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Smart Banking in Smart Cities

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MUKESH PATEL SCHOOL OF TECHNOLOGY MANAGEMENT AND

ENGINEERING

 

 

 

SVKM’S NMIMS

 

 

 

 

Smart Banking in Smart Cities

 

 

 

 

A Secondary Research submitted in partial fulfilment

Of the requirements for the degree of

MBA (Tech)

 

 

 

 

 

By

Shrey Gupta (C041)

 

Puleen Gupta (C042)

 

Harpreet Singh Khalsa (M073)

 

Saurabh Singh (M091)

 

 

Under Supervision

Of

Dr. Anuja Agarwal

 

 Year of Graduation (e.g. 2017)

1.)   Introduction

This research project aims at finding the possible services and attributes that may be desired by the citizens or customers which may or may not be residing in Smart Cities.

The concept of smart cities is in an evolving phase. The concept can be made a reality or close to reality is by developing solutions which have been developed by keeping customer’s opinions and views in mind.

1.1) Purpose

The purpose of this data analysis is to find out the factors of the success of the concept of smart banking. This also aims to find out the relationship between the different variables that affect this success factor as well as the extent to which the variable affect the other. This data analysis would also help us to forecast the future usage and spending trends.

1.2) Hypothesis

1.        Cashless and Digital banking will enable smart banking

2.      Smart Loans with the help of technology may enhance the facilities served by smarter banking.

3.        Transparency in banks will also lead to evolution of methods towards smarter banking.

4.      Enabling an electronic portal for document sharing to enable faster access to proper documents.

5.      The methods like e-cheque will lead to make banking smarter.

6.      Better banking systems will also lead to efficient and smarter cities.

1.3) Key Documents

Various other research papers, news reports, research reports were accessed to determine the variables revolving around the concept of smart banking such as cashless banking, integrated identities and payments solutions.  

 

2.)   Methodology

Data was collected from 171 observant through a set of questions. These questions were framed keeping in mind the variables and the hypotheses framed. The questionnaire comprised of questions about their payment behaviour, their likeliness of using proposed services and their current banking activities patterns.

These questionnaire was filled by a variety of respondents. It included people age groups ranging from 18-25 to 41-60 and above 60 and students to service-based employees to businessmen. This helped us to have a variety of answers to our questions to better understand the relations between the variables.

The answers to the questionnaire were then converted to the required scales to appropriately use the analysis tools such as Correlation and ANOVA and regression.

We made the following scales for the analysis of data

Gender: Male: 1           Female: 0

Age: 18, 21.5, 33, 50, 60

Occupation: Student: 0, Housewife: 5, Service: 10, Freelancer: 15, Business: 20

Annual income values :50,000 , 1,00,000 , 3,50,000 , 9,00,000 , 15,00,000

These were our values for the independent values.

3.)   Results

These were the following relationships between the data we were able to find out.

  1. Cashless Transactions

        The following graph shows the relationship between the annual income and the usage of cashless transactions.

[pic 1]

The following graph shows the relationship between the age and the usage of cashless transactions.

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