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A Market Research on
Consumer awareness and
usage of MOBILE BANKING

                         BY
                  GROUP - 14
M - Banking
Mobile banking - used for performing balance
checks, account transactions, payments, credit
applications and other banking transactions
through a mobile device


Apple's success with iPhone and the rapid
growth of phones based
on Google's Android have led to an increased
use of special client programs, called
apps, downloaded to the mobile device.
Change in the Telecom Sector


                 Mobile subscribers reaching an 800 million
                  mark.

 Trends in       Of total population of 1210 million, approx
                  295 million is Urban population.
the Telecom
  Industry       Out of that only 43 million are mobile
                  banking users.
                 Wireless Subscribers to reach 893 million by
                  2012/13
Methodology
Universe of the Study
• Urban Mobile users in India
• Assumption – Internet Access in all mobile phones
Locale of the Study
• Urban Mobile users having bank accounts

Sample of the Study
• Convenient sampling – friends and relatives
• Respondents were approached through a questionnaire
• 48 people responded from Delhi
Description of the Sample
       Age Group                                    Bank Account
 26                                            2
       25
 25                  23
 24                                                                                        Yes
       25
 23                                                          46                            No
                     23
 22
      19-25         26-35



           Gender                                     Occupation
                                   25                                                 22
                                                          20
                                   20
      10                           15
                          Male     10
                                             6
              38          Female    5
                                                                          0
                                   0
                                        Public Sector Private Sector Self Employed   Student
Description of the Sample
Have a Mobile Phone              Mobile Internet Service
     1
                                       9
                      Yes                                  Yes
                      No                                   No
         47
                                             39


                   M-Banking Service

                            13

                                             Yes
              35                             No
Reasons for Not Using M-Banking Service
 35
 30
 25
 20
 15
 10                                 Preference 7
                                    Preference 6
  5
                                    Preference 5
 0                                  Preference 4
                                    Preference 3
                                    Preference 2
                                    Preference 1
Population with Bank Account
According to statistics, 70 % of urban
population has bank accounts.


                4%


                             Have Bank Account

                             No Bank Account



                 96%
Hypothesis: Population with Bank
Account
                                p = 0.70 (70 % of urban population has
                                bank accounts.)
            1.04 (1 being yes
Mean        and 2 being no)
                                n = 48, þ^ =0.96

Variance          0.04

Standard                        α = 0.05
                  0.20
Deviation

                                H₀: þ = 0.70 ; Ha: þ > 0.70 (single tail)


                                Z from table = 1.645


                                Z observed value = 3.9
Rejection Region
Non - Rejection Region




                              3.9
Minitab output
 Test of p = 0.7 vs p > 0.7
                                      95% Lower
 Exact
 Sample X         N    Sample p       Bound P-Value
 1     46        48    0.958333      0.874586 0.000


Therefore we reject the null hypotheses. Percentage of
urban population having bank account is more than
70%.
Population using M-Banking
According to statistics, 43 million out of 310
million urban population use mobile banking i.e.
15%



                             Use Mobile Banking
                27%
                             Do not Use M-Banking

        73%
Hypothesis: Population using
  M-Banking
                                    p = 0.15
            1.729167 (1 being yes
 Mean
               and 2 being no)      n =48, þ^ = 0.27

Standard
                 0.449093           α = 0.05
Deviation

                                    H₀: þ = 0.15, Ha: þ ≠ 0.15 (double tail)
Sample
                 0.201684
Variance
                                    Z from table = 1.96

                                    Z observed value is 2.32
Rejection Region                            Rejection Region
                   Non - Rejection Region




                                                2.32
Minitab output
Test and CI for One Proportion

Test of p = 0.15 vs p not = 0.15

                                                       Exact
Sample    X    N   Sample p          95% CI          P-Value
1        13   48   0.270833   (0.152782, 0.418456)     0.040




 Here we see that population proportion is very close
 to the confidence interval starting from .152.
 therefore we do not reject the null hypothesis.
Female Population using M-
Banking
According to statistics, 15 % of 43 million active
mobile banking urban population is female.



