Table 3) and Active Bank Mitras(Table 1)

0.067841.


District wise:-

19. Correlation between Bank branch (Table 2) and Total fixed location Bank Mitras(table 1) is

0.403603

The above correlation is positive and moderate because more a backward district is economically

developed more no of Bank Branches operate there profitably and rural areas of those districts

are comparatively more developed economically than rural area of those back ward districts

which are not so economically developed, hence more no. of Bank Branches can successfully

deploy more number of Bank Mitras in those rural areas.

20. Correlation between Bank Branch (Table 2) and Active Bank Mitras(Table 1) is 0.496088

The above correlation is positive and moderate because more a backward district is economically

developed more no of Bank Branches operate there profitably and rural areas of those districts

are comparatively more developed economically than rural area of those backward districts

which are not so economically developed, hence more number of Bank Branches can

successfully deploy more number of Bank Mitras in those rural areas. Automatically more the

rural arte are economically sound more they can sustain active Bank Mitras and on opposite

highly backward districts not only have less number of Bank Branches but also less no of active

Bank Mitras in rural area as it is unprofitable for Bank Mitras to remain active in poor economic

condition. West Bengal, Punjab, Tamil Nadu, Karnataka, Gujarat, J&K and Andhra Pradesh has



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higher percentage of Active Bank Mitras whereas Arunachal Pradesh, Meghalaya, Nagaland and

Kerala has lower percentage of Active Bank Mitras. For Kerala reason may be, government

funding is not adequate and recent economic slowdown of Kerala.

CONCLUSIONS:-

From the overall point of view after doing above analysis it can be summarized as.

Backward districts of Andhra Pradesh, Maharashtra, Tamil Nadu and West Bengal,Bihar and

Punjab are most financially included; whereas North Eastern states, states of Kerala, Chattisgarh

and Odisha are least financially included and determining factors are level of industrial and

agricultural development, topography, government funding and peace of the region. Himalayan

states hugely depend on tourism, like Himachal Pradesh, Jammu & Kashmir and Uttarakhand

perform moderately due to good economic condition for tourism. Jharkhand though a financially

poor state, have disturbances, bad transport and low electrification still have moderate financial

inclusion due to good government funding. Rest of the states performed more or less moderately

in respect to financial inclusion of their backward districts and it is very much in per with their

level of industrial and agricultural development and no specific reason exists for economic

wellbeing in their backward districts, which ensures financial inclusion.

There is no solid relation exist between social progress or literacy on one hand and economic

condition on other hand. Financial inclusion is better in states with better economic condition,

good transport infrastructure, which are under more Govt. schemes and have good electrification.

Literacy rate or Social Progress Index has least impact on financial inclusion. Fund allocation by

a state government for backward districts wellbeing has also positively impacted financial

inclusion of those areas.

Financial inclusion of all backward districts of all states are not equal; it has been affected by

economic and geographical conditions mainly apart from Government initiatives.

As Bank Branches basically deployed Banking Correspondents, Bank Mitras and ATMs, urban

area of districts with higher number of bank branches have more Banking Correspondents, Bank

Mitras and ATMs in rural areas of those districts than urban area of districts with lower number

of Bank Branches.

It has been observed through the study that places which are more financially excluded are also

more financially week. Most of the commercial banks or other banks operated in the backward

districts are all perform their desired activities if only they can earn desired profit to operate.

There is difference in level of economic development among backward districts of different

states. States which are developed economically; their backward districts are more financially

included than backward districts of states which are financially week. For which backward areas

which are highly backward their financial inclusion remain constant or deteriorate, whereas those

backward areas which are comparatively wealthy are becoming more and more financially

included.

It is a good sign that government has identified backward districts for their overall development.

It can be expected that government will take desired steps for quick development of those areas



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before 2022. Still backward districts identified by government in different states are not so

logical, many so called backward districts of different states have been left over.

RECOMMENDATIONS:-

1. The government should look at equitable economic and social development of all the

backward districts, without economic development it is impossible to enhance financial inclusion

of those places.

2. Government should develop social infrastructure in rural areas so that it can ensure their

overall development.

3. Government should spread adequate awareness among peoples of backward districts regarding

benefit of formal financial institutions, as they are mostly illiterate regarding financial inclusion.

4. Government should allocate more fund for financial inclusion in backward districts of those

states which are less financially included.

LIIMITATIONS:-

1. The study is based on secondary data.

2. Study has been conducted from very few angles, more detailed study can be done based on

other parameters.

3. Lack of past study regarding this topic is a problem for getting idea regarding how this study

can be conducted

4. Statistical applications used in this study are very basic and small.

REFERENCES:-

1) Archived Official Website of Planning Commission.

2) Bedi, A.(September 2015). Recent Vision of Financial Inclusion in India. (International Journal of

Advance Research in Computer Science and Management Studies)IJARCSMS.

3) Bhanot, D., Banat V.& Bera S.(September 2012). Studying financial inclusion in north‐east

India. (International Journal of Bank Marketing) Emerald Group Publications.

4) Business wire India, official website.



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5) “Central transfers to states in India rewarding performance while ensuring equity” the report

sponsored by and submitted to NITI Aayog and authored by M. Govinda Rao.

6) Hindustan Times.

7) Office of the Registrar General & Census Commissioner, India.

8) Official Website of ministry of finance (under Jan Dhan Yojna data).

9) Official Website of NITI Aayog.

10) Rural Financial Inclusion Survey 2016-2017, NABARD

11) Sahoo, A.K., Pradhan, B. B.& Sahu, N. C.(February-2017). Determinants of Financial

Inclusion in Tribal Districts of Odisha: An Empirical Investigation. (Social Change journal)

SAGE Publications.

12) Shastri, A.(December 2014). Financial inclusion in Madhya Pradesh, a study with reference

to rural population. (Journal of Business Management and Social Sciences Research) Blue

Ocean Publications.

13) Singh, R.I.(May-June 2015). Perceptions of People from Economically Backward Section

towards Financial Inclusion: An Empirical Study of Ludhiana District Singh.(Journal of

Economics and Finance) International Organization of Scientific Research Publications.

14) Socio-Economic Caste Census 2011..

15) The Economic Times.

16) The Hindu.

17) The Times Of India.

18) Various Official Websites of different state governments.



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