                 20%              Use M-Banking


                                  Do Not Use M-
                                  Banking
          80%
Hypothesis: Female Population
 using M-Banking
p = 0.15

n =10, þ^ = 0.20

α = 0.05

H₀: þ = 0.15; Ha: þ ≠ 0.15 (double tail)

Z from table = 1.96

Z observed value is 0.44
Rejection Region                            Rejection Region
                   Non - Rejection Region




                                  0.44
Minitab output
Test and CI for One Proportion

Test of p = 0.15 vs p not = 0.15

                                                     Exact
Sample   X    N   Sample p          95% CI          P-Value
1        2   10   0.200000   (0.025211, 0.556095)     1.000




Therefore we do reject the null hypotheses.
Percentage of urban population having bank
account and is female is 15%.
Primary Service
According to statistics, 90% of 43 million active
mobile banking urban population primarily use it to
check their account balance.




                  21%          Use Mobile Banking


                               Do Not Mobile
                               Banking

         79%
Hypothesis: Primary Service

p = 0.90

n =48, þ^ = 0.85

α = 0.05

H₀: þ = 0.90, Ha: þ ≠ 0.90 (double tail)

Z from table = 1.96

Z observed value is -1.155
Rejection Region                                 Rejection Region
                        Non - Rejection Region




                   -1.155
Minitab output
Test and CI for One Proportion

Test of p = 0.9 vs p not = 0.9

                                                       Exact
Sample    X    N   Sample p          95% CI          P-Value
1        41   48   0.854167   (0.722362, 0.939296)     0.329



Therefore we do not reject the null hypotheses.
90% of urban mobile banking users use it to check
their account balance.
Two Sample Test
We conducted a separate survey on usage of mobile
banking primarily from people in Chandigarh. We got
33 responses with following results.



                  21%
                                Use Mobile Banking

                                Do Not Mobile
                                Banking

          79%
Hypothesis: Two Sample Test
H₀: þ1 – p2 = 0; Ha: þ1 – p2 ≠ 0                          n       33
(Double tail)                      n
                                   1
                                           48             2


                                   X   1
                                           13             X   2
                                                                      7
α = 0.05                                                              7
                                   ˆ
                                   p
                                           13
                                                .27       ˆ
                                                          p
                                                          2           33
                                                                               .21
                                   1       48
Z from table = 1.96

                                                ˆ ˆ
                                                p p
                                                1     2   P P     1            2
                                   Z
            P    X X 1        2
                                                    P Q
                                                          1            1
                 n n 1    2                               n n 1            2

                 12.96 6.93                         .27 .21            0
                    48 33                                         1            1
                                                .245 .754
                 .245                                             48           33
                                            0.61
Two Sample Test
Test and CI for Two Proportions

Sample    X    N   Sample p
1        13   48   0.270833
2         7   33   0.212121

Difference = p (1) - p (2)
Estimate for difference: 0.0587121
95% CI for difference: (-0.129063, 0.246487)
Test for difference = 0 (vs not = 0): Z = 0.61      P-
  Value = 0.540

 As p value is greater than α = 0.05 therefore do
 not reject the null hypothesis. Both the samples
 satisfy the null hypothesis.
Confidence Interval to Estimate
P1 - P2
               ˆˆ ˆˆ
               pq p q                                       ˆˆ ˆˆ
                                                            pq p q
 ˆ ˆ
 p p       Z   1 1
                          ˆ ˆ
                      P P p p
                      2       2
                                  1     2
                                                        Z   1 1   2       2
 1     2
               n n
                1         2
                                              1     2
                                                            n n
                                                             1        2


                     0.126        P P
                                  1     2
                                            0.245


     We get:

     Which is same as given by Minitab Solution i.e.
     95% CI for difference: (-0.129063, 0.246487)
Limitations of the study

Drawing descriptive or inferential conclusions from sample data about
a larger group.

The study has limitation as the data were collected only form urban
customers so the results cannot be generalized to pan India population.

The data has mainly been collected from respondents from age groups
of 19 to 35 years and cannot be generalised for whole population.

Responses did not cover all banks providing the survey which may
result in not revealing the true picture.
Further Scope of the study

The sample size could be increased to give more accurate results.

A cross-regional research could be done to cover Pan India
which would help in achieving a better picture.

Data from all age groups can be collected.

Data covering all banks providing the service can be included in
the research.

In depth analysis can be done by including more parameters in
research earlier constrained due to time limitation.
Thank you

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M banking

  • 1. A Market Research on Consumer awareness and usage of MOBILE BANKING BY GROUP - 14
  • 2. M - Banking Mobile banking - used for performing balance checks, account transactions, payments, credit applications and other banking transactions through a mobile device Apple's success with iPhone and the rapid growth of phones based on Google's Android have led to an increased use of special client programs, called apps, downloaded to the mobile device.
  • 3. Change in the Telecom Sector  Mobile subscribers reaching an 800 million mark. Trends in  Of total population of 1210 million, approx 295 million is Urban population. the Telecom Industry  Out of that only 43 million are mobile banking users.  Wireless Subscribers to reach 893 million by 2012/13
  • 4. Methodology Universe of the Study • Urban Mobile users in India • Assumption – Internet Access in all mobile phones Locale of the Study • Urban Mobile users having bank accounts Sample of the Study • Convenient sampling – friends and relatives • Respondents were approached through a questionnaire • 48 people responded from Delhi
  • 5. Description of the Sample Age Group Bank Account 26 2 25 25 23 24 Yes 25 23 46 No 23 22 19-25 26-35 Gender Occupation 25 22 20 20 10 15 Male 10 6 38 Female 5 0 0 Public Sector Private Sector Self Employed Student
  • 6. Description of the Sample Have a Mobile Phone Mobile Internet Service 1 9 Yes Yes No No 47 39 M-Banking Service 13 Yes 35 No
  • 7. Reasons for Not Using M-Banking Service 35 30 25 20 15 10 Preference 7 Preference 6 5 Preference 5 0 Preference 4 Preference 3 Preference 2 Preference 1
  • 8. Population with Bank Account According to statistics, 70 % of urban population has bank accounts. 4% Have Bank Account No Bank Account 96%
  • 9. Hypothesis: Population with Bank Account p = 0.70 (70 % of urban population has bank accounts.) 1.04 (1 being yes Mean and 2 being no) n = 48, þ^ =0.96 Variance 0.04 Standard α = 0.05 0.20 Deviation H₀: þ = 0.70 ; Ha: þ > 0.70 (single tail) Z from table = 1.645 Z observed value = 3.9
  • 10. Rejection Region Non - Rejection Region 3.9
  • 11. Minitab output Test of p = 0.7 vs p > 0.7 95% Lower Exact Sample X N Sample p Bound P-Value 1 46 48 0.958333 0.874586 0.000 Therefore we reject the null hypotheses. Percentage of urban population having bank account is more than 70%.
  • 12. Population using M-Banking According to statistics, 43 million out of 310 million urban population use mobile banking i.e. 15% Use Mobile Banking 27% Do not Use M-Banking 73%
  • 13. Hypothesis: Population using M-Banking p = 0.15 1.729167 (1 being yes Mean and 2 being no) n =48, þ^ = 0.27 Standard 0.449093 α = 0.05 Deviation H₀: þ = 0.15, Ha: þ ≠ 0.15 (double tail) Sample 0.201684 Variance Z from table = 1.96 Z observed value is 2.32
  • 14. Rejection Region Rejection Region Non - Rejection Region 2.32
  • 15. Minitab output Test and CI for One Proportion Test of p = 0.15 vs p not = 0.15 Exact Sample X N Sample p 95% CI P-Value 1 13 48 0.270833 (0.152782, 0.418456) 0.040 Here we see that population proportion is very close to the confidence interval starting from .152. therefore we do not reject the null hypothesis.
  • 16. Female Population using M- Banking According to statistics, 15 % of 43 million active mobile banking urban population is female. 20% Use M-Banking Do Not Use M- Banking 80%
  • 17. Hypothesis: Female Population using M-Banking p = 0.15 n =10, þ^ = 0.20 α = 0.05 H₀: þ = 0.15; Ha: þ ≠ 0.15 (double tail) Z from table = 1.96 Z observed value is 0.44
  • 18. Rejection Region Rejection Region Non - Rejection Region 0.44
  • 19. Minitab output Test and CI for One Proportion Test of p = 0.15 vs p not = 0.15 Exact Sample X N Sample p 95% CI P-Value 1 2 10 0.200000 (0.025211, 0.556095) 1.000 Therefore we do reject the null hypotheses. Percentage of urban population having bank account and is female is 15%.
  • 20. Primary Service According to statistics, 90% of 43 million active mobile banking urban population primarily use it to check their account balance. 21% Use Mobile Banking Do Not Mobile Banking 79%
  • 21. Hypothesis: Primary Service p = 0.90 n =48, þ^ = 0.85 α = 0.05 H₀: þ = 0.90, Ha: þ ≠ 0.90 (double tail) Z from table = 1.96 Z observed value is -1.155
  • 22. Rejection Region Rejection Region Non - Rejection Region -1.155
  • 23. Minitab output Test and CI for One Proportion Test of p = 0.9 vs p not = 0.9 Exact Sample X N Sample p 95% CI P-Value 1 41 48 0.854167 (0.722362, 0.939296) 0.329 Therefore we do not reject the null hypotheses. 90% of urban mobile banking users use it to check their account balance.
  • 24. Two Sample Test We conducted a separate survey on usage of mobile banking primarily from people in Chandigarh. We got 33 responses with following results. 21% Use Mobile Banking Do Not Mobile Banking 79%
  • 25. Hypothesis: Two Sample Test H₀: þ1 – p2 = 0; Ha: þ1 – p2 ≠ 0 n 33 (Double tail) n 1 48 2 X 1 13 X 2 7 α = 0.05 7 ˆ p 13 .27 ˆ p 2 33 .21 1 48 Z from table = 1.96 ˆ ˆ p p 1 2 P P 1 2 Z P X X 1 2 P Q 1 1 n n 1 2 n n 1 2 12.96 6.93 .27 .21 0 48 33 1 1 .245 .754 .245 48 33 0.61
  • 26. Two Sample Test Test and CI for Two Proportions Sample X N Sample p 1 13 48 0.270833 2 7 33 0.212121 Difference = p (1) - p (2) Estimate for difference: 0.0587121 95% CI for difference: (-0.129063, 0.246487) Test for difference = 0 (vs not = 0): Z = 0.61 P- Value = 0.540 As p value is greater than α = 0.05 therefore do not reject the null hypothesis. Both the samples satisfy the null hypothesis.
  • 27. Confidence Interval to Estimate P1 - P2 ˆˆ ˆˆ pq p q ˆˆ ˆˆ pq p q ˆ ˆ p p Z 1 1 ˆ ˆ P P p p 2 2 1 2 Z 1 1 2 2 1 2 n n 1 2 1 2 n n 1 2 0.126 P P 1 2 0.245 We get: Which is same as given by Minitab Solution i.e. 95% CI for difference: (-0.129063, 0.246487)
  • 28. Limitations of the study Drawing descriptive or inferential conclusions from sample data about a larger group. The study has limitation as the data were collected only form urban customers so the results cannot be generalized to pan India population. The data has mainly been collected from respondents from age groups of 19 to 35 years and cannot be generalised for whole population. Responses did not cover all banks providing the survey which may result in not revealing the true picture.
  • 29. Further Scope of the study The sample size could be increased to give more accurate results. A cross-regional research could be done to cover Pan India which would help in achieving a better picture. Data from all age groups can be collected. Data covering all banks providing the service can be included in the research. In depth analysis can be done by including more parameters in research earlier constrained due to time limitation.